The handover authentication protocol controls the access of multiple access points in a mobile wireless network (MWN). PairHand is a handover authentication protocol that uses identity-based public key cryptography based on bilinear pairing and provides batch verification to efficiently control multiple accesses. However, there may be errors in the messages transmitted via a wireless channel; such errors can affect the batch verification process. Previous studies involving PairHand have calculated the verification delay without considering errors. We have classified the message verification methods into two types: individual verification, in which the messages are individually verified and batch verification, in which the messages are verified all at once. We formulate the verification delay as a function of the bit error probability and visualize it. In our graph, the batch verification delay rapidly increases as the bit error probability increases and then forms an intersection with the individual verification delay. This intersection can be a guideline for whether to use batch verification or individual verification, depending on the bit error rate. We also classify the previously proposed handover authentication protocols into pairing-based protocols and pairing-free protocols and analyze the computation and communication costs of each. Based on the analysis results, we propose a mini-batch method to reduce the batch verification delay in an error-prone MWN. INDEX TERMS Batch handover authentication, batch verification delay, bilinear pairing, elliptic curve cryptography, handover authentication protocol, mini-batch verification, mobile wireless network.

SUMMARYThe reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.

SUMMARYRemote data checking (RDC) is a scheme that allows clients to efficiently check the integrity of data stored at an untrusted server using spot-checking. Efforts have been consistently devoted toward improving the efficiency of such RDC schemes because they involve some overhead. In this letter, it is assumed that a probabilistic attack model is adopted, in which an adversary corrupts exposed blocks in the network with a certain probability. An optimal spot-checking ratio that simultaneously guarantees the robustness of the scheme and minimizes the overhead is obtained.