Archive of Funded Research

Expand all
A Deep Learning Approach for Solving Network Security Problems

Yuval Shavitt, School of Electrical Engineering, TAU

A Machine Learning Collaborative Study of Language-Action Cues for Spontaneous Deceptive Communication, and Cyber-Ontology Development

Prof. Oded Maimon, Department of Industrial Engineering, TAU

Prof. Shuyuan Mary Ho, College of Communication & Information at Florida State University, USA.

In this study, the use of deceptive language is being examined and language usage patterns during online deceptive acts explored. As interpersonal communication is defined as a dynamic exchange of messages between or among two or more people, the research focuses on social interactions where participants try to mutually influence each other in a dynamic fashion. The investigators are thus seeking an answer to the following research question: what linguistic cues can be attributed to deception in a computer mediated communication across a pluralistic background of users?

A Novel Technology for Detecting Deceptive Behavior

Dr. Dino Levy, Coller School of Management, TAU

Prof. Yael Hanein, School of Electrical Engineering, TAU

The goal of the proposed research is to develop and test a novel autonomous system to detect deception in videos, based on the integration of unique physiological recordings and machine learning algorithms. This approach has direct online applications in ticket purchases, online meetings, job interviews, loan applications, and other situations where online deceptive communication might appear and security is important.

Adapting QC and MEC Algorithms to Anomaly Detection in Big Data

Prof. David Horn, School of Physics and Astronomy, TAU

The Quantum Clustering (QC) algorithm has been developed by us in 2001 and proved to be very successful in various applications. Over the past few years we have demonstrated that its generalization, DQC, can handle well big data and discover unexpected features in them. Here we propose to further develop QC, and our recently discovered Maximal Entropy Clustering (MEC), to be able to apply both to big data with the particular purpose of anomaly detection. This will hopefully turn out to be a useful tool for anomaly detection in cyber data.

Advanced Attacks Against Internet Security Protocols

Prof. Yuval Shavitt, Faculty Member, School of Electrical Engineering, TAU

We have recently presented DROWN [Usenix'16], a novel cross-protocol attack that can decrypt passively collected TLS sessions from up-to-date clients by using a server supporting SSLv2 as a Bleichenbacher RSA padding oracle. We suggest in this proposal multiple extensions to this research direction and, in particular, we will try to mount new attacks against modern cryptographic protocols, especially TLS, using our new approach, which is significantly different from classical Bleichenbacher attacks.

AI Based Man in the Middle Attacks

Amir Globerson, Blavatnik School of Computer Science, TAU

Dr. Matan Gavish, School of Computer Science & Engineering, HUJI

The field of artificial intelligence has made great strides in the last decade. Much of this progress is due to artificial neural network models (also known as deep-learning) that have achieved state of the art results in applications such as face recognition, image understanding, translation and speech recognition.

Alternative Enforcement in Cyber Space

Dr. Haim Wismonski, TAU

The proposed research question is: How to properly run an alternative legal measure in order to defend against damage caused by criminal offenses in cyberspace, alongside the measures taken today as part of the "classical" criminal investigation in cyberspace.

Anomaly Detection for Critical Infrastructure Protection: Second Generation

Amir Averbuch, Blavatnik School of Computer Science, TAU

The primary goal of this proposal is to develop methodologies (theories, algorithms, software and systems) to detect anomalies in an unstructured HDBD, which can be the underlying signs of malware, zero day attacks or operational malfunctions, or both, that can impact critical infrastructure.

Anonymous and Secure Electronic Voting Protecting our Democratic Infrastructure

Prof. Amnon Ta Shma, Blavatnik School of Computer Science, TAU

Prof. Alon Rosen, Efi Arazi School of Computer Science, IDC

The investigators believe the transition to electronic voting is inevitable and that there is no alternative to software-independent voting. They are studying the delicate security issues involving electronic voting and the money needed for implementing and testing such a system.

Attack Resilient Resource Placement in Cloud Computing System and Power Grid

Dr. Hanoch Levy, Blavatnik School of Computer Science, TAU

This research will extend the methodology and devise algorithmic solutions which will provide resource placement strategies that will be efficient and optimal with respect to malicious environments. In the context of cloud computing, the investigators will capture the votality of the resources, namely the L_i variables, as random variables, whose value depends on the number of resources the designer placed in the i-th site as well as on the probability that they fail (due to attacks).

Attack Resilient and Efficient DNS Infrastructure

Yehuda Afek, Blavatnik School of Computer Science, TAU

Prof. Anat Bremler-Barr, Efi Arazi School of Computer Science, IDC

Daniel Dubnikov

The DNS developers' community is struggling in recent years to make the DNS system resilient to various attacks while maintaining its efficiency and authenticity; however, there seems to be a cycle, each new fix has introduced a new vulnerability. Our goal is to cut the cycle proposing a solution that eliminates key vulnerabilities without enabling new ones. We believe we found a sweet spot design that disables DNS poisoning attacks [31, 32] without opening the door to new attacks such as zone walking [20, 21] or DDoS amplification attacks. DNSSEC is the main tool used to stop DNS poisoning and ensure the DNS replies authenticity; it employs asymmetric cryptography to sign DNS responses.

Automatically Verifying User Kernel Extensions

Prof. Mooly Sagiv, Blavatnik School of Computer Science, TAU

Prof. Noam Rinetzky, Blavatnik School of Computer Science, TAU

Dr. Aurojit Panda, Department of Computer Science, NYU, USA

Symbolic techniques for reasoning about programs have drastically advanced in the last three decades. We propose to develop novel techniques for harnessing symbolic techniques for proving the safety of dynamically loaded user-programs extending operating system kernels, thus ensuring that the integrity of the operating system is preserved.


Avionic Bus Cyber Attack Identification

Avishai Wool, School of Electrical Engineering, TAU

Gabi Shugul

Raz Tikochinski

Avionics bus cyber-attack identification is an embedded cyber solution research project, designed to detect and protect common military avionic buses, in use onboard transport a/c, helicopters, trainers and fighter aircrafts around the world. It will address the Blavatnik ICRC 2016 call for research for the topic: "Hardware and embedded systems security, security of IOT". This proposal is for a joint research of Prof. Avishai Wool (TAU faculty of Engineering) and Astronautics C.A. Ltd. (an Israeli company specializing in avionics and military electronics).


Balancing National Security and Privacy Rights to Privacy and the Rule of Law in Democratic Societies, a Comparative Analysis

Adv. Deborah Housen-Couriel

This research focuses on the means of defense against and the effects of the cooperation between shields and the attack on the decision making system.

