Biblio

Anonymity platforms route the traffic over a network of special routers that are known as mixes and implement various traffic disruption techniques to hide the communicating users' identities. Batch mixes in particular anonymize communicating peers by allowing message exchange to take place only after a sufficient number of messages (a batch) accumulate, thus introducing delay. We introduce a queueing model for batch mix and study its delay properties. Our analysis shows that delay of a batch mix grows quickly as the batch size gets close to the number of senders connected to the mix. We then propose a randomized batch mixing strategy and show that it achieves much better delay scaling in terms of the batch size. However, randomization is shown to reduce the anonymity preserving capabilities of the mix. We also observe that queueing models are particularly useful to study anonymity metrics that are more practically relevant such as the time-to-deanonymize metric.

This paper presents an efficiency and adaptive cryptographic protocol to ensure users' privacy and data integrity in RFID system. Radio Frequency Identification technology offers more intelligent systems and applications, but privacy and security issues have to be addressed before and after its adoption. The design of the proposed model is based on clustering configuration of the involved tags where they interchange the data with the reader whenever it sends a request. This scheme provides a strong mutual authentication framework that suits for real heterogeneous RFID applications such as in supply-chain management systems, healthcare monitoring and industrial environment. In addition, we contribute with a mathematical analysis to the delay analysis and optimization in a clustering topology tag-based. Finally, a formal security and proof analysis is demonstrated to prove the effectiveness of the proposed protocol and that achieves security and privacy.