Formal Methods for Information Protection Technology. Task 2: Mathematical Foundations, Architecture and Principles of Implementation of Multi-Agent Learning Components for Attack Detection in Computer Networks. Part 2

Abstract

Abstract : The use of open computer networks as an environment for exchange of information across the globe in distributed applications requires improved security measures on the network, in particular, to information resources used in applications. Integrity, confidentiality and availability of the network resources must be assured. To detect and suppress different types of computer unauthorized intrusions, modern network security systems (NSS) must be armed with various protection means and be able to accumulate experience in order to increase its ability to front against known types of intrusions, and to learn new types of intrusions. The project will perform three main tasks. 1. Develop a mathematical model and a tool that simulates various coordinated intrusion scenarios against computer networks; 2. Develop the mathematical foundations, architecture, and principles of implementation of autonomous-software-tool technology implementing the learning system for intrusion detection; 3. Develop the fundamentals, architecture and software for the computer security system based on multi-level encoding for information protection in mass application. To detect and suppress different types of computer intrusions, modern NSS must be able to accumulate experience in order to increase its ability to front against known type of attacks/intrusions and to learn unknown simple and complex, local and distributed types of attacks. This requires the use of a powerful intelligent learning subsystem (LS) in NSS. That is why the second task of the project concerns to the development of the formal model, architecture, and software prototype of the autonomous intelligent learning system for detection of the attacks/intrusions against computer network.