2 results match your criteria: "Saint-Petersburg University of State Fire Service of EMERCOM of Russia[Affiliation]"
Static Analysis of Information Systems for IoT Cyber Security: A Survey of Machine Learning Approaches.
Sensors (Basel)
February 2022
Department of Applied Mathematics and Information Technologies, Saint-Petersburg University of State Fire Service of EMERCOM of Russia, 196105 Saint-Petersburg, Russia.
Article Synopsis
- Modern IoT systems require advanced security measures, and static analysis has proven effective in analyzing their software, but increasing complexity necessitates the automation of this process.
- A hypothesis is proposed suggesting that machine learning can enhance static analysis for IoT systems, leading to a structured research approach that confirms this applicability and establishes a framework.
- Key contributions include systemizing static analysis stages, formalizing machine-learning models, reviewing related publications, proving machine learning's utility at various analysis stages, and presenting an intelligent framework for IoT static analysis.
Analytical Modeling for Identification of the Machine Code Architecture of Cyberphysical Devices in Smart Homes.
Sensors (Basel)
January 2022
Department of Applied Mathematics and Information Technologies, Saint-Petersburg University of State Fire Service of EMERCOM of Russia, 196105 Saint-Petersburg, Russia.
Ensuring the security of modern cyberphysical devices is the most important task of the modern world. The reason for this is that such devices can cause not only informational, but also physical damage. One of the approaches to solving the problem is the static analysis of the machine code of the firmware of such devices.
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