Abstract: Embodiments of the present disclosure relate to identifying collusive attackers in mobile crowdsourcing. According to embodiments of the present disclosure, the crowdsourcing behaviors of each device is abstracted as a binary variable and the similarity between any two device is measured, which result in less complex and lightweight in mathematical computation.

Abstract: A method comprises: receiving, by a second node, a new transaction to be recorded to a block in a blockchain (510), determining, by the second node, based on an identity of the block that the second node is one of a subset of block managers in the blockchain to store the block (520), adding the block to the blockchain responsive to the determination (530) and transmitting a block list, wherein the block list comprises information about the block (540).

Abstract: The present invention involves a method for distributed dynamic spectrum allocation performed by a source device and the source device, a method for dynamic spectrum allocation performed by a power node and the power node, the method including sending to appropriate power nodes a query message indicating that the source device requests to find an idle licensed spectrum; receiving from the appropriate power nodes a query response message indicating licensed spectrums; and determining whether the licensed spectrums are idle and selecting an idle licensed spectrum from the licensed spectrums to be used. In this way, the provided method may implement distributed dynamic spectrum allocation without using a central authority.

Abstract: The present invention involves a method for distributed dynamic spectrum allocation performed by a source device and the source device, a method for dynamic spectrum allocation performed by a power node and the power node, the method including sending to appropriate power nodes a query message indicating that the source device requests to find an idle licensed spectrum; receiving from the appropriate power nodes a query response message indicating licensed spectrums; and determining whether the licensed spectrums are idle and selecting an idle licensed spectrum from the licensed spectrums to be used. In this way, the provided method may implement distributed dynamic spectrum allocation without using a central authority.

Abstract: Method and apparatus are disclosed for detecting mutual-aid collusive (MAC) attack in a voting action of an online voting system. According to some embodiments, the method comprises: calculating a consumer-voter (CV) matrix, and/or calculating a similarity (SIM) matrix; and determining MAC attackers in the voting action based at least in part on the calculated CV matrix and/or similarity matrix. The method may further comprise: extracting for each voter in the voting action, a CV vector from the CV matrix, and/or extracting for a consumer in the voting action, a CV vector from the CV matrix; judging whether there is only one CV vector having elements with a same CV value and/or whether the consumer's CV vector has elements with a same CV value; and in response to a positive judge result, determining that the voter corresponding to the only one CV vector or the consumer is a MAC attacker, and related voters corresponding to the elements with the same CV value are MAC attackers.

Abstract: A method includes performing blind spectrum sensing of a frequency band to determine whether a primary user is using the frequency band. The blind spectrum sensing is based at least in part on a comparison between a detection statistic based on a maximum correlation coefficient and a detection threshold based on theoretical computation of a distribution of the detection statistic. The maximum correlation coefficient is for correlations between a plurality of signals corresponding to a plurality of snapshots taken by a cognitive radio of the frequency band and corresponding to a plurality of antennas used by the cognitive radio for taking the snapshots. The method includes determining whether to communicate using the frequency band based on whether the blind spectrum sensing indicates the frequency band is or is not used by the primary user. Apparatus and program products are disclosed.