Digital Transaction Cyber-Attack Detection Using Particle Swarm Optimization

Title

Digital Transaction Cyber-Attack Detection Using Particle Swarm Optimization

Creator

Monisha N.; Gunvanth G.; Jayapandian N.

Description

The cyber digital world is an essential variant in day-to-day life in advanced technology. There is a better change in the lifestyle as intelligent technology. In larger excite to increase the advanced technology which can be developed to humans in major dependent on network and internet users. Now, in modern times, the internet has changed the primary need in human lifestyle by giving access to everything in the world while sitting in one place knowing and updating the information and usage of online subscribers or Revolution. The world is moving in Rapid and Faster communications within a fraction of a second, at a lesser cost, and it has minimal paper-based processes and relies on the digitization document instead of a paperless environment. The data is handled by finch security practices, which are used in security worldwide to establish protected data management systems like digital lending, credits, mobile Banking, and mobile payment. Cryptocurrency and blockchain, B-trading, and banking as a service are included. At the same time, leveraging the new technologies is to resist hacking cyber-attacks. This article is also involved in artificial intelligence and machine learning (AI&ML) in different cyber-attacks. This article focuses on genetic algorithms to detect the cyber-attack. The main aim of the detection is future to prevent these cyber-attacks. The comparison will take two sample genetic algorithms. The first one is taken for Ant Colony Optimization (ACO), and the proposed model is taken for Particle Swarm Optimization. The average attack detection of ACO algorithm is 45 packets at the same time PSO algorithm will detect 50 packets. 2023 IEEE.

Source

Proceedings of the 4th IEEE International Conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2023

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Cyber-attacks; Deep Learning; Digital Transaction; Genetic Algorithm; Machine Learning; Particle Swarm Optimization

Coverage

Monisha N., Christ (Deemed To Be University), Department Of Cse, India; Gunvanth G., Christ (Deemed To Be University), Department Of Civil Engineering, India; Jayapandian N., Christ (Deemed To Be University), Department Of Cse, India

Rights

Restricted Access

Relation

ISBN: 979-835038462-8

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICSTCEE60504.2023.10585244

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