People are constantly using mobile technologies to exchange perspectives across the world. The search services they use, however, belong to centralized systems that may be easily censored. The Peer-to-Peer retrieval system was created to impede censorship of online information, but the decentralized nature of P2P makes it difficult to infer information that cannot be measured directly, such as the proportion of subversion, selfish nodes, network size, or churn rate. Recent advances have pushed providers toward large-scale wireless networks where data retrieval is difficult. Thus, we propose a defense mechanism that can: (1) tackle censorship issues; (2) employ probability density function, exponential weighted moving average and modified Chi-squared tests to estimate the proportion of malicious and selfish nodes; (3) defend against malicious and selective-forwarding attacks by adjusting the number of forwarding levels and requests to ensure high-match probability; (4) maintain high-retrieval rates even in large and highly mobile networks; and (5) guarantee robustness compared to other search systems. A series of experiments demonstrated our algorithm's high-retrieval rate, reasonable costs, mobility resilience, and robustness, demonstrating that the algorithm can work well when the network size is large and/or has a large proportion of selfish nodes, malicious nodes and mobile nodes.
- Distributed systems
- Membership churn
- Message forwarding
- Peer-to-peer (P2P) search and retrieval
- Probabilistic analysis
- Probability density function (pdf)