Welcome to
  • Ben-Gurion
    University
  • Cyber@Ben-Gurion
    University
  • Telekom
    Innovation Labs

The
Partnership

Telekom Innovation Laboratories are in the business of creating, inventing and innovating while having fun. It is a technological playground which was set-up by Deutsche Telekom and Ben Gurion University, where the most brilliant students, industry professionals and world class researchers are playing around with new ideas in order to design and shape the technology of the future.

To find answers to technological problems that no one have yet thought about, our researchers and developers possess excellent analytical skills, flexible thinking, curiosity and determination, although they all come from different backgrounds and disciplines.

If you are a true problem solver who dares to ask challenging questions, driven by innovation, technology, curiosity, and creativity – you will have a unique opportunity to work side by side with some of the most talented professionals like yourself, who were carefully selected to master the most disruptive and technologically diverse projects within the domains of Networks, Cyber Security, Big Data, Blockchain, AI, Machine Learning & Deep Learning, at the forefront of innovation.

Whether you join us as a student, researcher or an industry expert, you will enjoy groundbreaking, complex, high-profile work in a global environment, combining both research and development.

 

Latest Publications by Telekom Innovation Labs

In collaboration with Telekom Innovation Laboratories

CoBAn: A context based model for data leakage prevention

G Katz, Y Elovici, B Shapira

Information sciences 262, 137-158, 2014

In collaboration with Telekom Innovation Laboratories

CoBAn: A context based model for data leakage prevention

G Katz, Y Elovici, B Shapira

Information sciences 262, 137-158, 2014

A new context-based model (CoBAn) for accidental and intentional data leakage prevention (DLP) is proposed. Existing methods attempt to prevent data leakage by either looking for specific keywords and phrases or by using various statistical methods. Keyword-based methods are not sufficiently accurate since they ignore the context of the keyword, while statistical methods ignore the content of the analyzed text. The context-based approach we propose leverages the advantages of both these approaches. The new model consists of two phases: training and detection. During the training phase, clusters of documents are generated and a graph representation of the confidential content of each cluster is created. This representation consists of key terms and the context in which they need to appear in order to be considered confidential. During the detection phase, each tested document is assigned to several clusters and its contents are then matched to each cluster’s respective graph in an attempt to determine the confidentiality of the document. Extensive experiments have shown that the model is superior to other methods in detecting leakage attempts, where the confidential information is rephrased or is different from the original examples provided in the learning set.

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In collaboration with Telekom Innovation Laboratories

Mobile malware detection through analysis of deviations in application network behavior

A Shabtai, L Tenenboim-Chekina, D Mimran, L Rokach, B Shapira

Computers & Security 43, 2014, 1-18

In collaboration with Telekom Innovation Laboratories

Mobile malware detection through analysis of deviations in application network behavior

A Shabtai, L Tenenboim-Chekina, D Mimran, L Rokach, B Shapira

Computers & Security 43, 2014, 1-18

In this paper we present a new behavior-based anomaly detection system for detecting meaningful deviations in a mobile application’s network behavior. The main goal of the proposed system is to protect mobile device users and cellular infrastructure companies from malicious applications by: (1) identification of malicious attacks or masquerading applications installed on a mobile device, and (2) identification of republished popular applications injected with a malicious code (i.e., repackaging). More specifically, we attempt to detect a new type of mobile malware with self-updating capabilities that were recently found on the official Google Android marketplace. Malware of this type cannot be detected using the standard signatures approach or by applying regular static or dynamic analysis methods. The detection is performed based on the application’s network traffic patterns only. For each application, a model representing its specific traffic pattern is learned locally (i.e., on the device). Semi-supervised machine-learning methods are used for learning the normal behavioral patterns and for detecting deviations from the application’s expected behavior. These methods were implemented and evaluated on Android devices. The evaluation experiments demonstrate that: (1) various applications have specific network traffic patterns and certain application categories can be distinguished by their network patterns; (2) different levels of deviation from normal behavior can be detected accurately; (3) in the case of self-updating malware, original (benign) and infected versions of an application have different and distinguishable network traffic patterns that in most cases, can be detected within a few minutes after the malware is executed while presenting very low false alarms rate; and (4) local learning is feasible and has a low performance overhead on mobile devices.

