Autonomous Cognitive Model and Analysis for Survivable System

Yiwei Liao,Guosheng Zhao,Jian Wang

doi:10.1155/2020/3618284

Abstract

The research on autonomous recognition mechanism for survivability has vigorously been growing up. A method of autonomous cognitive model and quantitative analysis for survivable system was proposed based on cognitive computing technology. Firstly, a cognitive model for survivable system with cross-layer perception ability was established, a self-feedback evolution mode of cognitive unit based on monitor-decide-execute loop structure was improved, and a self-configuration of cognitive unit is realized. Then, combined with the cognitive state transition graph, the analysis of cognitive performance for survivable systems based on dynamic cognitive behavioral changes was constructed. Finally, the cognitive processes of survivable system were described by using formal modeling. Simulation validated the influence degree of test parameters on system survivability from two perspectives of the probability of intrusion detection systems vulnerability and attacks detected. Results show that enhancing the rate of monitoring actions change and the rate of performing actions change obviously improved the cognitive performance of survivable system.

Highlights

Survivability is a hot topic in the research on the nextgeneration Internet security
Recognition refers to the ability that the system possesses to “know” and “feel” the current system’s survival situation [11]
Recognition means the system’s response and adaptability when systems face malicious intrusion [13], which can reflect systems’ ability to assess its own security status and surrounding working environment, which can be analyzed from its recognition rate of security incidents and the recognition time of nonsecurity incidents

Summary

Introduction

Survivability is a hot topic in the research on the nextgeneration Internet security. Recognition reflects the system’s autonomous cognition of its own survival situations and securities of the scene and environment. The cross-layer perception is used to obtain the autonomous reasoning, dynamic decision-making, and resource reallocation of survivable systems, and to realize the self-adaptation to dynamic changes of the cognitive needs and environment security. Cognitive model should reach a balance between formal description and cognitive abstraction, so it can accurately describe and reflect the system’s recognition, and facilitate reasoning, providing theoretical support for the study of cognitive ability of survivable system. E service cognitive layer reflects the recognition of the matching ability of providing Internet resources required for applications and users It can serve high QoS service in complex environment, where massive, incomplete, or even malicious service scenarios exist.

Cognitive Process of Formal Modeling

E Action output

H P K G Z1 Z2 Z3 W1 W2 L1 P1 L2 h1 L3 S1 L4 P2 L5 S2 L6 S3

G C D SH SD

Findings

Conclusion