Best Practices for Verifiability-Correct Concurrent Systems

Noam Rinetzsky, Blavatnik School of Computer Science, TAU

Sharon Shoham, Blavatnik School of Computer Science, TAU

Concurrent systems software--such as operating system kernels, hypervisors, database engines, web servers and language run-times--forms the foundation of any modern computer system. It is extremely complex and hard to get right, with bugs making whole services unavailable or opening the doors of seemingly secure systems to viruses and criminals. Ensuring its reliability is thus imperative for building future trustworthy ICT infrastructures.

Co-Location-Resistant Clouds Security

Prof. Yossi Azar, Blavatnik School of Computer Science, TAU

We propose a model for designing and analyzing \emph{secure} VM placement algorithms, which are online vector bin packing algorithms that simultaneously satisfy certain optimization constraints and notions of security. We introduce several notions of security, establishing a connection between them. We also relate the efficiency of the online algorithm to the cost in the cloud computing.

Competition and Incentives for Information Exchange Regarding Cyber Security Threats

Dr. Noam Shamir, Coller School of Management, TAU

Dr. Hyoduk Shin, Rady School of Management, UC San Diego, USA

In this research proposal we examine in a rigorous manner a few important aspects of the legislation to counter cyber-security threats by sharing information regarding potential cyber-attacks. We first evaluate the claim that a shared database of security-threats benefits the private sector. Second, and more importantly, we evaluate the incentives of a company, operating in a competitive market, to contribute its information regarding cyber-security threats. In this work we highlight a few effects that a company must take into consideration when it reveals information regarding cyber security threats.

Compilation Integrity Assurance through Deep Code Alignment

Prof. Lior Wolf, Blavatnik School of Computer Science, TAU

We propose a completely novel approach for detecting hardware Trojans. We obtain, from the foundry or by other means the binaries. These binaries are expected to largely match the programming code provided by the hardware designer with some unavoidable additions inserted in order to support debugging, QA, and to comply with manufacturing constraints. We then identify for every line of the binaries (viewed as assembly code) the matching line in the original C code. Following this step, we can easily identify insertions and other forms of modifications. The engineers of the supplier company of any other verifying agency can then readily track these modifications and tag each one as malicious or not.

Confess or Deny? Strategies for Dealing with Cyber Attacks

Dr. Deganit Paikowsky, Department of International Relations, HUJI

The proposed research, which aims to yield a book- length manuscript, focuses on practices of cyber deterrence by exploring them in five countries—the US, Israel, Turkey, China and Russia—between the main questions: 1) to what extent and how have these countries adopted a cyber deterrence strategy? 2) Is cyber deterrence an effective strategy, that is, does cyber deterrence affect cyber-attacks, and if so, how?

Crime and IoT

Dr. Roey Tzezana, Blavatnik ICRC, TAU

The investigators suggest developing a better understanding of the security measures and regulations needed to combat new criminals and crimes, by studying the possibilities the IoT holds for criminal acts, conducting expert surveys to estimate timelines for the feasibility of certain crimes, developing high damage-potential scenarios for future crimes and providing the regulators and the Israeli police with policy advice on how to prepare for said crimes.

Cryptographic Proofs of Integrity

Nir Bitansky, Blavatnik School of Computer Science, TAU

Dr. Omer Paneth, Blavatnik School of Computer Science, TAU

This proposal addresses one such central concern, which is verifying the integrity of data and computation in scenarios that involve web entities that we cannot fully trust. Our focus is on developing cryptographic proofs of integrity to handle these scenarios. We study proofs systems with various desirable properties, such as zero knowledge, succinctness, and minimal interaction. We aim toward solutions with a mathematical proof of security based on standard computational assumptions.

Cyber Information Sharing in a Competitive and Conflicted Environment

Mr. Aviram Zrahia, Blavatnik ICRC, TAU

The problem this research addresses is how to reduce the level of objection and increase the level of cyber information sharing between parties in a competitive and conflicted environment. The goal of this research is to develop a model for sharing cyber information in a competitive environment, which could be integrated into existing and evolving sharing methodologies. The importance of this research is in finding a way for competing parties, whether commercial organizations or nations, to enhance their overall cyber-security capability to fight the cyber war by cooperating despite their conflicting interests

Cyber Jihad Taxonomy: A Qualitative Analysis of the Behavior of Jihadi members on Social Networks and the Jihad Subculture They Create

Udi Sommer, School of Political Science, TAU

Gahl Silverman, Blavatnik Research Center, TAU

The proposed study will use a holistic qualitative approach, assisted by a mixed methods analysis software (NVivo11), to apply a two-stage inquiry in order to: (1) identify the characteristics of a potential Jihadi terrorist; (2) identify the taxonomy of the discourse between Jihadi members; and (3) create a categorization of posts and replies that exhibit or inspire an implied preliminary jihadi terrorists’ behavior (see figure 1). The analytic leverage will then allow us to zoom in on the individual level and to draw a multilayered picture of cyber jihad subculture and the basis it sets for broader online terrorist activity

Cyber Security Technology Foresight

Dr. Tal Soffer, School of Education, TAU

The main goal of this study is to derive the current cyber security technology status from the analysis of popular standards such as NERC-CIP. Based on this analysis, a foresight process is being carried out in order to assess future directions and emerging technologies in cyber security, within the time-frame of the next 10-15 years. Attention is being paid also to new cyber-threats that may emerge within this period. The process includes an expert survey that can be repeated and reported on a yearly basis.

Cyber Threats are Self-Regulating Digital Platforms

Gal Oestreicher-Singer, Coller School of Management, TAU

Ohad Barzilay, Coller School of Management, TAU

Hilah Geva, Coller School of Management, TAU

In the proposed research we use state-of-the-art methods and develop novel approaches of our own to study the economic consequences of allowing a digital market to automatically approve sellers who submit products to that market. We aim to provide policy makers and platform stakeholders with new insights regarding the expected revenues and quality shifts that result from a digital platform’s self-regulation

Cyber-Nudging: Incentive Systems and Choice Architectures for Organizational Security

Eran Toch, Industrial Engineering, TAU

Eli Mograbi, Coller School of Management, TAU

In this project, we aim to investigate in nudging mechanisms, that aim to gently push users to safer and more responsible cyber behavior. We plan to design, develop, and evaluate non-monetary incentive systems and nudging mechanisms that have the potential to work in real-world organizations. We will test our designs in experimental conditions, evaluating whether they positively affect the safety behavior of the users while not harming their productivity. We will develop and test a new kind of incentive mechanism, which we call interaction incentives. This type of incentives relies on our ability to make computing experiences more or less usable, based on the behavior of the user. We will combine these incentives with different types of explanations and gamified environments to find out how can we point to safer behavior, without limiting users.

Cyber, Space and Nuclear Weapons Analogies, Interrelations and Differences in Forming National Strategy – A Comparative Analysis of the United States and Russia (USSR)

Dr. Amir Lupovici, School of Political Science, TAU

Dr. Dmitry Adamsky, Lauder School of Government, Diplomacy & Strategy, IDC

This study is aimed at portraying and analyzing major synergies, analogous and anomalies of American and Russian national strategy concerning the three most advanced technological strategic fields: cyber, space and nuclear weapons. It is achieving this by means of mapping the various actors, processes, mechanisms and strategies that influence the forming of American and Russian policy in each of these fields, comparing them and then analyzing the similarities, major differences, and interrelations.

