MAIS-IDS: A distributed intrusion detection system using multi-agent AIS approach

Seresht, Neda Afzali; Azmi, Reza

doi:10.1016/j.engappai.2014.06.022

Cited by 63 publications

(6 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The three immunological theories used in the AIS-clonal selection, immune networks, and negative selection-are briefly discussed in the following sections. [40][41][42].…”

Section: Artificial Immune System Approachesmentioning

confidence: 99%

Cost-effective clonal selection and AIS-based load balancing in cloud computing environment

Mosayebi¹,

Azmi²

2023

Preprint

Self Cite

View full text Add to dashboard Cite

One of the challenges in cloud computing is increasing efficiency, which calls for the application of task scheduling and load balancing. Numerous load-balancing methods that have been suggested for the cloud environment can increase efficiency. The Throttled policy is one of them that aids in evenly distributing user requests among virtual machines. In the first part of this article, we examined the cost of the Clonal selection algorithm with Throttled load balancing Policy and the Clonal selection algorithm with Distributed Service Broker Policy and contrasted them to the clonal selection and other immune systems mechanisms. Additionally, we suggest two additional mechanisms based on the artificial immune system. In the two proposed mechanisms, algorithms are introduced so that by benefiting from load balancing policies when receiving requests from users, in the shortest possible time and the fastest processing of data and with the lowest cost, they respond to users. In the second part, we introduce two other new algorithms that were created as a result of combining an evolutionary algorithm with the artificial immune system mechanisms. Algorithms have been evaluated and compared with other algorithms using the Cloud Analyst simulator in terms of average response time, average data center processing time, total data transfer cost, and total cost. The results attained show how much better the suggested algorithms are.

show abstract

“…The three immunological theories used in the AIS-clonal selection, immune networks, and negative selection-are briefly discussed in the following sections. [40][41][42].…”

Section: Artificial Immune System Approachesmentioning

confidence: 99%

Cost-effective clonal selection and AIS-based load balancing in cloud computing environment

Mosayebi¹,

Azmi²

2023

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The authors have also used a detector evolutionary process based on the gene evolution process. In the work of Seresht et al [ 46 ], an agent-based approach with inspiration from AIS is proposed for a distributed intrusion detection system. The proposed system MAIS-IDS is a composite system that analyses the traffic of network as well as the host.…”

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

“…Seresht and Azmi [57] proposed a distributed intrusion detection system using a multi-agent AIS approach (MAIS-IDS). It is a hybrid anomaly IDS that analyses system-setting and network trafc.…”

Section: Multi-agent Architecturesmentioning

confidence: 99%

A Flow-based Multi-agent Data Exfiltration Detection Architecture for Ultra-low Latency Networks

Marques

Epiphaniou

Al-Khateeb

et al. 2021

ACM Trans. Internet Technol.

View full text Add to dashboard Cite

Modern network infrastructures host converged applications that demand rapid elasticity of services, increased security, and ultra-fast reaction times. The Tactile Internet promises to facilitate the delivery of these services while enabling new economies of scale for high fidelity of machine-to-machine and human-to-machine interactions. Unavoidably, critical mission systems served by the Tactile Internet manifest high demands not only for high speed and reliable communications but equally, the ability to rapidly identify and mitigate threats and vulnerabilities. This article proposes a novel Multi-Agent Data Exfiltration Detector Architecture (MADEX), inspired by the mechanisms and features present in the human immune system. MADEX seeks to identify data exfiltration activities performed by evasive and stealthy malware that hides malicious traffic from an infected host in low-latency networks. Our approach uses cross-network traffic information collected by agents to effectively identify unknown illicit connections by an operating system subverted. MADEX does not require prior knowledge of the characteristics or behavior of the malicious code or a dedicated access to a knowledge repository. We tested the performance of MADEX in terms of its capacity to handle real-time data and the sensitivity of our algorithm’s classification when exposed to malicious traffic. Experimental evaluation results show that MADEX achieved 99.97% sensitivity, 98.78% accuracy, and an error rate of 1.21% when compared to its best rivals. We created a second version of MADEX, called MADEX level 2, that further improves its overall performance with a slight increase in computational complexity. We argue for the suitability of MADEX level 1 in non-critical environments, while MADEX level 2 can be used to avoid data exfiltration in critical mission systems. To the best of our knowledge, this is the first article in the literature that addresses the detection of rootkits real-time in an agnostic way using an artificial immune system approach while it satisfies strict latency requirements.

show abstract

MAIS-IDS: A distributed intrusion detection system using multi-agent AIS approach

Cited by 63 publications

References 17 publications

Cost-effective clonal selection and AIS-based load balancing in cloud computing environment

Cost-effective clonal selection and AIS-based load balancing in cloud computing environment

Plant and Salamander Inspired Network Attack Detection and Data Recovery Model

A Flow-based Multi-agent Data Exfiltration Detection Architecture for Ultra-low Latency Networks

Contact Info

Product

Resources

About