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Abstract. RSCTC'2010 Discovery Challenge was a special event of Rough Sets and Current Trends in Computing conference. The challenge was organized in the form of an interactive on-line competition, at TunedIT.org platform, in days between Dec 1, 2009 and Feb 28, 2010. The task was related to feature selection in analysis of DNA microarray data and classification of samples for the purpose of medical diagnosis or treatment. Prizes were awarded to the best solutions. This paper describes organization of the competition and the winning solutions.

Cognitive radio (CR) technology has emerged as a viable solution to solve the dilemma of spectrum scarcity and underutilization. It allows secondary users (SUs) to opportunistically access the primary user (PU) channel. Cooperative spectrum sensing (CSS) further improves the accuracy of detecting spectrum availability by exploiting spatial diversity gain. However, the open nature of CR networks (CRNs) makes CSS process be prone to Byzantine attack, resulting in the excessive interference to the PU and the waste of spectrum resources. To this end, we propose a joint spectrum sensing and resource allocation scheme to defend against Byzantine attack. Specifically, we develop a probabilistic Byzantine attack model to characterize attack behaviors from malicious users (MUs) and evaluate its negative impact on the CSS performance. Then, the delivery evaluation mechanism is designed to evaluate the sensing performance of SUs and distinguish between normal users and MUs. Based on this, we propose a selection-majority algorithm to improve CSS performance by exploiting sensing reports from MUs. To further solve the Byzantine attack, we propose a spectrum resource allocation algorithm, which allocates corresponding spectrum resources according to the historical behavior of SUs. By reducing the resources allocated to poorly performing SUs, this scheme incentivizes them to report correct sensing results and drive MUs to stop attacking or leave CRN. Extensive simulation results corroborate the correctness and effectiveness of our theoretical analysis and show that our proposed scheme can effectively resist Byzantine attack.

Cognitive radio (CR) is regarded as a powerful technology to solve the problem of spectrum shortage and underutilization. As a key function of CR technology, cooperative spectrum sensing (CSS) allows secondary users (SUs) to detect the primary user (PU)'s signal so that they identify and opportunistically access the available spectrum. However, the openness of CSS paradigm makes cognitive radio networks (CRNs) suffer from Byzantine attack, thereby undermining the premise of CR framework. To this aim, we formulate a probabilistic hard Byzantine attack model, in which malicious users (MUs) can conduct various attack strategies, and make an in‐depth investigation on the blind scenario. On the one hand, in order to ensure the robustness of CSS, a method to evaluate the reliability of the secondary user (SU)'s sensing result based on the channel status detection is proposed and an innovative weight coefficient is considered to selectively utilize the sensing information from MUs. On the other hand, we design a sequential fusion method based on reputation value (RV) and differential mechanism, with the aim of improving the efficiency of CSS. According to above methods and mechanism, the weighted differential sequential symbol (WDS2) algorithm is designed, which integrates the weight evaluation into sequential method to make the global decision for CSS. Finally, compared to the existing various data fusion algorithms, simulation results show that the proposed WDS2 not only defends against various Byzantine attacks to secure the robustness of CSS, but also requires less samples in support of an accurate global decision to improve the efficiency of CSS.

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