Cybersecurity Theory Development: the Israeli Case in Strategic Context

Dr. Lior Tabansky, Blavatnik ICRC, TAU

The Israeli cyber-defense capability is held in high regard. Could we generalize a roadmap to achieve a consistently excellent state of national cybersecurity from this case? Public discussions on Israeli cybersecurity are, however, usually detached from strategic context, impeding cybersecurity scholarship and policy efforts. We argue that the common explanations of cybersecurity as a by-product of military technology, entrepreneurial skills or innovative ICT sector are only manifestations of other variables. Uncovering the links between the Israeli grand-strategy and its cybersecurity policy will improve analytical tools and have policy implications.

Deep Learning Approach for Solving Network Security Problems

Iftach Haitner, Blavatnik School of Computer Science, TAU

Prof. Kobbi Nissim, Computer Science, Georgetown University, USA

Prof. Dov Gordon, Engineering, George Mason University, USA

Dr. Uri Stemmer, Blavatnik School of Computer Science, TAU

We aim to explore the ways in which secure computation and differential privacy can be composed synergistically to provide utility beyond what either framework alone can provide. In particular, to deepen our understanding of what is feasible, both asymptotically and concretely, for certain key applications of interest.

DeepFuzzing: Breaking the Limits of Traditional Fuzzers with Deep Learning

Lior Wolf, Blavatnik School of Computer Science, TAU

We consider the problem of “Greybox Fuzzing”, e.g effectively fuzzing an endpoint software while guided by the softwares code lines coverage. Our approach incorporates three deep learning models, which are learned concurrently and online while the AI-powered fuzzer runs. The first network predicts the correct code coverage map for a given software input, serving as a differentiable model of the execution process of the given software. The second model generates additional useful seeds that are likely to demonstrate new execution paths of the software. A third network, which is a GAN discriminator, helps to make sure that the samples created by the generator appear valid. Our method is expected to greatly increases the effectiveness of the fuzzer as measured by:(i) the number of bugs found during the process, (ii) the number of code lines that were ultimately covered and (iii) the number of newly discovered execution paths of the software computer Science

Detecting Cryptocurrency Scams and Measuring Cryptocurrency Quality

Prof. Neil Gandal, Economics, TAU

Prof. Marie Vasek, Computer Science, University of New Mexico, USA

We will research two related issues. The first issue involves developing a methodology and using that methodology to detect cryptocurrency scams. The second issue involves examining the relationship between coin quality and success.

Detection of Cyber Attacks in Industrial Control Systems by Intrinsic Sensor Data

Amir Globerson, Blavatnik School of Computer Science, TAU

Matan Gavish, Computer Science and Engineering, HUJI

Ronen Talmon, Electrical Engineering, Technion

Recent years have seen an explosive increase in cyber- attacks against industrial control systems (ICS), including power stations, power grids, dams and water utilities. Cyber-attacks on such systems can have disastrous effects, and any industrialized nation must build an infrastructure for detecting such attacks and deflecting them. In the proposed research we assume the worst- case-scenario in which an attack has already gained control, and even hijacked the sensors of a monitored ICS. We propose to develop a last line of cyber defense: an ICS Takeover Detection System (ICS-TDS), aimed to detect a cyber-takeover of the monitored ICS, even in the presence of successful sensor hijacking.

Differential Privacy and Secure Computation

Iftach Haitner, Blavatnik School of Computer Science, TAU

Prof. Kobbi Nissim, Computer Science, Georgetown University, USA

Prof. Dov Gordon, Engineering, George Mason University, USA

Dr. Uri Stemmer, Blavatnik School of Computer Science, TAU

We aim to explore the ways in which secure computation and differential privacy can be composed synergistically to provide utility beyond what either framework alone can provide. In particular, to deepen our understanding of what is feasible, both asymptotically and concretely, for certain key applications of interest.

Do Firms Under-Report Information on Cyber Attacks? Evidence from Capital Markets

Prof. Eli Amir, Coller School of Management, TAU

Dr. Shai Levi, Coller School of Management, TAU

Firms should disclose information on material cyber- attacks. However, because managers have incentives to withhold negative information, and investors cannot independently discover most cyber-attacks, firms may underreport cyber-attacks. Using data on cyber-attacks that were voluntary disclosed by firms and those that were withheld and later discovered by sources outside the firm, we estimate the extent to which firms withhold information on cyber-attacks. Our results suggest there is underreporting of cyber-attacks, and imply that if regulators wish to ensure that information on attacks reaches investors, they should consider tightening mandatory disclosure requirements.

Dynamics and Geography of the Cybersecurity Industry

Dr. Tali Hatuka, Department of Geography and Human Environment, TAU

Prof. Erran Carmel, Information Technology Department, Kogod School of Business, American University, Washington DC, USA

We are not aware of any academic studies that have taken an in-depth look at the cybersecurity industry nor at its major clusters. Thus, this study will be a first. Our research goals are: First to assess and analyze the emergence and development of the cybersecurity industry, how this industry developed, where, and why it looks as it does today. We will present an historical analysis paying close attention to location decisions. Sources include interviews and secondary literature. Second, to map the geographical spread of the cybersecurity industry using Geographic Information Systems. We will map cybersecurity firms in each cluster in the spatial context, to develop the geography and ecosystem scale; and map the firms spread over time. Third, to analyze the role of key stakeholders in developing the industry using network analysis tools.

Economic Utilization of Workforce-Based Labeling for Security Applications

Dr. Tomer Geva, Coller School of Management, TAU

This research examines the strategic importance and the impact of network structure and the effect of uncertainty and risk aversion on the validity of the negotiating process.

Evolving Cyber-threats and Countermeasures: Mathematical, Behavioral and Legal Perspectives

Prof. Joachim Meyer, Department of Industrial Engineering, TAU

Prof. Ronen Avraham, Faculty of Law, TAU

This research addresses a set of interrelated research questions, combining analytical (optimization), behavioral (experimental economic and psychology) and legal perspectives. From a behavioral modeling perspective the investigators are developing quantitative models to predict users’ behavior in environments with changing threats and information about threats and they are validating the models with empirical studies. Under what conditions will end-users be particularly vulnerable to attacks? What will affect the end-user’s motivation to prevent security threats? The research will then be extended, addressing questions such as, what advice, alerts or nudges can be used so that end-users respond positively to this information, avoiding "cry wolf" and information-overload effects, due to which users cease to respond to indications (Akhawe & Porter Felt, 2013)?

