UC Riverside

In recent years we have witnessed an almost exponential growth in traffic that is transferred over the Internet. This traffic growth is a result of various innovations in network technology. However, this growth has also introduced various problems with regards to performance and security in modern networks. In this thesis we develop various frameworks that address some of those problems. The thesis is divided in two parts, the first deals with security issues and the second deals with performance issues.

In the first part, we analyze how modern day IDS systems are unable to efficiently cope with both the volume of traffic and the amount of information that can be collected from modern day systems. To deal with information overload, we develop and automated framework for feature selection that specifies the optimal set of features that a given system should monitor. This allows the IDS to focus only on what is important. To address the scalability problem in IDS systems, we develop Jaal, a framework that enables intrusion detection at ISP scales. The key idea in Jaal is to monitor traffic and construct in-network packet summaries. The summaries are then processed centrally to detect attacks with high accuracy.

In the second part, we first highlight how battery technology is often the perfor-

mance bottleneck in smartphones. Consequently we develop a mathematical framework that accurately predicts how much energy a given high definition video will consume on a mobile device. The predictive framework empowers user by pre-calculating energy con- sumption and letting the user decide whether a certain video download is worth the energy budget available. Finally, we develop NEST, a novel transport framework for delivering ex- tractive summaries of a dataset distributed across multiple producers over NDN. The goal is to exploit diversity in network conditions between a consumer and different producers towards delivering the consumer-specified summary while minimizing latency.