METHOD OF SYNTHESIS OF POPULATION ALGORITHMS IN THE ARCHITECTURE OF DECEPTIVE SYSTEMS WITH BAITS AND TRAPS

Abstract

In the work, a new method of synthesis of the algorithm of discrete optimization of moth and flame in the architecture of deceptive systems with decoys and traps is developed. In contrast to known approaches, the proposed method provides the formation of a discrete search space with a coordinate representation of objects, the synthesis of a spiral trace based on the dynamic movement of the moth and flame to avoid premature convergence to local optima.

Setting the problem of choosing the next steps of deception systems, which includes the management of decoys and traps and their adjustment in the process of responding to events, is considered as an optimization problem. Its purpose is to increase the effectiveness of detection of computer attacks and malicious software in corporate networks. The changing parameters are the operating steps of deception systems, process models, and architectural features, and the limitations are the characteristics of the operating environment of corporate networks.

The proposed method makes it possible to ensure finding the optimal sequence of steps in changing conditions, including the possibility of their operational adaptation to the attacker's actions. This, in turn, enables the creation of deceptive systems capable of long-term autonomous functioning without the constant involvement of administrators and with increased resistance to recognition of their working principles by attackers.

The conducted experiments showed the prospects of the proposed direction of research and synthesis in the architecture of deceptive systems of population algorithms for optimizing their choice of further steps.

Prospects for further research are in deepening the integration of population algorithms into the architecture of deceptive systems with baits and traps, as well as in developing a method of organizing their functioning in accordance with the proposed conceptual model. The results of the work are aimed at increasing the level of cyber protection of corporate networks through the creation of intelligent adaptive systems for countering modern self-propelled missiles and anti-aircraft weapons.