Extracting Signatures and Filters for Zero-day Sophisticated DNS and other DDoS Attacks

Prof. Yehuda Afek, Blavatnik School of Computer Science, TAU

Prof. Anat Bremler-Barr, Efi Arazi School of Computer Science, IDC

With the support of ICRC Blavatnik fund we were able to complete this research successfully and design and develop a new technique and algorithms for distinct heavy hitters (dHH). A (classic) heavy hitter (HH) in a stream of elements is a key (e.g., the domain of a query) which appears in many elements (e.g., requests). When stream elements consist of pairs, () a distinct heavy hitter (dhh) is a key that is paired with a large number of different subkeys. Our algorithms dominate previous designs in both the asymptotic (theoretical) sense and practicality. Specifically the new fixed-size algorithms are simple to code and with asymptotically optimal space accuracy tradeoffs. Based on these algorithms, we build and implement a system for detection and mitigation of Random Subdomain DDoS attacks. We perform experimental evaluation, demonstrating the effectiveness of our algorithms.

Future Crimes Enabled by Blockchain-Based Technologies

Dr. Roey Tzezena, Research Fellow Centered Robotic Initiative (HCRI), Brown University, USA

In this research, we will develop a better understanding of the security measures and regulations needed to combat the new criminals and crimes, by studying the potential criminal acts that blockchain-based technologies could be used for. We will conduct expert surveys and interviews to create an analytical framework for such crimes, and develop scenarios and policy recommendations.

Guiding and Incentivizing Cyber-Security Behavior

Dr. Eran Toch, Department of Industrial Engineering, TAU

In this project, the investigator is conducting theoretical and empirical research with two objectives in mind: first, to propose and evaluate a theory that explains users’ decision-making given negative and positive incentives and second, to test how we can influence users’ decision- making processes by designing gamification-based incentive systems. By the end of the study, the investigator plans to offer a toolkit for the optimal design of incentive systems for cyber-security that enhances user involvement in the interaction in enterprise security systems.

Hostile Influence Operations via Social Media: A Cybersecurity Issue? Assessing the Applicability of Recent Evidence to the Israeli Soft Power

Dr. Lior Tabansky, Blavatnik ICRC, TAU

This interdisciplinary research aims to develop a new analytical framework for cyber power and cybersecurity, explicitly including defense against hostile influence operations. It builds on the work done during the 2013 internship of Margarita Jaitner from the Swedish Defence College with Mr. Tabansky at the Yuval Ne’eman workshop.

Identification of Malicious Websites by Learning the Websites’ Design Attributes

Prof. Irad Ben Gal, Department of Industrial Engineering, TAU

In this research we suggest a machine learning procedure for automatically identifying crack websites. Based on a primary model, we show that classification by HTML colors and design features can reach an accuracy of over 90% in some cases. Adding metadata, such as webpage keywords, enhances the accuracy in the tested dataset. We show how conventional machine learning models can be used to classify suspicious websites by learning their design features that are often overlooked and obtain results in the context of developing intelligent cyber security mechanisms. The main purpose of this work is to strengthen the preliminary results and scale the developed algorithms to analyze large number (millions) of websites automatically.

Implications of the GDPR on Higher Education System in the Era of Digital Education

Dr. Tal Soffer, School of Education, TAU

Dr. Anat Cohen, School of Education, TAU

Dr. Yoel Raban, School of Education, TAU

The main goals of the study are: a) to describe the needs for transforming the higher education under the regime of the new GDPR in light of the growing usage of emerging technologies. b) to recommend a policy for performing the necessary changes to comply with this regulations, taking into considerations the potential pedagogical aspects stemming from the usage of emerging technologies.

Increasing Incentives for Cyber Defense in Organizations using the Principles of Behavioral Economics

Ori Weisel, Coller School of Management, TAU

Yevgeny Mugerman, School of Management, BIU

Eyal Winter, Economics, HUJI

Infrastructure for Cyber Threat Information Sharing

Prof. Tova Milo, Blavatnik School of Computer Science, TAU

Dr. Daniel Deutch, Blavatnik School of Computer Science, TAU

The goal of this project is to develop solid scientific foundations for large-scale cyber threat information sharing and analysis. The investigators believe that such a principled approach is essential in order to obtain knowledge of superior quality, to realize the task more effectively and automatically to be able to reuse solutions and thereby to improve the effectiveness of defensive cyber operations and incident response activities.

Leakage-free Cryptography: Eliminating Side Channel Leakage Using Compiler Optimization

Eyal Ronen, Blavatnik School of Computer Science, TAU

Yuval Yarom, School of Computer Science, University of Adelaide, Australia

Markus Wagner, University of Vienna, Austria

Chitchanok Chuengsatiansup, School of Computer Science, University of Adelaide, Australia

Minhui Xue, University of Adelaide, Australia

Iftach Haitner, Blavatnik School of Computer Science, TAU

Low rank approximation of a distribution-based kernel for super-fast malware detection in a very big data

Amir Averbuch, Blavatnik School of Computer Science, TAU

Tatiana Osokin, TAU

Gil Shabat, TAU

The goal of this proposal is to detect malwares (anomalies) in an unsupervised way. The input data, which is classified as a training data, is arranged as a kernel matrix. The distances among the kernel entries are measured as Wasserstein distances also called Earth Mover's Distance. The distances will be between distributions. This enables us to process also unstructured data. The malware detection is based on embedding the kernel matrix into a lower dimensional space represented by a manifold. Then, a newly arrived multidimensional data point, which did not participate in the training data and is embedded into the lower dimensional space, is classified as normal or anomaly if it lies in the manifold or deviate from it, respectively.

Media Management Aspects of Cybersecurity Crisis

Yarden Vatikay and Prof. Yehiel Limor, Mass Communications and Political Science, HUJI

The research question is therefore do cyber communication crises resemble other communication crises, and are the models for managing other communication crises suitable also for managing cyber ones? We believe this research could promote academic and professional communication crisis research and management in the public and private sectors, thus suggesting new models for analyzing and managing communication crises in cyberspace. It could also promote understanding and enhance preparedness of the issue among the relevant factors in the public and private sectors and contribute to the knowledge of challenges in the cyberspace era.


Memory Access Safety-Checking Tools for Programs that Share Memory with Devices

Dr. Adam Morrison, Blavatnik School of Computer Science, TAU

Dr. Dan Tsafrir, Department of Computer Science, Technion

Memory access vulnerabilities (such as buffer overflow) are prevalent in unmanaged programming languages, and concurrent memory access vulnerabilities are prevalent in managed and unmanaged languages alike. Significant research has therefore been put into developing tools that help programmers identify and protect against such vulnerabilities. We observe, however, that (1) setups allowing programs to utilize non-CPU devices that independently access the memory are becoming increasingly popular, and that (2) none of the aforementioned tools are applicable in such setups. We propose to investigate this problem and make the first step towards a solution.

