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https://ptsldigital.ukm.my/jspui/handle/123456789/513483Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Rosilah Hassan, Associate Professor Dr. | |
| dc.contributor.author | Maha Abdelhaq (P50000) | |
| dc.date.accessioned | 2023-10-16T04:37:10Z | - |
| dc.date.available | 2023-10-16T04:37:10Z | - |
| dc.date.issued | 2014-03-24 | |
| dc.identifier.other | ukmvital:74807 | |
| dc.identifier.uri | https://ptsldigital.ukm.my/jspui/handle/123456789/513483 | - |
| dc.description | Mobile ad hoc network (MANET) is a collection of mobile, decentralized and self-organizing nodes that are used in special cases such as military purposes. MANET properties render its environment vulnerable to different types of attacks namely black hole, wormhole and flooding-based attacks. Flooding-based attacks are one of the most dangerous attacks which could paralyze the functionality of the whole network. In essence, flooding attacks employ a technique which depends on overflowing the network with bogus packets and can be performed through various types of attacks which are resource consumption attack (RCA), hello flood, routing table overflow, rushing attacks and exploiting node penalizing schemes. In order to secure MANET from attacks, many researchers have introduced intrusion detection algorithms which are based on artificial immune systems (AISs). This is because AISs utilize the human immune system (HIS) analogy to introduce efficient, self-defensive and self-organizing algorithms, which could meet the challenges of the MANET environment. However, the current AIS algorithms lack the generality by which it could secure a standard routing protocol over MANET from a wide range of attack techniques with high accuracy and low false positive rates. In addition, research shows less attention on introducing an AIS algorithm that could reduce the effect of the attack on the main network performance metrics. The main objective of this research is to develop an efficient, self-defensive and self-organizing computational intelligent algorithm which combines the relevant features of danger theory-based AISs and fuzzy logic theory. This is done by inspiring the detection functionality of dendritic cells (DCs) in the HIS and the accurate decision making functionality of fuzzy logic theory to introduce an AIS intrusion detection algorithm called Dendritic Cell Fuzzy Algorithm (DCFA). The proposed algorithm has been tested and verified by detecting the denial of service (DoS) attack namely, RCA using QualNet version 5.0.2 simulator over MANET. The research has found that AIS is efficient for developing intrusion detection algorithms with high accuracy and low false positive rates. Moreover, the results show the capability of DCFA to perform the detection operation with high efficiency and effectiveness.,PhD | |
| dc.language.iso | eng | |
| dc.publisher | UKM, Bangi | |
| dc.relation | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat | |
| dc.rights | UKM | |
| dc.subject | Artificial immune | |
| dc.subject | Immune fuzzy intrusion | |
| dc.subject | Fuzzy intrusion detection | |
| dc.subject | Immune fuzzy intrusion detection algorithm | |
| dc.subject | Universiti Kebangsaan Malaysia -- Dissertations | |
| dc.title | Artificial immune fuzzy intrusion detection algorithm over manet | |
| dc.type | Theses | |
| dc.format.pages | 155 | |
| dc.identifier.barcode | 003152 (2014) | |
| Appears in Collections: | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ukmvital_74807+Source01+Source010.PDF Restricted Access | 3.31 MB | Adobe PDF |  View/Open |
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