Cited by 28Mobile Ad Hoc NetworksSecurity in Wireless Sensor NetworksNetwork Security and Intrusion Detection

Masquerading attacks detection in mobile ad hoc networks

Open access
Abbas, Sohail, Faisal, Mohammad, Ur Rahman, Haseeb, Khan, Muhammad Zahid, Merabti, Madjid, Khan, Atta ur Rehman·2018·IEEE Access

Abstract

Due to the lack of centralized identity management and the broadcast nature, wireless ad hoc networks are always a palatable target for masquerading attacks. The attackers can spoof identities of privileged legitimate users for various malicious reasons, such as to launch DoS or DDoS attacks, to access unauthorized information, and to evade the detection and accountability. In the current and limited literature, masquerading attacks are mostly counteracted by signal-strength-based detection systems. However, these schemes are mostly proposed to work for infrastructure-based IEEE 802.11 wireless networks using fixed access points, air monitors, or fixed anchor nodes, which are not suitable for the ad hoc architecture. In this paper, we propose a detection system for masquerading attacks without using fixed anchor nodes or air monitors. We develop an anomaly detection model based on the statistical significant testing for our masquerading detection system that takes into consideration the signal strength fluctuation. We conduct a test bed of Samsung Galaxy-based smartphones in order to analyze the real-world signal strength variation. We also plug the real-world signal strength variation in our model for the evaluation of the detection accuracy. We propose the received signal-strength-based masquerading attack detection scheme, which is carried out first by each node in its one-hop vicinity and then extended to five-hop proximity for broader detection scope and improved accuracy. The proposed scheme is evaluated using an NS-2 network simulator for detection accuracy in different environments. The results obtained indicate that our proposed scheme produces more than 90% true positives.

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Crossref · 10.1109/access.2018.2872115

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  • A hardware-independent technique based on an adaptive anomaly detection model that takes signal strength variations into account can detect masquerade attacks.

    “The authors present a hardware-independent technique for detecting masquerade attacks that is based on an adaptive anomaly detection model that takes signal strength variations into account.”
  • An anomaly detection model using signal strength fluctuations can detect masquerading attacks, with malicious nodes detected by factoring maximum speed and time of reception.

    “In [120], to address this problem, network specialists recommend an anomaly detection model that detects attacks using signal strength fluctuations. The malicious nodes are detected by factoring in the maximum speed of the nodes and the time of reception.”

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References 44 · Cited by 28

Authors
Abbas, S., Faisal, M., Ur Rahman, H., Khan, M. Z., Merabti, M., & Khan, A. U. R.
Affiliations
  • University of Sharjah (AE)
  • University of Malakand (PK)
  • Sohar University (OM)
Venue
IEEE Access
Published
2018
Volume
6
Pages
55013-55025
ISSN
2169-3536 (ISSN-L)
OpenAlex
W2894477425
Cited by
28
References
44
Citations by year
2025: 1 · 2024: 1 · 2022: 8 · 2021: 5 · 2020: 11 · 2019: 2
FWCI
2.79
Type
journal article
Language
en
Open access
Locations
  • IEEE Access (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › Mobile Ad Hoc Networks
  • Physical Sciences › Computer Science › Computer Networks and Communications › Security in Wireless Sensor Networks
  • Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
Keywords
masquerading attacks, mobile ad hoc networks, identity spoofing, received signal strength, anomaly detection, statistical significance testing, signal strength fluctuations, denial-of-service attacks, DDoS attacks, wireless network security

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