Intrusion detection system using hybrid Fuzzy Genetic algorithm

Potteti, Sumalatha; Parati, Namita

doi:10.1109/icoei.2017.8300775

Cited by 7 publications

(6 citation statements)

References 7 publications

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“…Each research chooses a detection approach depending on the data type, working environment and type of attack. Indeed, basing on various researches [9], [12], [13] we can classify the detection approaches into misuse detection system, anomaly detection, hybrid detection, and specification based detection, as shown in Figure 2. that detects an intruder on the system or network, based on the signature of the attack.…”

Section: Classification Of Detection Approachesmentioning

confidence: 99%

“…that detects an intruder on the system or network, based on the signature of the attack. With this method, important modules are used from an existing dataset in which produces a low false alarm that can cover a wide range of known attacks [13]. Nevertheless, the misuse detection cannot detect a novel attack that it must frequently update a signature to define a new attack [14].…”

Section: Classification Of Detection Approachesmentioning

confidence: 99%

“…Nevertheless, anomaly detection generates many false alerts because the data collected is not stable, which leads a weak detection. -Hybrid detection: the objective of this method is to optimize the detection of an intrusion on a system by combining the detection by anomaly and the misuse detection system [13]. Although this approach offers higher detection accuracy, it involves a high complexity and implementation cost [9].…”

Section: Classification Of Detection Approachesmentioning

confidence: 99%

“…-Specification based detection: uses specifically to describe the correct operation of a protocol or system in order to monitor them. This action depends on the constraints of each area where the IDS is implemented [13]. The disadvantage of this method is that it is not efficient in term of detecting novel attacks as the anomaly detection.…”

Section: Classification Of Detection Approachesmentioning

confidence: 99%

See 3 more Smart Citations

Intrusion detection based on fuzzy logic for wireless body area networks: review and proposition

Bengag¹,

Bengag²,

Moussaoui³

2022

IJEECS

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Wireless body area networks (WBANs) are very helpful for monitoring the patient’s case, due to the medical sensors. However, this technology faces several problems such as loss communication, security issues and energy consumption. Our work focused on the security and specifically the intrusion detection system (IDS), which is one of the most effective techniques used to identify the presence of intrusions in a network. To make the IDS more efficient, the fuzzy logic (FL) is one of the well-known techniques that is known for its powerful mechanism used to differentiate network traffic levels. In this paper, we start to present an overview of IDS and FL functionality. Moreover, we give a survey of recent works dealing IDS based on FL in wireless sensor and classify them on different measures. Hence, our comparative study is very helpful for the researchers, to understand the use of FL in IDS and have clear vision for developing their own security solution. In the second part, we develop a novel IDS based on Mamdani type fuzzy inference system for detecting jamming attacks in WBAN. Our IDS was built in Matlab, also we are used Castalia platform and OMNET++ simulator to simulate different scenarios of WBAN.

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Section: Classification Of Detection Approachesmentioning

confidence: 99%

Section: Classification Of Detection Approachesmentioning

confidence: 99%

Section: Classification Of Detection Approachesmentioning

confidence: 99%

Section: Classification Of Detection Approachesmentioning

confidence: 99%

See 2 more Smart Citations

Intrusion detection based on fuzzy logic for wireless body area networks: review and proposition

Bengag¹,

Bengag²,

Moussaoui³

2022

IJEECS

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“…In 2017, Potteti and Parati [33] described the hybrid IDS which is based on fuzzy genetic algorithm. They have suggested the main drawback of IDS is high rate of false positive.…”

Section: Related Workmentioning

confidence: 99%

A review on intrusion detection system based on data mining and evolutionary algorithms

Gupta¹,

Singh²

2018

IJATEE

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Intrusion detection is the procedure for determining intrusions in the network. This paper explores the methodology in the direction of intrusion detection system. It explores the possibility of enhancement and propounding the advantages.This study helps in exploring the method analytically, methodically and experimentally. This paper lists the gaps and the advantages, so that future framework can be design to enhance the efficiency. It also provides the detail discussion based on the attributes and parameters variations. Finally future suggestions have been listed.

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Medical big data intrusion detection system based on virtual data analysis from assurance perspective

Cai

Wang

2021

Int J Syst Assur Eng Manag

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Intrusion detection system using hybrid Fuzzy Genetic algorithm

Cited by 7 publications

References 7 publications

Intrusion detection based on fuzzy logic for wireless body area networks: review and proposition

Intrusion detection based on fuzzy logic for wireless body area networks: review and proposition

A review on intrusion detection system based on data mining and evolutionary algorithms

Medical big data intrusion detection system based on virtual data analysis from assurance perspective

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