Mitigating the Risk of Advanced Cyber-Attackers

Prof. Asher Tishler, Coller School of Management, TAU

Dr. Ohad Barzilay, Coller School of Management, TAU

The proposed research examines some aspects of the new rules. The investigators aim to draft formal analytical opportunities for the attacker and the respective challenges faced by the defender.

Mobile Phone Data for Society and Privacy for the Individual: From the Conflict to a Synergy in Transport Flows Analysis

Prof. Itzhak Benenson, Department of Geography and Human Environment, School of Geosciences, Faculty of Exact Sciences, TAU

Prof. Itzhak Omer, Department of Geography and Human Environment, School of Geosciences, Faculty of Exact Sciences, TAU

Raazesh Sainudiin, Department of Mathematics, Uppsala University, Uppsala, Sweden

Our research aims at establishing the necessary and sufficient space-time resolution and level of aggregation of mobility data that are required for the smart city transportation planning and management and, at the same time, clearly understand the potential harms to privacy, avoid disclosure of individual information and establish the forms of mobility data supply and procedures of data management and analysis in order to guarantee individual privacy. The outcome of this interaction should be clear privacy- preserving rules of mobility data aggregation for transportation planning and management.

Multi Robot Coverage and Surveillance

Prof. Dan Halperin, Blavatnik School of Computer Science, TAU

We propose to devise and analyze novel efficient algorithms for multi-robot motion coordination, where a fleet of robots is carrying out tasks of coverage and surveillance. Monitoring and surveillance by fleets of robots is a burgeoning trend around the globe targeting a wide range of tasks from wildlife protection through mine detection to border patrolling. In recent years our group has been in the forefront of developing efficient methods for robot motion planning, for optimizing motion plans, and for dealing with generalized variants of multi-robot motion. We plan to harness techniques from algorithmic robotics and computational geometry and to develop new tools for a family of multi-robot tasks related to tracking and monitoring, tools that will be at once practically efficient and backed by theoretical analysis.

Network Attack and Detection in Modbus/TCP SCADA Systems

Prof. Avishai Wool, TAU

Dr. Leonid Lev

This research is comprised of several tasks: 1) Developing network penetration-test tools specifically for the Modbus SCADA protocol. 2) Experimentation with the penetration tools. 3) Testing the model-based anomaly-detection system on data from the IEC HEDVa environment and from U.Twente. 4) Testing the anomaly-detection system against the penetration tools.

Non-Public Financial Information Leak

Dr. Roy Zuckerman, Coller School of Management, TAU

This research proposes an exploratory study of the role of cyber security in non-public information leaks. This study examines whether firms properly oversee the online security measures taken to protect non-public financial information both within the organization and with the affiliated service providers. In addition, the investigators are attempting to identify certain service providers which are more likely to be associated with leaks and determine if they are associated with weak cyber security measures. This is the first study to highlight the risk of trading based on non-public information obtained via cyber hacks. As such, policy implications based on the findings of such a study may be far-reaching.

Non-Public Hacks

Dr. Roy Zuckerman, Coller School of Management, TAU

In this study we investigate the preponderance of obtaining non-public financial information through cyber hacks. Using data acquired from a major networking equipment provider, we find that attempted hacks on public companies' HQs rise by up to 60% during the 14 calendar days preceding the release of quarterly earnings. Attacks drop to normal levels a day after the earnings release. We find no such effect for private companies in our dataset. The results remain robust after controlling for day for the week, malware activity and other seasonal effects. We find no significant abnormal returns for the firms in our sample prior to the release of quarterly earnings. Taken together, these results imply that cyber hackers have significant interest in obtaining non-public financial information prior to its release.

Personal Genomic Data: Privacy and Security Aspects

Prof. Benny Chor, Blavatnik School of Computer Science, TAU

Dr. Metsada Pasmanik-Chor, Bioinformatics, TAU

The current research employs the tools of game theory, decision and optimization problems and economic tools to analyze scenarios.

Photonic Emission Side-Channel Cryptanalysis of Secure Hardware Devices

Prof. Avishai Wool, School of Electrical Engineering, TAU

The goal of this work is to apply the methods and know-how developed on the power-analysis side-channel and apply them to the photonic emission side channel. The TAU and Berlin teams already have a good working relationship and would like to collaborate on this topic. It is believed that a solver-based approach allows for a much better description of the very detailed information leakage which can be exposed by the photonic side channel.

Privacy by Design by Legislation

Prof. Michael Birnhack, Faculty of Law, TAU

Prof. Avner Levin, Law, Ryerson University, Canada

Privacy is a key element in cyber security. Protecting personal data held and processed by cybernetic systems converges with other security principles and may enhance data subjects’ and end-users’ trust in such systems, resulting in greater acceptance thereof. Violations of privacy, on the other hand, will diminish trust, acceptance and efficiency of cyber systems. However, privacy and security are not fully congruent concepts and at times, privacy requires taking measures that might limit the functionality and usability of technological systems. This research asks “How can a cybernetic system achieve the optimal combination of usability, security and privacy”?

ProGReSS - Sectoral Cyber Capability Maturity Model

Lior Tabansky, Blavatnik ICRC, TAU

The PROGRESS (Promoting Global Cyber Resilience for Sectors and Society) Cyber-Capability Maturity Model (PROGRESS CCMM) aims to create practical action plans for improving the cyber capability maturity of each vital sector. The main innovation of the PROGRESS CCMM is its ability to capture any economic sector as a whole. Science has established that resilience is an emergent property, a behavior resulting from reciprocal interactions in complex systems. This means that increasing robustness of an individual component does not linearly improve resilience. Yet the majority of cybersecurity methods and frameworks analyze a single organization. 

Reconciling Cyber-Security Research with Privacy Law: The Video Analytics and Medical Image Analysis Examples

Prof. Nahum Kiryati, Professor at the School of Electrical Engineering, TAU

Research and development (R&D) in video content analysis, medical image analysis, and other data analysis techniques related to anomaly detection, require huge amounts of data for training and evaluation. This is underscored by the groundbreaking deep-learning paradigm. The only practical source for relevant data is collections of real data acquired in the field. In the context of video content analysis, this refers to actual video surveillance databases acquired in public areas. Such data is strictly protected by privacy regulations. Consequently, its use for R&D is practically limited to large corporate entities that handle the data as part of their business. These include surveillance system providers, cloud services and social networks. Academic research on these topics is therefore crippled, and new industrial players are also excluded. In the context of medical image analysis, the relevant data is the collection of medical images stored in Picture Archiving and Communication Systems (PACS) at hospitals. Access to this resource is usually available to hospital staff only, creating an effective data monopoly with respect to external academic and industrial players. The proposed research, at the interface between technology, law and policy, will evaluate the problem and develop interdisciplinary solutions, facilitating academic R&D in video content analysis, medical image analysis and similar cyber-security anomaly-oriented data analysis challenges.

