CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets

Inspecting packets to detect intrusions faces challenges when coping with a high volume of network traffic. Packet-based detection processes every payload on the wire, which degrades the performance of network intrusion detection system (NIDS). This issue requires an introduction of a flow-based NID...

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Bibliographic Details
Main Author: Alaidaros, Hashem Mohammed
Format: Thesis
Language:English
English
Published: 2017
Subjects:
Online Access:https://etd.uum.edu.my/6950/1/s93165_01.pdf
https://etd.uum.edu.my/6950/2/s93165_02.pdf
https://etd.uum.edu.my/6950/
Abstract Abstract here
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author Alaidaros, Hashem Mohammed
author_facet Alaidaros, Hashem Mohammed
author_sort Alaidaros, Hashem Mohammed
description Inspecting packets to detect intrusions faces challenges when coping with a high volume of network traffic. Packet-based detection processes every payload on the wire, which degrades the performance of network intrusion detection system (NIDS). This issue requires an introduction of a flow-based NIDS that reduces the amount of data to be processed by examining aggregated information of related packets. However, flow-based detection still suffers from the generation of the false positive alerts due to incomplete data input. This study proposed a Conditional Hybrid Intrusion Detection (CHID) by combining the flow-based with packet-based detection. In addition, it is also aimed to improve the resource consumption of the packet-based detection approach. CHID applied attribute wrapper features evaluation algorithms that marked malicious flows for further analysis by the packet-based detection. Input Framework approach was employed for triggering packet flows between the packetbased and flow-based detections. A controlled testbed experiment was conducted to evaluate the performance of detection mechanism’s CHID using datasets obtained from on different traffic rates. The result of the evaluation showed that CHID gains a significant performance improvement in terms of resource consumption and packet drop rate, compared to the default packet-based detection implementation. At a 200 Mbps, CHID in IRC-bot scenario, can reduce 50.6% of memory usage and decreases 18.1% of the CPU utilization without packets drop. CHID approach can mitigate the false positive rate of flow-based detection and reduce the resource consumption of packet-based detection while preserving detection accuracy. CHID approach can be considered as generic system to be applied for monitoring of intrusion detection systems.
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spelling oai:etd.uum.edu.my:69502021-05-02T01:08:52Z https://etd.uum.edu.my/6950/ CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets Alaidaros, Hashem Mohammed QA76 Computer software Inspecting packets to detect intrusions faces challenges when coping with a high volume of network traffic. Packet-based detection processes every payload on the wire, which degrades the performance of network intrusion detection system (NIDS). This issue requires an introduction of a flow-based NIDS that reduces the amount of data to be processed by examining aggregated information of related packets. However, flow-based detection still suffers from the generation of the false positive alerts due to incomplete data input. This study proposed a Conditional Hybrid Intrusion Detection (CHID) by combining the flow-based with packet-based detection. In addition, it is also aimed to improve the resource consumption of the packet-based detection approach. CHID applied attribute wrapper features evaluation algorithms that marked malicious flows for further analysis by the packet-based detection. Input Framework approach was employed for triggering packet flows between the packetbased and flow-based detections. A controlled testbed experiment was conducted to evaluate the performance of detection mechanism’s CHID using datasets obtained from on different traffic rates. The result of the evaluation showed that CHID gains a significant performance improvement in terms of resource consumption and packet drop rate, compared to the default packet-based detection implementation. At a 200 Mbps, CHID in IRC-bot scenario, can reduce 50.6% of memory usage and decreases 18.1% of the CPU utilization without packets drop. CHID approach can mitigate the false positive rate of flow-based detection and reduce the resource consumption of packet-based detection while preserving detection accuracy. CHID approach can be considered as generic system to be applied for monitoring of intrusion detection systems. 2017 Thesis NonPeerReviewed text en https://etd.uum.edu.my/6950/1/s93165_01.pdf text en https://etd.uum.edu.my/6950/2/s93165_02.pdf Alaidaros, Hashem Mohammed (2017) CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets. Doctoral thesis, Universiti Utara Malaysia.
spellingShingle QA76 Computer software
Alaidaros, Hashem Mohammed
CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets
thesis_level PhD
title CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets
title_full CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets
title_fullStr CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets
title_full_unstemmed CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets
title_short CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets
title_sort chid conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets
topic QA76 Computer software
url https://etd.uum.edu.my/6950/1/s93165_01.pdf
https://etd.uum.edu.my/6950/2/s93165_02.pdf
https://etd.uum.edu.my/6950/
work_keys_str_mv AT alaidaroshashemmohammed chidconditionalhybridintrusiondetectionsystemforreducingfalsepositivesandresourceconsumptiononmalicousdatasets