Big Data: Threat Landscape and Protection Gap Analysis
The advent of IoT and cloud services has resulted in collecting and sharing massive amounts of data. From a security perspective, these data represents a valuable target for attackers. As data-driven processes become integrated in the fabric of business, the entire society is becoming increasingly vulnerable to threats to data reliability and availability. Finally, the increase in redundancy of data available for collection, analysis and dissemination have strained traditional rules to protect privacy and confidentiality. The Big Data threat landscape continues to evolve. Opportunistic one-shot attacks have been supplemented by leakages that are more persistent and, in many cases, far more worrisome. This means that we need to start designing Big Data systems not just to prevent attacks and recover from them, but also to detect successful attackers quickly and contain them so that any data leakage can be identified and countered. This talk starts by introducing the emerging Big Data Threat Landscape with reference to some vertical domains and performs a Protection Gap Analysis to list some known vulnerabilities. Then a paradigm of Detect, Contain and Recover is introduced as a practical foundation for managing risks connected to Big Data.
Ernesto Damiani is currently Director of the Information Security Research Center at Khalifa University of Technology, Abu Dhabi. He is the leader of the Big Data Initiative at the Etisalat British Telecom Innovation Center (EBTIC). Ernesto is on extended leave from the Department of Computer Science, Università degli Studi di Milano, Italy, where he leads the SESAR research lab and has served the Head of the Ph.D. Program in Computer Science for many years. Ernesto’s research interests include secure cloud-based architectures, privacy-preserving Big Data analytics and Cyber-Physical Systems security. Ernesto holds/has held visiting positions at a number of international institutions, including George Mason University in Virginia, US, Tokyo Denki University, Japan, LaTrobe University in Melbourne, Australia, and the Institut National des Sciences Appliquées (INSA) at Lyon, France. He is a Fellow of the Japanese Society for the Progress of Science.
Ernesto is currently the Principal Investigator of the Toreador project, funded by the European Commission in the framework of the ICT-16-2015: Big data – Research call. In the past, he has been Principal Investigator in a number of large-scale research projects funded by the European Commission, the Italian Ministry of Research and by private companies such as British Telecom, Cisco Systems, SAP, Telecom Italia, Siemens Networks (now Nokia Siemens) and many others. Ernesto serves in the editorial board of several international journals; among others, he is the EIC of the International Journal on Big Data and of the International Journal of Knowledge and Learning. He is Associate Editor of IEEE Transactions on Service-oriented Computing and of the IEEE Transactions on Fuzzy Systems. Ernesto is a senior member of the IEEE and served as Vice-Chair of the IEEE Technical Committee on Industrial Informatics. In 2008, Ernesto was nominated ACM Distinguished Scientist and received the Chester Sall Award from the IEEE Industrial Electronics Society. Ernesto has co-authored over 350 scientific papers and many international patents and books, including “Open Source Systems Security Certification” (Springer 2009).
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