A Hierarchical Detection and Response System to Enhance Security Against Lethal Cyber-Attacks in UAV Networks

Unmanned aerial vehicles (UAVs) networks have not yet received considerable research attention. Specifically, security issues are a major concern because such networks, which carry vital information, are prone to various attacks. In this paper, we design and implement a novel intrusion detection and...

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Veröffentlicht in:IEEE transactions on systems, man, and cybernetics. Systems Jg. 48; H. 9; S. 1594 - 1606
Hauptverfasser: Sedjelmaci, Hichem, Senouci, Sidi Mohammed, Ansari, Nirwan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.09.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Schlagworte:
Ad hoc networks
Anomaly detection and rules-based intrusion detection techniques
Computer Science
Cryptography and Security
cyber-attacks
Cybersecurity
Denial of service attacks
Ground stations
Information dissemination
Intrusion detection
intrusion detection system (IDS)
Intrusion detection systems
Jamming
Mobile communication
Mobile computing
Monitoring
Networking and Internet Architecture
Networks
Spoofing
Unmanned aerial vehicles
unmanned aerial vehicles (UAVs)
intrusion detection system
cyber-attacks
Anomaly detection and rules-based intrusion detection techniques
Intrusion detection
Mobile communication
IDS
Unmanned aerial vehicles
Ad hoc networks
UAV
Monitoring
ISSN:2168-2216, 2168-2232
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Beschreibung
Zusammenfassung:Unmanned aerial vehicles (UAVs) networks have not yet received considerable research attention. Specifically, security issues are a major concern because such networks, which carry vital information, are prone to various attacks. In this paper, we design and implement a novel intrusion detection and response scheme, which operates at the UAV and ground station levels, to detect malicious anomalies that threaten the network. In this scheme, a set of detection and response techniques are proposed to monitor the UAV behaviors and categorize them into the appropriate list (normal, abnormal, suspect, and malicious) according to the detected cyber-attack. We focus on the most lethal cyber-attacks that can target an UAV network, namely, false information dissemination, GPS spoofing, jamming, and black hole and gray hole attacks. Extensive simulations confirm that the proposed scheme performs well in terms of attack detection even with a large number of UAVs and attackers since it exhibits a high detection rate, a low number of false positives, and prompt detection with a low communication overhead.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2017.2681698