• ETRI Journal
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• v.42 no.6
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• pp.976-986
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• 2020

Internet of Things (IoT) is considered the future network to support wireless communications. To realize an IoT network, sufficient spectrum should be allocated for the rapidly increasing IoT devices. Through cognitive radio, unlicensed IoT devices exploit cooperative spectrum sensing (CSS) to opportunistically access a licensed spectrum without causing harmful interference to licensed primary users (PUs), thereby effectively improving the spectrum utilization. However, an open access cognitive IoT allows abnormal IoT devices to undermine the CSS process. Herein, we first establish a hard-combining attack model according to the malicious behavior of falsifying sensing data. Subsequently, we propose a weighted sequential hypothesis test (WSHT) to increase the PU detection accuracy and decrease the sampling number, which comprises the data transmission status-trust evaluation mechanism, sensing data availability, and sequential hypothesis test. Finally, simulation results show that when various attacks are encountered, the requirements of the WSHT are less than those of the conventional WSHT for a better detection performance.

• Journal of electromagnetic engineering and science
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• v.12 no.1
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• pp.1-7
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• 2012

In this paper, we investigated the throughput of a cognitive radio network where two primary frequency channels (PCs) are sensed and opportunistically accessed by N secondary users. The sharing sensing member (SSM) protocol is introduced to sense both PCs simultaneously. According to the SSM protocol, N SUs (Secondary User) are divided into two groups, which allows for the simultaneous sensing of two PCs. With a frame structure, after determining whether the PCs are idle or active during a sensing slot, the SUs may use the remaining time to transmit their own data. The throughput of the network is formulated as a convex optimization problem. We then evaluated an iterative algorithm to allocate the optimal sensing time, fusion rule and the number of members in each group. The computer simulation and numerical results show that the proposed optimal allocation improves the throughput of the SU under a misdetection constraint to protect the PCs. If not, its initial date of receipt shall be nullified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1319-1335
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• 2017

This paper proposes an opportunistic reporting-based sensing-reporting-throughput optimization scheme that maximizes the spectral efficiency of secondary users (SUs) in cooperative cognitive radio networks with a soft combining rule. The performance of cooperative spectrum sensing depends on the sensing time, the reporting time of transmitting sensing results, and the fusion scheme. While longer sensing time and reporting time improve the sensing performance, this shortens the allowable data transmission time, which in turn degrades the spectral efficiency of SUs. The proposed scheme adopts an opportunistic reporting scheme to restrain the reporting overhead and it jointly controls the sensing-reporting overhead in order to increase the spectral efficiency of SUs. We show that there is a trade-off between the spectral efficiency of SUs and the overheads of cooperative spectrum sensing. The numerical results demonstrate that the proposed scheme significantly outperforms the conventional sensing-throughput optimization schemes when there are many SUs. Moreover, the numerical results show that the sensing-reporting time should be jointly optimized in order to maximize the spectral efficiency of SUs.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.75-83
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• 2011

Cognitive radio (CR) technology is to maximize the spectrum utilization by allocating the unused spectrums to the unlicensed users. This technology enables the sharing of channels among secondary (unlicensed) and primary (licensed) users on a non-interference basis after sensing the vacant channel and as a result, it is possible to harness wireless frequency more efficiently. To enhance the accuracy of sensing, RDSS was suggested. It is a fusion mechanism based on the reputation of sensing nodes and WSPRT (weighted sequential probability ratio test). However, in RDSS, the execution number of WSPRT could increase according to the order of inputted sensing values, and the fast defense against the forged values is difficult. In this paper, we propose a transaction signing-based authentication scheme for secure distributed spectrum sensing to response the forged values. The validity of proposed scheme is provided by BAN logic.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.74-80
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• 2015

In cognitive radios, spectrum sensing plays an important role in accurately detecting the presence or absence of a licensed user. However, the intervention of malicious users (MUs) degrades the performance of spectrum sensing. Such users manipulate the local results and send falsified data to the data fusion center; this process is called spectrum sensing data falsification (SSDF). Thus, MUs degrade the spectrum sensing performance and increase uncertainty issues. In this paper, we propose a method based on the Hausdorff distance and a similarity measure matrix to measure the difference between the normal user evidence and the malicious user evidence. In addition, we use the Dempster-Shafer theory to combine the sets of evidence from each normal user evidence. We compare the proposed method with the k-means and Jaccard distance methods for malicious user detection. Simulation results show that the proposed method is effective against an SSDF attack.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.8-25
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• 2017

