The authors first review the recently proposed Das's biometric-based remote user authentication scheme, and then show that Das's scheme is still insecure against some attacks and has some problems in password change phase. In order to overcome the design flaws in Das's scheme, an improvement of the scheme is further proposed. Cryptanalysis shows that our scheme is more efficient and secure against most of attacks; moreover, our scheme can provide strong mutual authentication by using verifying biometric, password as well as random nonces generated by the user and server.
Cooperative spectrum sensing can mitigate the effects of shadowing and fading. However, when the number of cognitive users is very large, the bandwidth for reporting their sensing results will be insufficient. In order to eliminate the fail sensing problem for a cognitive radio system with double threshold detector, a new cooperative spectrum sensing algorithm is presented based on reputation in this paper. In particular, the closed forms for the normalized average number of sensing bits, the probabilities of the detection and the false-alarm are derived. Simulation results show that the average number of sensing bits decreases greatly without failing sensing , and the sensing performance is improved comparing with the conventional double threshold detection and the conventional single threshold detection.
Social networks play an important role in our daily lives. However, social ties are rather elusive to quantify, especially for large groups of subjects over prolonged periods of time. In this work, we first propose a methodology for extracting social ties from long spatio-temporal data streams, where the subjects are 17,795 undergraduates from a university of China and the data streams are the 9,147,106 time-stamped RFID check-in records left behind by them during one academic year. By several metrics mentioned below, we then analyze the structure of the social network. Our results center around three main observations. First, we characterize the global structure of the network, and we confirm the small-world phenomenon on a global scale. Second, we find that the network shows clear community structure. And we observe that younger students at lower levels tend to form large communities, while students at higher levels mostly form smaller communities. Third, we characterize the assortativity patterns by studying the basic demographic and network properties of users. We observe clear degree assortativity on a global scale. Furthermore, we find a strong effect of grade and school on tie formation preference, but we do not find any strong region homophily. Our research may help us to elucidate the structural characteristics and the preference of the formation of social ties in college students’ social network.
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