On the Privacy and Performance of Mobile Anonymous Microblogging
Microblogging is a popular form of online social networking activity. It allows users to send messages in a one-to-many publish-subscribe manner. Most current service providers are centralized and deploy a client-server model with unencrypted message content. As a consequence, all user behavior can, by default, be monitored, and censoring based on message content can easily be enforced on the server side. A distributed, peer-to-peer microblogging system consisting of mobile smartphone-equipped users that exchange group encrypted messages in an anonymous and censorship-resistant manner can alleviate privacy and censorship issues. We experimentally evaluate message spread of such systems with simulations that run on a range of synthetic and real-world mobility inputs, thus extending the previous work. We show that such systems are feasible for a range of mobility and network settings, both under normal and under adversarial conditions, e.g., under the presence of nodes which jam the network or send spam.
Performance evaluation of delay-tolerant wireless friend-to-friend networks for undetectable communication
Anonymous communication systems have recently increased in popularity in wired networks, but there are no adequate equivalent systems for wireless networks under strong surveillance. In this work we evaluate the performance of delay-tolerant friend-to-friend networking, which can allow anonymous communication in a wireless medium under strong surveillance by relying on trust relationships between the network’s users. Since strong anonymity properties incur in performance penalties, a good understanding of performance under various conditions is crucial for the successful deployment of such a system. We simulate a delay-tolerant friend-to-friend network in several scenarios using real-world mobility data, analyze the trade-offs of network-related parameters and offer a preliminary throughput estimation.
It’s the Data that Matters! On the Detection of False Data in Wireless Sensor Networks
On Data-centric Intrusion Detection in Wireless Sensor Networks