Combating the Looping Behavior: A Result of Routing Layer Attack

Bhatti, David Samuel; Sardar, Kinza; Jabeen, Meh; Chaudhry, Umair B.

doi:10.14569/ijacsa.2018.090463

Cited by 2 publications

(1 citation statement)

References 45 publications

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“…Sometimes, they are also classified on the basis of attack vectors such as packet encapsulation, relay, high transmission power, high-quality link (out-of-band channel) or protocol deviation. We can study them further from 43,58,59 . The concept of a wormhole is discussed below with the help of two use cases they may help in deciding the thresholds of alerts.…”

Section: Wormhole Attack Scenariosmentioning

confidence: 99%

DAIWN: Detection and Isolation of Wormhole Nodes in Wireless Ad Hoc Networks

Bhatti

Saleem

Imran³

et al. 2023

Preprint

Self Cite

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The wormhole attack is one of the most treacherous attacks projected at the routing layer that can bypass cryptographicmeasures and derail the entire communication network. It is too difficult to prevent a priori; all the possible countermeasures are either too expensive or ineffective. Indeed, literature solutions either require expensive hardware (typically UWB or secure GPStransceivers) or pose specific constraints to the adversarial behavior (doing or not doing a suspicious action). The proposed solution belongs to the second category because the adversary is assumed to have done one or more known suspicious actions. In this solution, we adopt a heuristic approach to detect wormholes in ad hoc networks based on the detection of their illicit behaviors. Wormhole and post wormhole attacks are often confused in literature; that’s why we clearly state that our methodology does not provide a defence against wormholes, but rather against the actions that an adversary does after thewormhole, such as packet dropping, tampering with TTL, replaying and looping, etc. In terms of contributions, the proposed solution addresses the knock-out capability of attackers that is less targeted by the researcher’s community. In addition, it neither requires any additional hardware nor a change in it; instead, it is compatible with the existing network stack. The idea is simulated in ns2.30, and the average detection rate of the proposed solution is found to be 98-99%. The theoretical time to detect a wormhole node lies between 0.07-0.71 seconds. But, from the simulation, the average detection and isolation time is 0.67 seconds. In term of packet loss, the proposed solution has a relatively overhead of ≈ 22%. It works well in static and mobile scenarios, but the frame losses are higher in mobile scenarios as compared to static ones. The computational complexity of the solution is O(n). Simulation results advocate that the solution is effective in terms of memory, processing, bandwidth, and energy cost. The solution is validated using statistical parameters such as Accuracy, Precision, F1-Score andMatthews correlation coefficient (Mcc).

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Section: Wormhole Attack Scenariosmentioning

confidence: 99%

DAIWN: Detection and Isolation of Wormhole Nodes in Wireless Ad Hoc Networks

Bhatti

Saleem

Imran³

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Detection and isolation of wormhole nodes in wireless ad hoc networks based on post-wormhole actions

Bhatti,

Saleem,

Imran

et al. 2024

Sci Rep

Self Cite

View full text Add to dashboard Cite

The wormhole attack is one of the most treacherous attacks projected at the routing layer that can bypass cryptographic measures and derail the entire communication network. It is too difficult to prevent a priori; all the possible countermeasures are either too expensive or ineffective. Indeed, literature solutions either require expensive hardware (typically UWB or secure GPS transceivers) or pose specific constraints to the adversarial behavior (doing or not doing a suspicious action). The proposed solution belongs to the second category because the adversary is assumed to have done one or more known suspicious actions. In this solution, we adopt a heuristic approach to detect wormholes in ad hoc networks based on the detection of their illicit behaviors. Wormhole and post wormhole attacks are often confused in literature; that’s why we clearly state that our methodology does not provide a defence against wormholes, but rather against the actions that an adversary does after the wormhole, such as packet dropping, tampering with TTL, replaying and looping, etc. In terms of contributions, the proposed solution addresses the knock-out capability of attackers that is less targeted by the researcher’s community. In addition, it neither requires any additional hardware nor a change in it; instead, it is compatible with the existing network stack. The idea is simulated in ns2.30, and the average detection rate of the proposed solution is found to be 98-99%. The theoretical time to detect a wormhole node lies between 0.07-0.71 seconds. But, from the simulation, the average detection and isolation time is 0.67 seconds. In term of packet loss, the proposed solution has a relatively overhead of $$\approx$$ ≈ 22%. It works well in static and mobile scenarios, but the frame losses are higher in mobile scenarios as compared to static ones. The computational complexity of the solution is O(n). Simulation results advocate that the solution is effective in terms of memory, processing, bandwidth, and energy cost. The solution is validated using statistical parameters such as Accuracy, Precision, F1-Score and Matthews correlation coefficient ($$M_{cc}$$ M cc ).

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Combating the Looping Behavior: A Result of Routing Layer Attack

Cited by 2 publications

References 45 publications

DAIWN: Detection and Isolation of Wormhole Nodes in Wireless Ad Hoc Networks

DAIWN: Detection and Isolation of Wormhole Nodes in Wireless Ad Hoc Networks

Detection and isolation of wormhole nodes in wireless ad hoc networks based on post-wormhole actions

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