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DS4CS 2021 : IEEE CSR Workshop on Data Science for Cyber Security | |||||||||||||||
Link: https://www.ieee-csr.org/workshops/ds4cs/ | |||||||||||||||
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Call For Papers | |||||||||||||||
CALL FOR PAPERS
---------------------------------------------------- DS4CS 2021: IEEE Workshop on Data Science for Cyber Security Held in conjunction with the International Conference on Cyber Security and Resilience (CSR 2021) Virtual Conference, 26-28 July 2021 Website: https://www.ieee-csr.org/workshops/ds4cs Twitter: https://twitter.com/ds4cs Facebook: https://www.facebook.com/ds4cs/ Link: https://www.ieee-csr.org/workshops/DS4CS_CFP.pdf OBJECTIVE ---------------------------------------------------- Over the years cyber-threats have increased in numbers and sophistication; adversaries now use a vast set of tools and tactics to attack their victims with their motivations ranging from intelligence collection to destruction or financial gain. Lately, the introduction of IoT devices on a number of applications, spanning from home automation to monitoring of critical infrastructures, has created an even more complicated cyber-defense landscape. The sheer number of IoT devices deployed globally, most of which are readily accessible and easily hacked, allows threat actors to use them as the cyber-weapon delivery system of choice in many today's cyber-attacks, ranging from botnet-building for DDoS attacks, to malware spreading and spamming. Staying on top of these evolving cyber-threats has become an increasingly difficult task that nowadays entails the collection, analysis, and leveraging of huge volumes of data and requires methodologies and techniques located at the intersection of statistics, data mining, machine learning, visualization and big data. Although the application of Data Science methodology to the Cyber Security domain is a relative new topic, it steadily gathers the interest of the research community as showcased by the utilization of data science techniques in a variety of cyber-defense facets that include proactive technologies (e.g., cyber threat intelligence gathering and sharing), platform profiling (e.g., trust calculation and blacklisting), attack detection/mitigation (e.g., active network monitoring, situational awareness, and adaptable mitigation strategies), and others. This workshop aims to spotlight cutting-edge research in data science driven cyber-security in academia, business and government, as well as help in the alignment of these endeavors. WORKSHOP TOPICS ---------------------------------------------------- Prospective authors are encouraged to submit previously unpublished contributions from a broad range of topics, which include but are not limited to the following: - Big data-driven cyber-security (incl. analytics, management) - Machine and deep learning methods for cyber-security (incl. malware/phishing/botnet/ spam/intrusion/anomaly detection) - Visualization methods (incl. visual situation awareness, VR & AR visualization, real-time visualization) - AI-driven cybersecurity - Private information retrieval - Cyber-threat intelligence collection, identification and sharing at scale - Private/sensitive information protection - Machine-learning powered traffic analysis and attack modelling - Machine learning-based platform profiling and trust management - Advanced attack detection and mitigation IMPORTANT DATES ---------------------------------------------------- Workshop papers' deadline: April 19, 2021 Workshop authors' notification: May 3, 2021 Camera-ready submission: May 10, 2021 Early registration deadline: May 31, 2021 Workshop's date: July 26, 2021 SUBMISSION ---------------------------------------------------- Submitted manuscripts should not exceed 6 pages (plus 2 extra pages, being subject to overlength page charges) and should be of sufficient detail to be evaluated by expert reviewers in the field. The workshop's proceedings will be published by IEEE and will be included in IEEE Xplore. Detailed information about the paper submission and guidelines to authors can be found at the conference's website https://www.ieee-csr.org/instructions/ Workshop Chairs ---------------------------------------------------- Christos Tryfonopoulos, University of the Peloponnese (GR) Spiros Skiadopoulos, University of the Peloponnese (GR) Stratos Idreos, Harvard University (US) Publicity chair ---------------------------------------------------- Paraskevi Raftopoulou, University of the Peloponnese (GR) Program Committee ---------------------------------------------------- Christos Anagnostopoulos, University of Glasgow (UK) Avi Arampatzis, Democritus University of Thrace (GR) Denilson Barbosa, University of Alberta (CA) Srikanta Bedathur, IIT Delhi (IN) Christos Dimitrakakis, University of Oslo (NO) Gabriel Ghinita, University of Massachusetts at Boston (US) Aris Gkoulalas-Divanis, IBM Watson (US) Christos Iliou, CERTH (GR) and Bournemouth University (UK) Mouna Kacimi, Free University of Bozen-Bolzano (IT) Panos Kalnis, King Abdullah University of Science and Technology (SA) Gjergji Kasneci, University of Tübingen (DE) Aniket Kate, Purdue University (US) George Kollios, Boston University (US) George Lepouras, University of the Peloponnese (GR) Ida Mele, IASI-CNR (IT) Dimitris Michail, Harokopio University of Athens (GR) Katerina Mitrokotsa, Chalmers University of Technology (SE) Luis Munoz Gonzalez, Imperial College London (UK) Kim Pecina, DIaLOGIKa GmbH (DE) Nikos Platis, University of the Peloponnese (GR) Neoklis Polyzotis, Google (US) Panagiotis Rizomiliotis, Harokopio University of Athens (GR) Alkis Simitsis, Athena Research Center (GR) Marco Squarcina, TU Wien (AT) Theodora Tsikrika, CERTH (GR) Ioannis Tsimperidis, Democritus University of Thrace (GR) Thanasis Vergoulis, Athena Research Center (GR) -- |
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