preventive action
Multi-Agent Optimization for Safety Analysis of Cyber-Physical Systems: Position Paper
Gürcan, Önder, Yakymets, Nataliya, Tucci-Piergiovanni, Sara, Radermacher, Ansgar
Failure Mode, Effects and Criticality Analysis (FMECA) is one of the safety analysis methods recommended by most of the international standards. The classical FMECA is made in a form of a table filled in either manually or by using safety analysis tools. In both cases, the design engineers have to choose the trade-offs between safety and other development constraints. In the case of complex cyber-physical systems (CPS) with thousands of specified constraints, this may lead to severe problems and significantly impact the overall criticality of CPS. In this paper, we propose to adopt optimization techniques to automate the decision making process conducted after FMECA of CPS. We describe a multi-agent based optimization method which extends classical FMECA for offering optimal solutions in terms of criticality and development constraints of CPS.
Credential Stuffing Attack: Countermeasures using Patterns and Machine Learning
"Credential Stuffing Attack" is a less known and highly successful cyber-attack launched against web portals. It exploits the human behavior of re-using the passwords for ease to memorize and the weakness in defense technologies. A bad actor gets hold of user's credentials leaked from a website and tries the same set of credentials on different websites for further access on user's data. Traditional defense mechanism deployed by web portals fail to defend against this attack as it's a very silent, slow and evade the signature-based rules. Most of the small and medium scale web portals find it difficult to detect the attack.
Proactive Intervention to Downtrend Employee Attrition using Artificial Intelligence Techniques
Barvey, Aasheesh, Kapila, Jitin, Pathak, Kumarjit
To predict the employee attrition beforehand and to enable management to take individualized preventive action. Using Ensemble classification modeling techniques and Linear Regression. Model could predict over 91% accurate employee prediction, lead-time in separation and individual reasons causing attrition. Prior intimation of employee attrition enables manager to take preventive actions to retain employee or to manage the business consequences of attrition. Once deployed this will model can help in downtrend Employee Attrition, will help manager to manage team more effectively. Model does not cover the natural calamities, and unforeseen events occurring at an individual level like accident, death etc.