Catálogo de publicaciones - libros

Compact e-cash schemes allow a user to withdraw a wallet containing coins in a single operation, each of which the user can spend unlinkably. One big open problem for compact e-cash is to allow multiple denominations of coins to be spent efficiently without executing the spend protocol a number of times. In this paper, we give a () solution to this open problem by introducing two additional protocols, namely, compact spending and batch spending. Compact spending allows spending all the coins in one operation while batch spending allows spending any number of coins in the wallet in a single execution. We modify the security model of compact e-cash to accommodate these added protocols and present a generic construction. While the spending and compact spending protocol are of constant time and space complexities, complexities of batch spending is linear in the number of coins to be spent together. Thus, we regard our solution to the open problem as . We provide two instantiations under the -SDH assumption and the LRSW assumption respectively and present security arguments for both instantiations in the random oracle model.

This paper introduces a framework for fraud detection in mobile communication networks based on the current as well as past behavioral pattern of subscribers. The proposed fraud detection system (FDS) consists of four components, namely, rule-based deviation detector, Dempster-Shafer component, call history database and Bayesian learning. In the rule-based component, we determine the suspicion level of each incoming call based on the extent to which it deviates from expected call patterns. Dempster-Shafer’s theory is used to combine multiple evidences from the rule-based component and an overall suspicion score is computed. A call is classified as normal, abnormal, or suspicious depending on this suspicion score. Once a call from a mobile phone is found to be suspicious, belief is further strengthened or weakened based on the similarity with fraudulent or genuine call history using Bayesian learning. Our experimental results show that the method is very promising in detecting fraudulent behavior without raising too many false alarms.

This paper studies the interplay of network connectivity and perfectly secure message transmission under the corrupting influence of a Byzantine adversary that may move from player to player but can corrupt no more than players at any given time. It is known that, in the stationary adversary model where the adversary corrupts the same set of players throughout the protocol, perfectly secure communication among any pair of players is possible if and only if the underlying synchronous network is (2 + 1)-connected. Surprisingly, we show that (2 + 1)-connectivity is sufficient (and of course, necessary) even in the proactive (mobile) setting where the adversary is allowed to corrupt different sets of players in different rounds of the protocol. In other words, adversarial mobility has no effect on the possibility of secure communication. Towards this, we use the notion of a Communication Graph, which is useful in modelling scenarios with adversarial mobility. We also show that protocols for reliable and secure communication proposed in [15] can be modified to tolerate the adversary. Further these protocols are round-optimal if the underlying network is acollection of disjoint paths from the sender to receiver .