CONSTRUCTION OF ATTACK DETECTION SYSTEMS IN INFORMATION NETWORKS ON NEURAL NETWORK STRUCTURES

Abstract

Systems for detecting network intrusions and detecting signs of attacks on information systems have long been used as one of the necessary lines of defense of information systems. Today, intrusion and attack detection systems are usually software or hardware-software solutions that automate the process of monitoring events occurring in an information system or network, as well as independently analyze these events in search of signs of security problems. As the number of different types and ways of organizing unauthorized intrusions into foreign networks has increased significantly in recent years, attack detection systems (ATS) have become a necessary component of the security infrastructure of most organizations. The article proposes a software prototype of a network attack detection system based on selected methods of data mining and neural network structures. The conducted experimental researches confirm efficiency of the created model of detection for protection of an information network. Experiments with a software prototype showed high quality detection of network attacks based on neural network structures and methods of intelligent data distribution. The state of protection of information systems to counter cyber attacks is analyzed, which made it possible to draw conclusions that to ensure the security of cyberspace it is necessary to implement a set of systems and protection mechanisms, namely systems: delimitation of user access; firewall; cryptographic protection of information; virtual private networks; anti-virus protection of ITS elements; detection and prevention of intrusions; authentication, authorization and audit; data loss prevention; security and event management; security management.