Righting Our Wrongs in Digital Downloading

Dr. Dikla Perez, Business Administration, BIU

Dr. Ayelet Gneezy, Rady School of Management, University of California, San Diego, USA

Prof. Yael Steinhart, Coller School of Management, TAU

Shirly Bluvstein, Leonard N. Stern School of Business, New York University, USA

This research addresses the popularity of this illegal and unethical behavior in the cyber space and examines the conditions under which people decide to “right their wrongs” by agreeing to offer monetary compensation to content producers after engaging in illegal digital downloading. Specifically, we aim to examine whether (a) perceived social norms, (b) legal consequences, and (c) the interaction between them affect individuals’ moral perceptions regarding illegal digital downloading and their consequent tendency to engage in moral regulation after downloading content illegally. Our experiments rely on an innovative paradigm for evaluating moral-regulation behavior, namely, offering individuals an opportunity to financially compensate (or express intentions to compensate) the party they have wronged.

Robust Decentralized Digital Currency

Dr. Iftach Haitner, Blavatnik School of Computer Science, TAU

Dr. Benny Applebaum, Electrical engineering, TAU

Dr. Amos Fiat, Blavatnik School of Computer Science, TAU

Dr. Eran Tromer, Blavatnik School of Computer Science, TAU

This research studies essential aspects of the security, economy and policy implications of Bitcoin like digital currencies. Via the perspectives of cryptography, distributed computing, computer engineering and algorithmic game theory, the investigators aim to improve understanding, identify flaws and create new systems that serve society better in functionality and robustness. They are implementing a broad investigation of these issues, using their expertise in cryptography, computer engineering and Algorithmic Game Theory.

Safety and Privacy of Mobile Applications through Model Inference

Shahar Maoz, Blavatnik School of Computer Science, TAU

Eran Toch, Department of Industrial Engineering, TAU

Eran Tromer, Blavatnic School of Computer Science, TAU

Mobile operating systems pose serious security and privacy threats and therefore can compromise the smart city and degrade trust between citizens and governments. In this proposal, we develop AppMod, a model-based framework for safe mobile applications on the Android platform. The approach relies on dynamic analysis of apps, uses model-based inference and differencing to detect privacy violations and behavioral anomalies, and suggests new interactions that allow users to effectively control their privacy and security.

Secure Shared Learning in Healthcare: Inference of Hospital Infection Risks

Prof. Galia Rahav, Sackler Faculty of Medicine, TAU and Sheba Medical Center

Prof. Benny Chor, School of Computer Science, TAU

Dr. Adi Akavia, Center for Cyber Law and Policy, Haifa University

Prof. Zohar Yakhini, Efi Arazi School of Computer Science, IDC

The use of data science to support inference in medical science has seen great progress in recent years and is a very active research domain with important practical implications. The application of state of the art techniques in this context requires skill and knowledge as well as large volumes of data, to support higher confidence statistics. We propose to develop methods, algorithms and protocols to enable secure data sharing for performing machine learning tasks on data combined from several parties. The protocols will support the sharing and transfer of encrypted or masked data; the performance of learning on said protected data, with no significant leakage of information; and the secure communication of the learning results to the data providers.

Securing Servers and Endpoints using Software Guard Extensions

Prof. Sivan A. Toledo, Blavatnik School of Computer Science, TAU

Dr. Eran Tromer, Blavatnik School of Computer Science, TAU

This research project addresses three crucial aspects of using SGX to secure servers and endpoints in such applications: analyzing the security of SGX itself; enabling SGX applications and integration with complementary approaches. In summary, the research will enable effective and rigorous use of the soon- to-be-ubiquitous SGX hardware, in the service of numerous applications that require trust in platforms.

Security Hardening against Hardware Vulnerabilities through Hardware Separation

Dr. Erez Shmueli, Industrial Engineering, TAU

Prof. Assaf Schuster, Computer Science Department, Technion

Dr. Nadav Amit, Computer Science Department, Technion

In our research, we wish to explore the solution space for the mitigation against this new class of security vulnerabilities, including yet undiscovered ones, and to study the inherent trade-off between protection and performance. To protect against these vulnerabilities, we wish to take a more drastic measure, by separating the hardware resources, compute, and memory, which are allocated to the OS and its processes. This separation can be done in different levels to serve diverse purposes: weak separation to complement current protection schemes by alleviating their overheads, and strong separation to protect against unknown security threats.

Shocks to and Security in the Bitcoin Ecosystem: An Interdisciplinary Approach

Prof. Neil Gandal, School of Economics, Faculty of Social Science, TAU

Dr. Tyler Moore, School of Cyber Studies, Tandy School of Computer Science, The University of Tulsa, USA

This research includes the following key topics: the optimal resource allocation for protecting a network and the recent rise in digital currencies. The latter, which was led by the introduction of Bitcoin in 2009, creates an opportunity to measure information security risk in a way that has often not been possible in other contexts. Digital currencies (or cryptocurrencies) aspire to compete against other online payment methods such as credit/debit cards and PayPal, as well as serve as an alternative store of value. They have been designed with transparency in mind, which creates an opportunity to quantify risks better. While Bitcoin's design provides some safeguards against `counterfeiting' of the currency, in practice, the ecosystem is vulnerable to thefts by cybercriminals, frequently targeting intermediaries such as wallets or exchanges.

Smart Cities Cyber Security (SCCS)

Prof. Michael Birnhack, The Buchmann Faculty of Law, TAU

Prof. Issi Rosen-Zvi, The Buchmenn Faculty of Law, TAU

Dr. Tali Hatuka, Department of Geophysics, TAU

A theoretical and empirical study is being conducted, taking Israeli cities as a case study. Several Israeli cities take a leading role in developing Smart City, making them ideal candidates for initial research. The goal is to offer a multi- faceted toolkit for the optimal design of cyber systems for smart cities in Israel. This is a broad goal and it is impossible to cover all aspects of SCCS. Hence, the investigators are focusing on four interrelated dimensions, which they think are cornerstones of a viable SCCS: planning, technology. The research is creating a set of tools for policy-makers and municipalities in the process of developing a smart city.

Space 'Assets and Applications' Cybersecurity

Baram, Gil, CISAC, Stanford, USA


Strategic Cyber Reasoning in Attacker-Defender Resource Allocation Games

Ayala Arad, Coller School of Management, TAU

Prof. Stefan Penczynski, University of Mannheim, Germany

In the proposed research, we develop extensions of the popular Colonel Blotto game with application in cyber security and study cyber-attacker and defender strategic reasoning experimentally. The project is expected to provide defenders with some basic principles for allocating security costs across various components of a system when defending against anonymous attackers. Furthermore, based on the experimental results, we intend to construct an equilibrium-like solution concept, which takes into account that players use categorical thinking or multi- dimensional reasoning. The solution concept is expected to be particularly useful for predicting behavior in situations of repeated interaction between a particular defender and attacker, where both players become more sophisticated over time and learn from their opponent’s previous actions, although they are subject to certain cognitive or computational limitations.

