Scalable and efficient distributed algorithms for defending against malicious Internet activity

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Sung, Minho
Xu, Jun
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The threat of malicious Internet activities such as Distributed Denial of Service (DDoS) attacks, spam emails or Internet worms/viruses has been increasing in the last several years. The impact and frequency of these malicious activities are expected to grow unless they are properly addressed. In this thesis, we propose to design and evaluate a set of practical and effective protection measures against potential malicious activities in current and future networks. Our research objective is twofold. First, we design the methods to defend against DDoS attacks. Our research focuses on two important issues related to DDoS attack defense mechanisms. One issue is the method to trace the sources of attacking packets, which is known as IP traceback. We propose a novel packet logging based (i.e., hash-based) traceback scheme using only a one-bit marking field in IP header. It reduces processing and storage cost by an order of magnitude than the existing hash-based schemes, and is therefore scalable to much higher link speed (e.g., OC-768). Next, we propose an improved traceback scheme with lower storage overhead by using more marking space in IP header. Another issue in DDoS defense is to investigate protocol-independent techniques for improving the throughput of legitimate traffic during DDoS attacks. We propose a novel technique that can effectively filter out the majority of DDoS traffic, thus improving the overall throughput of the legitimate traffic. Second, we investigate the problem of distributed network monitoring. We propose a set of novel distributed data streaming algorithms that allow scalable and efficient monitoring of aggregated traffic. Our algorithms target the specific network monitoring problem of finding common content in traffic traversing several nodes/links across the Internet. These algorithms find applications in network-wide intrusion detection, early warning for fast propagating worms, and detection of hot objects and spam traffic.
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