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In collaboration with Telekom Innovation Laboratories

Identifying Attack Propagation Patterns in Honeypots Using Markov Chains Modeling and Complex Networks Analysis

Bar, Ariel and Shapira, Bracha and Rokach, Lior and Unger, Moshe

Software Science, 2016 IEEE International Conference on Technology and Engineering (SWSTE), 28-36

In collaboration with Telekom Innovation Laboratories

Identifying Attack Propagation Patterns in Honeypots Using Markov Chains Modeling and Complex Networks Analysis

Bar, Ariel and Shapira, Bracha and Rokach, Lior and Unger, Moshe

Software Science, 2016 IEEE International Conference on Technology and Engineering (SWSTE), 28-36

Honey pots are computer resources that are used to detect and deflect network attacks on a protected system. The data collected from honey pots can be utilized to better understand cyber-attacks and provide insights for improving security measures, such as intrusion detection systems. In recent years, attackers’ sophistication has increased significantly, thus additional and more advanced analytical models are required. In this paper we suggest several unique methods for detecting attack propagation patterns using Markov Chains modeling and complex networks analysis. These methods can be applied on attack datasets collected from honey pots. The results of these models shed light on different attack profiles and interaction patterns between the deployed sensors in the honey pot system. We evaluate the suggested methods on a massive data set which includes over 167 million observed attacks on a globally distributed honey pot system. Analyzing the results reveals interesting patterns regarding attack correlations between the honey pots. We identify central honey pots which enable the propagation of attacks, and present how attack profiles may vary according to the attacking country. These patterns can be used to better understand existing or evolving attacks, and may aid security experts to better deploy honey pots in their system.

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Meet The Team of Telekom Innovation Labs

Yuval Elovici

Director

Yuval Elovici

Director

Yuval Elovici is the director of the Telekom Innovation Laboratories at Ben-Gurion University of the Negev (BGU), head of BGU Cyber Security Research Center, Research Director of iTrust at SUTD, SUTD principle investigator of ST Electronics-SUTD Cyber Security Lab, a Professor in the Department of Software and Information Systems Engineering at BGU, and the incumbent of the Davide and Irene Sala Chair in Homeland Security Research. He holds B.Sc. and M.Sc. degrees in Computer and Electrical Engineering from BGU and a Ph.D. in Information Systems from Tel-Aviv University. Yuval has published articles in leading peer-reviewed journals and various peer-reviewed conferences. In addition, he has co-authored a book on social network security and a book on information leakage detection and prevention. His primary research interests are computer and network security, cyber security, web intelligence, information warfare, social network analysis, and machine learning. Yuval also consults professionally in the area of cyber security and is the co-founder of Morphisec, a startup company that develops innovative cyber security mechanisms that relate to moving target defense.

Oleg Brodt

Chief Innovation Officer

Oleg Brodt

Chief Innovation Officer

Oleg serves as the R&D Director of Deutsche Telekom Innovation Labs Israel, focusing on future technologies in the fields of Cyber Security and Artificial Intelligence; as well as the R&D Director for Cyber@BGU – an umbrella organization responsible for all cyber security research and industrial collaborations at the Ben Gurion University, Beer-Sheva, Israel (Israel’s Cyber Capital). Prior to joining DT Labs and Cyber@BGU, Oleg acted as an attorney, specializing in Hi-Tech, and represented a broad spectrum of local and international clients, including individual and institutional investors, VCs and long list of start-ups and Hi-Tech companies, among many others. In this capacity, Oleg still serves as a member of the Hi-Tech committee of the Israeli Bar Association. Before practicing law, Oleg served in various management positions for leading Hi-Tech companies, where he gained in-depth experience in both technological and business matters. He was also a member of the ‘Nova Project’, a country-wide organization providing strategic management consulting for non-profits in Israel. Oleg gained substantial technological training at an elite IDF Hi-tech unit, where he served as a team leader. For his pre-military training, Oleg completed practical engineering (PE) studies at the Israeli Air-Force College, focusing on networks, computer communications and microelectronics. In addition, Oleg holds both Bachelor’s and Master’s degrees in international business law as well as a degree in business and management, all with honors, from the Inter-Disciplinary Center (IDC) Herzliya, Israel. Oleg teaches the “Legal Aspect of Entrepreneurship” course at Ben-Gurion University, serves as a mentor in various technological programs, incubators and accelerators, and is a frequent speaker in various technological events.

Dudu Mimran

CTO

Dudu Mimran

CTO

Dudu Mimran is the CTO of Telekom Innovation Laboratories Israel. He is a seasoned technical and business executive in the areas of big data, AI, IoT, cyber security, the cloud, fintech, and telecommunications, with expertise in innovation, business and technology strategy, enterprise digital transformation, and team building. He is the founder of multiple startup companies and the inventor of over 50 patents. In addition, he has developed dozens of innovative products, taking them from ideation to product delivery, written and spoken extensively on technology and other areas, and shares his expertise by serving as a mentor for startups and teaching at innovation centers.

