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Peer-to-peer flow detection algorithm has been studied for several years. Port-based classification, regular expression, graphlet and various machine learning based algorithms have been proposed as solutions. Unfortunately, all previous algorithms have been failed in various aspects especially for the encrypted peer-to-peer traffic. In this paper, we present a new algorithm to delivers more effectiveness. We have also prototyped our algorithm and evaluate on a test-bed. The performance evaluation has demonstrated the better effectiveness of our algorithm in comparison to the previous ones.

SSL is a protocol for secured traffic connections. By using the SSL, HTTPS has been designed to prevent eavesdroppers and malicious users from web application services. However, man-in-the-middle attack techniques based on stripping and sniffing the HTTPS connections are still possible, causing security problems on web applications. Several scrip-kiddy tools to launch such attacks are easy to find and available on the Internet. In this paper, we therefore proposed a solution to protect against SSL striping attack. By enforcing a connection to HTTPS, our techniques determine the web URL and enforce the communication to HTTPS for protecting against the SSL striping attack. The experimental results on a test-bed have demonstrated an effectiveness and efficiency of our solution.

In this paper, we introduce Explicit Rate Adjustment (ERA), a new Multi-rate Multicast Congestion Control (MU-MCC) algorithm. Via ERA, the receiver explicitly adjusts its reception rate accordiug to the network conditions using the TCP throughput equation and Packet-pair Probe. The design goals are responsiveness, elliciency in network utilization, scalability and fairness (including inter-protocol fairness, intraprotocol fairness, intra-session fairness and TCP-friendliness) as well as simple implementation. We have built ERA into a network simulator (nsZ) and demonstrate via simulations that the goals are reached.