FRID: Flood Attack Mitigation Using Resources Efficient Intrusion Detection Techniques in Delay Tolerant Networks

Khalid, Waqar, Ahmed, Naveed, Khalid, Muhammad, Ud Din, Aziz, Khan, Aurangzeb and Arshad, Muhammad (2019) FRID: Flood Attack Mitigation Using Resources Efficient Intrusion Detection Techniques in Delay Tolerant Networks. IEEE Access, 7. pp. 83740-83760. ISSN 2169-3536

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Official URL: https://doi.org/10.1109/ACCESS.2019.2924587

Abstract

Delay tolerant networks (DTNs) are a special type of intermittently connected networks (ICN) featured by variable delay, frequent disruption, asymmetric data rates, and high-error rates. The DTNs have been primarily developed for interplanetary networks (IPNs), however, it shows applicability to challenged networks. Thus, solutions devised for security and routing for traditional networks do not apply to DTNs due to its unique nature. Moreover, this paper shows less attention particularly in security and its related strings. In DTNs, malicious nodes launch various attacks that include packet drop, a fake packet, and flood attack. These attacks inevitably overuse scarce resources (bandwidth, buffer, and energy) in DTNs, which leads to low packet delivery ratio and high packet loss ratio. Flood attack is listed in top among the challenging attacks in DTNs. The existing techniques to confront flood attack suffered from high-detection time and low-detection accuracy. This paper proposed novel resources efficient (distributed and intrusion detection system-based) algorithms to mitigate flood attack. The simulation results show considerable improvement in detection time, detection accuracy, and resource consumption, and also show enhanced packet delivery ratio and reduced packet loss ratio.

Item Type: Article
Uncontrolled Keywords: Delay tolerant networks (DTNs), flood attack, misbehaving nodes, packet delivery ratio, packet loss ratio and resources consumption
Subjects: F200 Materials Science
G400 Computer Science
G600 Software Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Elena Carlaw
Date Deposited: 25 Jul 2019 08:43
Last Modified: 11 Oct 2019 10:05
URI: http://nrl.northumbria.ac.uk/id/eprint/40152

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