This survey paper explores the application of multimodal feedback in automated systems for motor learning. In this paper, we review the findings shown in recent studies in this field using rehabilitation and various motor training scenarios as context. We discuss popular feedback delivery and sensing mechanisms for motion capture and processing in terms of requirements, benefits, and limitations. The selection of modalities is presented via our having reviewed the best-practice approaches for each modality relative to motor task complexity with example implementations in recent work. We summarize the advantages and disadvantages of several approaches for integrating modalities in terms of fusion and frequency of feedback during motor tasks. Finally, we review the limitations of perceptual bandwidth and provide an evaluation of the information transfer for each modality.

• Journal of Medicine and Life Science
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• v.15 no.2
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• pp.51-55
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• 2018

Acceptance and Commitment Therapy (ACT) is a functional contextual intervention approach based on the behavioral theory on human language, which views human suffering as originating in psychological inflexibility fostered by cognitive fusion and experiential avoidance. Thus, the goal of ACT is to enhance psychological flexibility using six core processes including acceptance, cognitive defusion, self-as-context, contact with present moment, values clarification, and committed action. Recent clinical trials have suggested the efficacy for ACT in the treatment of various mental illness and psychological distress. The aim of this review is to offer more knowledge and better understanding of ACT by presenting its underlying principle and an overview of the research field.

• Korean Journal of Cognitive Science
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• v.4 no.1
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• pp.261-294
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• 1993

Most of expert systems,as a rule-based system,should be convenient to modify a rule and to insert a new rule, which is called modularity of rules. When we think correlated evidences in expert systems. conventional systems are too local to recognize the common origin of the information, and they would update the belief of the hypothesis as if it were supposed by independence soureces. In this paper to overcome such drawbacks we propose Fuzzy Belief Network which is based on the Beysian Network which provide the modulartiy between rules. To build Fuzzy Belief Network, we define nodes and links and propose algorithms for data fusion in individual node and for propagation belief value obtained as a result of data fusion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1042-1062
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• 2010

Cooperative spectrum sensing (CSS) is an effective technology for alleviating the unreliability of local spectrum sensing due to fading/shadowing effects. Unlike most existing solutions, this paper considers the use of CSS technology in decentralized networks where a fusion center is not available. In such a decentralized network, some attackers may sneak into the ranks of cooperative users. On the basis of recent advances in bio-inspired consensus algorithms, an attack-proof, decentralized CSS scheme is proposed in which all secondary users can maintain cooperative sensing by exchanging information locally instead of requiring centralized control or data fusion. Users no longer need any prior knowledge of the network. To counter three potential categories of spectrum sensing data falsification (SSDF) attacks, some anti-attack strategies are applied to the iterative process of information exchange. This enables most authentic users to exclude potentially malicious users from their neighborhood. As represented by simulation results, the proposed scheme can generally ensure that most authentic users reach a consensus within the given number of iterations, and it also demonstrates much better robustness against different SSDF attacks than several existing schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.10
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• pp.832-842
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• 2013

Cognitive Radio has attracted intensive interests of the researchers, recently. The data rate always increases in the emerging technologies. The increased data rate poses mainly two challenges for spectrum sensing. One is that the state of primary user (PU) is fast and alternatively varying between "on/off" in a spectrum sensing window. The other is that the asynchronicity among the reports in a cooperative spectrum sensing setting becomes more apparent. Both of them would deteriorate the spectrum sensing performance. Thus, we propose an asynchronous cooperative spectrum sensing method to cope with these two challenges. A likelihood ratio test based spectrum sensing is developed for a single cooperator. The likelihood ratio is obtained in the setting of fast varying PU state. The likelihood ratio test is uniformly powerful according to the Neyman-pearson lemma. Furthermore, the asynchronicity among the cooperators are studied. Two sets of fusion weights are discussed for the asynchronous time among cooperators. One is designed based on the condition probability of the PU state variation and the other one is designed based on the queueing theory. The simulation results are provided with different fusion methods. The performance improvements are demonstrated.