C01: Collective, distributed and multi-criteria decision-making approaches for supporting Cyber-Physical Security Analytics

Paper Submission for C01

SMC2018:C01 submission site (external site)

Abstracts

Data science techniques and decision support tools play a key role in the latest advances made in a sheer variety of physical/cyber-security analytics domains, such as: video-surveillance, intrusion and insider threat detection, financial fraud identification, etc. Continuous feedback processes between system and human analyst(s) become paramount to capture the dynamic, continuously evolving nature of the information being analysed in such domains, to ultimately make optimal decisions within the given context. Notwithstanding, single-analyst or single-criterion decisions are no longer suitable, as we enter an increasingly connected and distributed society with security-related data pertaining multiple dimensions of information, demanding confidence, trust, and integrity of decisions (among other reasons). This raises the notable challenges of accommodating group (multiple analysts with diverse opinions and viewpoints) and multi-criteria approaches as part of the human-machine decision support processes. To cope with these challenges, this session covers – but is not limited to – recent advances in the following topics: methodologies, models, intelligent/interactive techniques, data-driven approaches, simulations and case studies, experimental evaluations and implementations related to multi-criteria, group and decision-making approaches applied to: analytics scenarios pertaining cyber-physical security analytics, e.g. intrusion detection, authentication, insider threats, monitoring systems, financial data analytics, blockchain technologies, smart-cities and intelligent transportation systems, etc.

Session Chairs