Cognitive Spectrum and Its Security Issues

Arkoulis, Stamatios; Kazatzopoulos, L.; Delakouridis, C.; Marias, Giannis F.

doi:10.1109/ngmast.2008.102

Cited by 29 publications

(20 citation statements)

References 16 publications

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“…A first attempt to identify and categorize non-conformant nodes in the Cognitive Radio Networking context is made by Arkoulis et al [28]. Their classification is slightly modified and briefly summarized below:…”

Section: Attacker Profilesmentioning

confidence: 99%

“…Obviously, each single node may send one or no such requests, depending on its current needs. One problem that arises here is that an attacker could inject fake requests (and information) [28] into the DSA network aiming at either confusing the sharing mechanism, or misleading it to assign the available opportunities to the wrong nodes. In the latter case, the fake requests might seem to be sent from an existing and valid entity of the network (a victim in this case), while in the former case this is not a requirement.…”

Section: Fake Spectrum Requests Injectionmentioning

confidence: 99%

“…One more problem, which arises when exchanging requests and other operational details between nodes and the spectrum sharing mechanism, is that an attacker may try to falsify the requests sent by its competitors [28]. Such an attack belongs to the class of man-in-the-middle ones, where an attacking node captures the packets in question (carrying negotiation-related information) and injects them back after manipulating their contents in a way advantageous to itself.…”

Section: Spectrum Requests Falsificationmentioning

confidence: 99%

“…Unfortunately, this might not always be the case. An attacker may either deny submitting the required information to the sharing mechanism, or may send information not representing the reality [28,29]. Such behavior is based on the fact that both collecting the required details, as well as sending them back to the respective collector, is not only time, but also resource, consuming (e.g., energy to be consumed may be critical for small mobile devices).…”

Section: Client Feedback Falsificationmentioning

confidence: 99%

“…Unfortunately, this may not always be the case. A node may on purpose report lower satisfaction levels, or falsely claim that it suffers from significant QoS degradation [28]. Consequently, the misled sharing mechanism might choose to allocate more resources to the complaining nodes aiming at compensating them for their (fake) losses.…”

Section: Fake Complaints Regarding the Received Qosmentioning

confidence: 99%

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Misbehavior Scenarios in Cognitive Radio Networks

et al. 2010

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Recent advances in the fields of Cognitive Radio and the proliferation of open spectrum access promise that spectrum-agile wireless communication will be widespread in the near future, and will bring significant flexibility and potential utility improvements for end users. With spectrum efficiency being a key objective, most relevant research focuses on smart coexistence mechanisms. However, wireless nodes may behave selfishly and should be considered as rational autonomous entities. Selfishness, pure malice or even faulty equipment can lead to behavior that does not conform to sharing protocols and etiquette. Thus, there is a need to secure spectrum sharing mechanisms against attacks in the various phases of the sharing process. Identifying these attacks and possible countermeasures is the focus of this work.

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Section: Attacker Profilesmentioning

confidence: 99%

Section: Fake Spectrum Requests Injectionmentioning

confidence: 99%

Section: Spectrum Requests Falsificationmentioning

confidence: 99%

Section: Client Feedback Falsificationmentioning

confidence: 99%

Section: Fake Complaints Regarding the Received Qosmentioning

confidence: 99%

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Misbehavior Scenarios in Cognitive Radio Networks

et al. 2010

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Security and privacy issues for the network of the future

Marias

Barros

Fiedler

et al. 2011

Security Comm Networks

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The vision towards the Network of the Future cannot be separated from the fact that today's networks, and networking services are subject to sophisticated and very effective attacks. When these attacks first appeared, spoofing and distributed denial-of-service attacks were treated as apocalypse for networking. Now, they are considered moderate damage, whereas more sophisticated and inconspicuous attacks, such as botnets activities, might have greater and far reaching impact. As the Internet is expanding to mobile phones and smart dust and as its social coverage is liberalized towards the realization of ubiquitous computing (with communication), the concerns on security and privacy have become deeper and the problems more challenging than ever. Re-designing the Internet as the Network of the Future is self-motivating for researchers, and security and privacy cannot be provided again as separate, external, add-on, solutions. In this paper, we discuss the security and privacy challenges of the Network of the Future and try to delimit the solutions space on the basis of emerging techniques. We also review methods that help the quantification of security and privacy in an effort to provide a more systematic and quantitative treatment of the area in the future

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Technical Approaches for Improved Spectrum Sharing

Velez

Matinmikko

2014

Signals and Communication Technology

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Cognitive Spectrum and Its Security Issues

Cited by 29 publications

References 16 publications

Misbehavior Scenarios in Cognitive Radio Networks

Misbehavior Scenarios in Cognitive Radio Networks

Security and privacy issues for the network of the future

Technical Approaches for Improved Spectrum Sharing

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