Rami Puzis

Department of Software and Information Systems Engineering

Rami Puzis

Department of Software and Information Systems Engineering

Rami Puzis is a Senior Lecturer (Assistant Professor) in the Department of Software and Information Systems Engineering at the Ben-Gurion University of the Negev. He received his B.Sc. degree in Software Engineering, M.Sc. in Information Systems Engineering, and Ph.D. from BGU. The topic of his dissertation was the deployment of distributed network intrusion detection systems. He was a research associate in the Laboratory of Computational Cultural Dynamics at the University of Maryland. His primary specialization is in the area of complex networks analysis with applications to cyber security, and social and communication network analysis. He has been the principal investigator of a series of research projects funded by Deutsche Telekom AG, the Israeli Ministry of Defense and Ministry of Economy, and several leading cyber security companies.

Asaf Shabtai

Department of Software and Information Systems Engineering

Asaf Shabtai

Department of Software and Information Systems Engineering

Dr Asaf Shabtai is a senior lecturer (Assistant Prof.) at the Department of Software and Information Systems Engineering at Ben-Gurion University. Asaf is a recognized expert in information systems security and has led several large-scale projects and researches in this field. His main areas of interest are computer and network security,  machine learning, cyber intelligence, security awareness, security of IoT and smart mobile devices, social network analysis, and security of avionic and operational technologies (OT) systems. Asaf holds a B.Sc. in Mathematics and Computer Science (1998); B.Sc. in Information Systems Engineering (1998); a M.Sc. in Information Systems Engineering (2003) and a Ph.D. in Information Systems Engineering (2011) all from Ben-Gurion University. Since 2005, Asaf has been a principle investigator and project manager of various research projects funded by Deutsche Telekom AG, (Telekom Innovation Laboratories @ BGU), Israeli Ministry of Defense, Israeli Ministry of Trade and Commerce, and several leading cyber security companies. Asaf has published over 70 refereed papers in leading peer-reviewed journals and conferences. In addition, he has co-authored a book on information leakage detection and prevention. Asaf also received the Toronto Award for young scientists in 2017.

Lior Rokach

Head of Department of Software and Information Systems Engineering

Lior Rokach

Head of Department of Software and Information Systems Engineering

Lior Rokach is a data scientist and Professor in the Department of Software and Information Systems Engineering at Ben-Gurion University of the Negev where he serves as the head of the department. He established the Machine Learning and Big Data labs at BGU which promote innovative adaptations of machine learning and data science methods to create the next generation of intelligent systems. Lior has made significant contributions to the cyber security field by developing machine learning algorithms that are capable of identifying malwares and protecting user data and privacy.
Lior joined BGU in 2005 after receiving a B.Sc. (summa cum laude), M.Sc. (cum laude), and Ph.D. from Tel Aviv University. He is the author of over 100 peer reviewed papers in leading journals and six books including Data Leakage Detection and Prevention, Pattern Classification Using Ensemble Methods, Data Mining with Decision Trees, and Decomposition Methodology for Knowledge Discovery and Data Mining. He is also co-editor of several handbooks published by Springer (Data Mining and Knowledge Discovery Handbook and Recommender Systems Handbook), and he is currently co-editing the Handbook of Computational Intelligence in Cyber Security.

Bracha Shapira

Department of Software and Information Systems Engineering

Bracha Shapira

Department of Software and Information Systems Engineering

Bracha Shapira is a professor in the Department of Software and Information Systems Engineering at Ben-Gurion University of the Negev and the incumbent of the Carole Weinstein Chair in Information Systems Engineering. She served as the Chair of the department between 2011 and 2017 and is now BGU’s Deputy Dean of the Faculty of Engineering Sciences. She is a researcher at the Telecom Innovation Laboratories at BGU and BGU’s Cyber Security Center. She is a graduate of Hebrew University in Jerusalem (M.Sc. in Computer Science) and Ben-Gurion University of the Negev (Ph.D. in Information Systems Engineering). She leads numerous research projects related to personalization, user profiling, privacy, and the application of machine learning methods to cyber security and recommender systems. She has authored more than 120 papers in various leading conferences and journals.

Yehudith Naftalovich

Director of Operations & Finance

Yehudith Naftalovich

Director of Operations & Finance

Mrs. Naftalovitch orchestrates the activities of multiple research labs working with local and multi-national companies. Among her responsibilities are budget planning and management, contracts initiation and maintenance, human resources strategy and implementation, businesses and university relationship management.