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, theintroduction of IoT devices on a number of domains, ranging from smart applications (e.g., smart cities/grids/agriculture) to goods and infrastructure monitoring (e.g., transportation/logistics/powermonitoring), 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 and protecting the underlying equipment have become increasingly difficult tasksthat nowadays entailthe collection, analysis, and leveraging of huge volumes of data and require 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 and this year it emphasizes on the usage of such techniques on important applications such as drone/fleet/vehicle management, transportation/logistics/supply chain monitoring, and smart cities/agriculture/mobility.
Prospective authors are encouraged to submit previously unpublished contributions from a broad range of topics, which include but are not limited to the following: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/sensitive information operation (incl. retrieval, protection, extraction)
› Cyber-threat intelligence collection, identification and sharing at scale
› Machine-learning powered security (incl. traffic analysis, attack modelling, platform profiling and trust management)
› Advanced attack detection and mitigation
› Data science driven cyber-security for monitoring and management (incl. fleet/drone/ vehicle/transportation/logistics/ supply chain)
› Data science driven cyber-security for smart applications (incl. mobility/agriculture/ cities)
Paper submission deadline: March 15 April 20, 2023 AoE
Authors’ notification: April 1 April 25, 2023 AoE
Camera-ready submission: April 15 May 3, 2023 AoE
Early registration deadline: May 5, 2023 AoE
Workshop date: July 31- August 2, 2023
The workshop’s proceedings will be published by IEEE and will be included in IEEE Xplore. The guidelines for authors, manuscript preparation guidelines, and policies of the IEEE CSR conference are applicable to DS4CS 2023 workshop. Please visit the authors’ instructions page for more details. When submitting your manuscript via the conference management system, please make sure that the workshop’s track 2T4 DS4CS is selected in the Topic Areas drop down list.
Workshop chairs
Christos Tryfonopoulos, University of the Peloponnese (GR)
Spiros Skiadopoulos, University of the Peloponnese (GR)
Anish Jindal, Durham University (UK)
Publicity chair
Paraskevi Raftopoulou, University of the Peloponnese (GR)
Contact us
trifon AT uop.gr
spiros AT uop.gr
anish.jindal AT durham.ac.uk
Program committee
Christos Anagnostopoulos, University of Glasgow (UK)
Gagangeet Singh Aujla, Durham University (UK)
Denilson Barbosa, University of Alberta (CA)
Srikanta Bedathur, IIT Delhi (IN)
Giampaolo Bovenzi, University of Napoli Federico II (IT)
Theodore Dalamagas, Athena Research Center (GR)
Christos Dimitrakakis, University of Oslo (NO)
Gabriel Ghinita, University of Massachusetts at Boston (US)
Aris Gkoulalas-Divanis, IBM Watson (US)
Antonios Gouglidis, Lancaster Univeristy (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)
George Kollios, Boston University (US)
George Lepouras, University of the Peloponnese (GR)
Dongzhu Liu, University of Glasgow (UK)
Ida Mele, IASI-CNR (IT)
Dimitris Michail, Harokopio University of Athens (GR)
Antonio Montieri, University of Napoli Federico II (IT)
Luis Munoz Gonzalez, Imperial College London (UK)
Kim Pecina, DIaLOGIKa GmbH (DE)
Nikos Platis, University of the Peloponnese (GR)
Panagiotis Rizomiliotis, Harokopio University of Athens (GR)
Nguyen Truong, University of Glasgow (UK)
Theodora Tsikrika, Centre for Research and Technology (GR)
Sandeep Shukla, IIT Kanpur (IN)
Giannis Tsimperidis, Democritus University of Thrace (GR)
Thanasis Vergoulis, Athena Research Center (GR)
This workshop is supported in part by project ENIRISST+ under grant agreement No. MIS 5047041 from the General Secretary for ERDF & CF, under Operational Programme Competitiveness, En- trepreneurship and Innovation 2014-2020 (EPAnEK) of the Greek Ministry of Economy and Development (co-financed by Greece and the EU through the Euro- pean Regional Development Fund) – https://www.enirisst-plus.gr