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Evaluation of decentralized email architecture and social network analysis based on email attachment sharing 10.17863/CAM.21035 Tsipenyuk, Gregory Crowcroft, Jon Present day email is provided by centralized services running in the cloud. The services transparently connect users behind middleboxes and provide backup, redundancy, and high availability at the expense of user privacy. In present day mobile environments, users can access and modify email from multiple devices with updates reconciled on the central server. Prioritizing updates is difficult and may be undesirable. Moreover, legacy email protocols do not provide optimal email synchronization and access. Recent phenomena of the Internet of Things (IoT) will see the number of interconnected devices grow to 27 billion by 2021. In the first part of my dissertation I am proposing a decentralized email architecture which takes advantage of user's a IoT devices to maintain a complete email history. This addresses the email reconciliation issue and places data under user control. I replace legacy email protocols with a synchronization protocol to achieve eventual consistency of email and optimize bandwidth and energy usage. The architecture is evaluated on a Raspberry Pi computer. There is an extensive body of research on Social Network Analysis (SNA) based on email archives. Typically, the analyzed network reflects either communication between users or a relationship between the email and the information found in the email's header and the body. This approach discards either all or some email attachments that cannot be converted to text; for instance, images. Yet attachments may use up to 90% of an email archive size. In the second part of my dissertation I suggest extracting the network from email attachments shared between users. I hypothesize that the network extracted from shared email attachments might provide more insight into the social structure of the email archive. I evaluate communication and shared email attachments networks by analyzing common centrality measures and classication and clustering algorithms. I further demonstrate how the analysis of the shared attachments network can be used to optimize the proposed decentralized email architecture. University of Cambridge 2018-06-29 Thesis Doctoral Doctor of Philosophy (PhD) en https://www.repository.cam.ac.uk/handle/1810/273963 controlled.access https://www.repository.cam.ac.uk/bitstreams/c7813331-3027-4be7-9f7b-ac611112e773/download 87eda9de84448d1f82354d60eee3eb5f https://www.repository.cam.ac.uk/bitstreams/f6bf23f1-7546-4d08-8052-966beb927d12/download c93dd0dfb79133b6804a882cf1d78903 https://www.rioxx.net/licenses/all-rights-reserved/ Internet of Things Social Network Analysis Graph Centrality Measures Nearest Neighbor K-Means Clustering Enron