Symbolic Reasoning for Executable Code

Prof. Mooly Sagiv and Dr. Noam Rinetzky, Blavatnik School of Computer Science, TAU

Our goal is to develop tools, techniques, and methodologies that help detect vulnerabilities in realistic software systems by synthesizing inputs that can force a program to go from one given program point to another, or determine that no such input exists, and hence that this particular vulnerability never occurs. We plan to do so by expressing the feasibility of an execution path using a logical formula and harnessing the power of modern symbolic SAT solvers, e.g., Z3, to identify a satisfying assignment, i.e., an input scenario which exposes the vulnerability, or determine that none exists.

The Blame Game: National Strategies During Cyber Conflict

Dr. Udi Sommer, Political Science, TAU

Gil Baram, Political Science, TAU

We propose to undertake the first comprehensive study to examine factors underlying the strategic choices of states involved in cyber conflicts. Choice of any specific strategy may have important implications for the country, its leaders, and its relations with other international actors. Therefore, it is necessary to examine in depth the considerations that may influence national decision makers in choosing their strategy, the factors that lead to this choice and its implications.

The Deniability Mechanism in the Cyber Age – Its Effect on States' Behavior in the International System

Gil Baram, Department of Political Science, TAU

Most research so far has only dealt with one side of the equation, namely – how states attribute attacks to other nations and how they verify and prove their accusations. However, almost no research has been done on the opposite side of the equation, i.e., how states successfully manage to deny their responsibility for alleged cyber-attacks and evade accusations that they were responsible for committing an attack. This research will deal precisely with this topic. By using several quantitative and qualitative techniques, this research seeks to examine how does the use of the deniability mechanism affects the degree of aggression of states in the international arena. The ultimate purpose of this research is to create a theoretical framework that will allow for a better understanding of how the use of offensive cyber warfare technology affects the relations between states and the lack of visible long-term conventional war.

The Effect of Engagement on Private Information

Prof. Gal Oestreicher-Singer, Coller School of management, TAU

In this research proposal, it is hypothesized that engaged users will agree to reveal more personal information as compared to the less engaged and that compliance with a website’s requests for engagement will lead to subsequent information revelation. This exploratory research can improve our understanding of the process of information revelation as well as increase user awareness to pitfalls and help policy- makers in the field of privacy to make more informed decisions regarding website design for privacy.

The Emergence of a New Profession: Data Protection Officers in Israeli Organizations

Michael Birnhack, Faculty of Law, TAU

Guy Mundlak, Faculty of Law, TAU

The proposed research seeks to examine the emergence of this new cyber profession in Israel, a small, developed economy that is active in the global market. While the substantive law on data protection is important for understanding the context of the legal regime that informs what organizations must do, the study’s emphasis is on the process installed by the laws and the agents who are appointed to oversee it. Hence, beyond the study of privacy law, the study utilizes organizational and neo-institutional theory.

The Interplay of Cyber Vulnerability and Enterprise Credit Risk

Dr. Shachar Reichman, Coller School of Management, TAU

Sam Ransbotham, Department of Information System, Boston College, USA

George Westerman, Sloan School of Management, MIT, USA

This research aims to develop a novel method to evaluate the interaction between cyber vulnerability and enterprise financial risk as reflected by its credit rating. Using multiple data from online financial and security sources we will explore the effect of a firm’s cyber factors, including DNS hacking events, intrusion risks, exposure to DOS attacks, servers’ configuration levels, and privacy measures, on its credit rating. We will then examine the counter effect, how a credit rating downgrade affects the firms’ information security measures.

The Intersection of Cybersecurity and Space Security: New Threats to Cyber-Enabled Space Activities and the Development of Legal and Policy Responses

Adv. Deborah Housen-Couriel, LL.M, MPA

One of the most compelling interdisciplinary challenges to cybersecurity at present is also a hitherto under-researched one; that is, the intersecting threat vectors in cyberspace and in outer space with which states and private entities are currently engaging. These vectors converge around the present vulnerabilities of satellites and the data transmitted by satellite communications, which take place almost entirely through cyberspace. The proposal detailed below addresses the intersection of cybersecurity and space security at the three levels of legal analysis, governance regimes and present and future public policy.

The Nature of Cyber Threats & The Road to Cyber Security Regulation

Eviatar Matania, Political Science Studies, TAU

Global efforts to regulate cyberspace in the context of international security are challenged by fundamentally different perceptions on the nature of cyber conflict by the world’s greatest cyber-powers: China, Russia, and the United States. This study explores the most critical aspects of cyberspace regulation that each cyber power attribute and perceives, that have prevented gaining further progress after the failure of the 2016-2017 Group of Governmental Experts, that was set to formally establish negotiations on cyberspace regulation.

The Selfish and Caring of Sharing: Exploring the Reasons and Personal Outcomes of Public-Shaming

Prof. Yael Steinhart, Coller School of Management, TAU

Prof. Jacob Goldenberg, Arison School of business, HUJI

Dr. Chen Pundak, Coller School of management, TAU

The proposed research will focus on public-shaming that runs through social networks. It will include a series of studies to explore the motivations and outcomes of public-shaming. We hypothesize that: (1) vulnerability to one's self-image will increase the likelihood of joining active shaming, especially when the wrongdoer is perceived to be similar to the 'shamer'; (2) self-image perceptions will increase after taking part in online shaming; (3) shaming will occur when its goal leans toward expressing the 'shamer's identity rather than toward fulfilling functional needs; (4) morality will drive public-shaming when the wrongdoer is non-identified rather than identified.

Towards an Interdisciplinary Unified Theory of Cyber Power: Security Studies, Meta-Governance, National Innovation System

Prof. Isaac Ben-Israel and Lior Tabansky, Blavatnik ICRC, TAU

Cyber security science is different: it is a science in the presence of adversaries. Exact sciences help understand the technology. Social science scholarship may help to better understand the actors – but it is underutilized. We identify and develop state-of-the-art scholarship in three topical thrusts, and then integrate these theoretical building blocks to develop an interdisciplinary unified theory of Cyber Power which is generalizable to multiple settings.

Towards Higher Accuracy of Behavioral Big Data Analysis

Prof. Dov Te’eni, Coller School of Management, TAU

Prof. David G. Schwartz, Information System, BIU

Dr. Inbal Yahav, Coller School of Management, TAU

This interdisciplinary study develops a hybrid classification method that integrates qualitative analysis with classifier design for text and image analysis of online behavioral big data, which we call Qualitatively Augmented Text Classifier Algorithms (QATCA). This method will be developed and evaluated on an existing cyber intelligence platform that analyzes Dark Web activity undetectably and autonomously. The application of the method relies on computer support that not only aids qualitative analysis and classifier design but also ensures the integration of both components.

