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Register a new userEcology-Based DoS Attack in Cognitive Radio Networks
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Added by
Shin-Ming Cheng
Publication date
2016
fields
Informatics Engineering
and research's language is
English
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Cognitive radio technology, which is designed to enhance spectrum utilization, depends on the success of opportunistic access, where secondary users (SUs) exploit spectrum void unoccupied by primary users (PUs) for transmissions. We note that the system behaviors are very similar to the interactions among different species coexisting in an ecosystem. However, SUs of a selfish nature or of misleading information may make concurrent transmissions with PUs for additional incentives, and thus disrupt the entire ecosystem. By exploiting this vulnerability, this paper proposes a novel distributed denial-of-service (DoS) attack where invasive species, i.e., malicious users (MUs), induce originally normal-behaved SUs to execute concurrent transmissions with PUs and thus collapse the cognitive radio network. We adopt stochastic geometry to model the spatial distributions of PUs, SUs, and MUs for the analysis of the mutual interference among them. The access strategy of each SU in the spectrum sharing ecosystem, which evolves with the experienced payoffs and interference, is modeled by an evolutionary game. Based on the evolutionary stable strategy concept, we could efficiently identify the fragile operating region at which normal-behaved SUs are eventually evolved to conduct concurrent transmissions and thus to cause the ruin of the network.
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In this paper, a novel spectrum association approach for cognitive radio networks (CRNs) is proposed. Based on a measure of both inference and confidence as well as on a measure of quality-of-service, the association between secondary users (SUs) in the network and frequency bands licensed to primary users (PUs) is investigated. The problem is formulated as a matching game between SUs and PUs. In this game, SUs employ a soft-decision Bayesian framework to detect PUs signals and, eventually, rank them based on the logarithm of the a posteriori ratio. A performance measure that captures both the ranking metric and rate is further computed by the SUs. Using this performance measure, a PU evaluates its own utility function that it uses to build its own association preferences. A distributed algorithm that allows both SUs and PUs to interact and self-organize into a stable match is proposed. Simulation results show that the proposed algorithm can improve the sum of SUs rates by up to 20 % and 60 % relative to the deferred acceptance algorithm and random channel allocation approach, respectively. The results also show an improved convergence time.
With the evolution of WCN (Wireless communication networks), the absolute fulfillment of security occupies the fundamental concern. In view of security, we have identified another research direction based on the attenuation impact of rain in WCN. An approach is initiated by an eavesdropper in which a secure communication environment is degraded by generating Artificial Rain (AR), which creates an abatement in the secrecy rate, and the cybersecurity gets compromised. By doing so, an attacking scenario is perceived, in which an intruder models a Half-Duplex (HD) attack. Half-Duplex specifies the attack on the downlink instead of targeting both uplink and downlink. This allows the attacker to alleviate the miss-rate of the attacking attempts. The layout for the HD attack is explained using RRC (Radio Resource Control)-setup. Further, we have determined and examined the performance parameters such as secrecy rate, energy efficiency, miss-rate, sensitivity in the presence of AR. Further comparison of rural and urban scenarios in the presence and absence of AR is carried out concerning the variation in secrecy rate with respect to the millimeter-wave frequencies and distance. Lastly, the methodology of the HD attack is simulated, revealing that the HD attack maintains a low miss rate with improved performance as compared to the performance and miss-rate attained by the full-duplex attack
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Recent work has demonstrated that by monitoring the Real Time Bidding (RTB) protocol, one can estimate the monetary worth of different users for the programmatic advertising ecosystem, even when the so-called winning bids are encrypted. In this paper we describe how to implement the above techniques in a practical and privacy preserving manner. Specifically, we study the privacy consequences of reporting back to a centralized server, features that are necessary for estimating the value of encrypted winning bids. We show that by appropriately modulating the granularity of the necessary information and by scrambling the communication channel to the server, one can increase the privacy performance of the system in terms of K-anonymity. Weve implemented the above ideas on a browser extension and disseminated it to some 200 users. Analyzing the results from 6 months of deployment, we show that the average value of users for the programmatic advertising ecosystem has grown more than 75% in the last 3 years.
A new form of multiuser diversity, named emph{multiuser interference diversity}, is investigated for opportunistic communications in cognitive radio (CR) networks by exploiting the mutual interference between the CR and the existing primary radio (PR) links. The multiuser diversity gain and ergodic throughput are analyzed for different types of CR networks and compared against those in the conventional networks without the PR link.
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