Pso Based Intrusion Detection: A Pre-Implementation Discussion

Bekri, Mohamed El; Diouri, Ouafaa

doi:10.1016/j.procs.2019.11.002

Cited by 6 publications

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Dhaliwal et al 25 , Pattawaro et al 26 , and Jiang 27 , deployed XGBoost for dimensionality reduction to reduce the irrelevant features for intrusion detection. Ghosh et al 28 , El Bekri 29 , and Li 30 have applied particle swarm optimization (PSO) for feature selection and classification.…”

Section: Related Workmentioning

confidence: 99%

Retracted: An empirical intrusion detection system based on XGBoost and bidirectional long‐short term model for 5G and other telecommunication technologies

Karthikraja¹,

Senthilkumar²,

Rajadurai

et al. 2022

Computational Intelligence

View full text Add to dashboard Cite

Recently, intrusion detection system (IDS) has become an essential remedy to protect networks from malicious activities and attacks. The attacks force the network activities under risk and cause network data as an unrecoverable one. The attacks have different features in nature and their detection rate is low. An efficient attack detection system requires a huge volume of network transactions and relevant features for training. But the existing datasets have significant and nonsignificant features together. Hence, the significant feature selection plays a major role to detect the attacks. For this reason, this paper adopts the XGBoost approach to identify the relevant (significant) features of the attacks in the dataset. After this XGBoost, this article applies the bidirectional long short term model (Bi-LSTM) for the detection and classification of the attacks. This Bi-LSTM model is a novel approach to the IDS and very effective to increase the detection rate. Thus, this article focuses on feature reduction and classification of the attacks.The experimental results show that the proposed 1216

show abstract

Section: Related Workmentioning

confidence: 99%

Retracted: An empirical intrusion detection system based on XGBoost and bidirectional long‐short term model for 5G and other telecommunication technologies

Karthikraja¹,

Senthilkumar²,

Rajadurai

et al. 2022

Computational Intelligence

View full text Add to dashboard Cite

show abstract

“…The movement of a particle is constrained by its velocity and memory of locations where the objective of the search space is to explore the objective function with minimum cost. While applying PSO in IDS, it is important to consider different factors such as the search space, particle’s initialization pattern, swarm size, and particle dynamics, and they are established in the work of El Bekri et al [ 32 ]. The authors have tried to combine data-mining techniques together with PSO for intrusion detection.…”

Section: Related Workmentioning

confidence: 99%

Plant and Salamander Inspired Network Attack Detection and Data Recovery Model

Sharma

Issac

Xin

et al. 2023

Sensors

View full text Add to dashboard Cite

The number of users of the Internet has been continuously rising, with an estimated 5.1 billion users in 2023, which comprises around 64.7% of the total world population. This indicates the rise of more connected devices to the network. On average, 30,000 websites are hacked daily, and nearly 64% of companies worldwide experience at least one type of cyberattack. As per IDC’s 2022 Ransomware study, two-thirds of global organizations were hit by a ransomware attack that year. This creates the desire for a more robust and evolutionary attack detection and recovery model. One aspect of the study is the bio-inspiration models. This is because of the natural ability of living organisms to withstand various odd circumstances and overcome them with an optimization strategy. In contrast to the limitations of machine learning models with the need for quality datasets and computational availability, bio-inspired models can perform in low computational environments, and their performances are designed to evolve naturally with time. This study concentrates on exploring the evolutionary defence mechanism in plants and understanding how plants react to any known external attacks and how the response mechanism changes to unknown attacks. This study also explores how regenerative models, such as salamander limb regeneration, could build a network recovery system where services could be automatically activated after a network attack, and data could be recovered automatically by the network after a ransomware-like attack. The performance of the proposed model is compared to open-source IDS Snort and data recovery systems such as Burp and Casandra.

show abstract

“…The subordinate heuristic can be procedures, a simple local search, or simply a construction method [187]. The following are algorithms of meta-heuristic methods: Artificial Immune Systems (AIS) [55], Ant Colony Optimization (ACO) [47], Genetic Algorithms [175], particle Swarm Optimization (PSO) [101,52], etc. Thus, Genetic Algorithms (GA) are one of the most known meta-heuristics.…”

Section: Meta-heuristicsmentioning

confidence: 99%

A Survey on Multi-Agent Based Collaborative Intrusion Detection Systems

Bougueroua

Mazouzi

Belaoued

et al. 2021

Journal of Artificial Intelligence and Soft Computing Research

View full text Add to dashboard Cite

Multi-Agent Systems (MAS) have been widely used in many areas like modeling and simulation of complex phenomena, and distributed problem solving. Likewise, MAS have been used in cyber-security, to build more efficient Intrusion Detection Systems (IDS), namely Collaborative Intrusion Detection Systems (CIDS). This work presents a taxonomy for classifying the methods used to design intrusion detection systems, and how such methods were used alongside with MAS in order to build IDS that are deployed in distributed environments, resulting in the emergence of CIDS. The proposed taxonomy, consists of three parts: 1) general architecture of CIDS, 2) the used agent technology, and 3) decision techniques, in which used technologies are presented. The proposed taxonomy reviews and classifies the most relevant works in this topic and highlights open research issues in view of recent and emerging threats. Thus, this work provides a good insight regarding past, current, and future solutions for CIDS, and helps both researchers and professionals design more effective solutions.

show abstract

Pso Based Intrusion Detection: A Pre-Implementation Discussion

Cited by 6 publications

References 6 publications

Retracted: An empirical intrusion detection system based on XGBoost and bidirectional long‐short term model for 5G and other telecommunication technologies

Retracted: An empirical intrusion detection system based on XGBoost and bidirectional long‐short term model for 5G and other telecommunication technologies

Plant and Salamander Inspired Network Attack Detection and Data Recovery Model

A Survey on Multi-Agent Based Collaborative Intrusion Detection Systems

Contact Info

Product

Resources

About