Ultralong Fiber Laser for Secure Communications

Dr. Jacob Scheuer, School of Electrical Engineering, TAU

The main objectives of this exploratory program are to investigate the resilience of a certain scheme to a variety of active attacks and to obtain quantitative metrics regarding information about the key that might be obtained by a potential adversary. The research includes both theoretical and experimental efforts to study the system’s resilience to eavesdropping and for developing appropriate countermeasures.

Understanding IP Hijack Events

Prof. Yuval Shavitt, School of Electrical Engineering, TAU

Surprisingly, a large-scale analysis of hijack events that will enable security system designers to understand this risk has never been published. In this project, hijack events are analyzed over time and active monitoring is compared with BGP based detection

Understanding the Role of Cyber Insurance in Combating Cyber Risk

Ronen Avraham, Faculty of Law, TAU

Baker Tom, Law, University of Pennsylvania, USA

Commercial cyber insurance is becoming increasingly important as the cyber risk exposure of corporations is rapidly mounting, considered to be the fastest-growing field of private market insurance in the U.S. and Israel. Along with the meteoric increase in global sales of cyber insurance, the importance of discussing critical social questions regarding the impact of the cyber insurance industry on social welfare is rising. For example, does cyber insurance help mitigate cyber risk by providing businesses, or encouraging businesses to be equipped, with the best cyber protection tools, or does it worsen things by, for example, making businesses indifferent to cyber risks? How can policymakers balance the scales between the public policy goal of cyber loss reduction and insurers’ private goal of increasing the size and profitability of the market for insurance against cyber losses? Answering these kinds of questions requires a better understanding of the cyber insurance market than that provided by existing literature.

Using Nudges to Reduce the Appeal of Online Misinformation

Dr. Meyrav Shoham, School of Social and Policy Studies, TAU

Prof. Shira Dvir Gvirsman, Department of Communication Studies, TAU

The proposed research explores how nudges can be used to make misinformation and its purveyors less appealing to people, reducing the likelihood that they will be swayed by it and consume if further. We focus on how fluency can affect judgments of misinformation and interest in engaging further with those who spread it. Fluency, or the experienced ease with which information is processed, can occur because information is more legible, readable, or visually appealing. This suggests that if misinformation is presented in a fluent manner, susceptible individuals will be especially likely to fall prey to it. In our project, we build on this insight and explore different ways of altering the presentation of misinformation and their impact. Our goal is to determine when reduced fluency is most effective in diminishing the appeal and effectiveness of misinformation and those who spread it.

Values and Cyber Security

Prof. Neil Gandal, School of Economics, TAU

Prof. Sonia Roccas, Professor of Psychology, The Open University of Israel

Despite all of the technological advances, cyber security is largely determined by the behavior of the end-users. The integrity the network depends on the willingness of the users to adhere to security guidelines. Increasing awareness to security threats and the steps that should be taken to avoid them is an important factor. However, increased awareness is not sufficient to ensure safe behavior. People often behave in ways that expose them to the risk of undesirable consequences even when they are well aware of these consequences (unhealthy eating habits, unsafe driving practices, etc.). Thus, a different approach is needed to identify factors that increase willingness of end-users to adopt safe behavior.

Viciousness and Caring of Sharing: Conflicts and Motivations of Online Shamers

Dr. Dikla Perez, Business and Administration, BIU

Dr. Ayelet Gneezy, Rady School Faculty, UC San Diego, USA

Prof. Yael Steinhart, Coller School of Management, TAU

Shirly Bluvstein, Stern School of Business, NYU, USA

Despite all of the technological advances, cyber security is to a large extent determined by the behavior of the end-users. The integrity the network depends on the willingness of the users to adhere to security guidelines. Increasing awareness to security threats and the steps that should be taken to avoid them is an important factor. However, increased awareness is not sufficient to ensure safe behavior. People often behave in ways that expose them to the risk of undesirable consequences even when they are well aware of these consequences (unhealthy eating habits, unsafe driving practices, etc.). Thus, a different approach is needed to identify factors that increase willingness of end-users to adopt safe behavior.

Violence and the (Social) Construction of Cyber Deterrence

Dr. Amir Lupovici, School of Political Science, TAU

The proposed research, which aims to yield a book-length manuscript, focuses on practices of cyber deterrence by exploring them in five countries—the US, Israel, Turkey, China and Russia—between the years 1999-2014. The project seeks to answer two main questions: 1) to what extent and how have these countries adopted a cyber deterrence strategy? 2) Is cyber deterrence an effective strategy, that is, does cyber deterrence affect cyber-attacks, and if so, how?

What’s the Value of Bug Bounty Programs?

Ms. Keren Elazari, Blavatnik ICRC, TAU

The Vulnerability Rewards program, better known as Bug Bounty (BB) programs, are frameworks that allow companies to reward individual hackers for discovering and disclosing security and privacy breaches in the most popular sites in the world. To date, Facebook has paid hackers from around the world more than $2 million in rewards for their discoveries of bugs through its Bug Bounty program. Almost every major technology firm operates a similar framework. PayPal, Yahoo, Samsung, Twitter, Microsoft, Google are just a few familiar names among the hundreds of global companies that operate the Bug Bounty program in order to offer incentives to independent hackers and security researchers who report code-based weaknesses or breaches. The first BB plan was established for the browser Netscape in 1995. Today, 20 years later, ground-breaking research being conducted in the US found that Mozilla’s BB program is one of the most cost effective tools for identifying weaknesses in software and security issues.

You can Log-out Any Time You Like, But Can You Ever Leave? Increased Social-Network Usage is Associated with Psychological Distress and Enhanced Cyber Security Risks among Individuals with Impaired Neural Filtering Ability of Social-Network Info

Prof. Gal Sheppes and Prof. Roy Luria, School of Psychology, TAU

Half a billion Facebook (FB) users log-in multiple times a day and spend 18 minutes on average each visit. Although this statistic raises significant worries that increased usage may be associated with maladaptive psychological consequences such as anxious and depressive symptoms, existing studies provide mixed results. We suggest that individuals vary in their ability to control FB cues when such cues interfere with performing goal directed activities. For example, some individuals may fail to overcome the urge to click an open FB tab when working on a school project. We argue that for these individuals in particular, enhanced FB usage may be associated with maladaptive psychological elements. Accordingly, the main premise of this research program is that enhanced FB usage would lead to increased anxious and depressive symptoms, mainly among individuals with impaired ability to filter potent FB information when this information is incongruent with one's goals

Tel Aviv University makes every effort to respect copyright. If you own copyright to the content contained
here and / or the use of such content is in your opinion infringing, Contact us as soon as possible >>