Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Analysing the Encrypted Search Algorithms on Encrypted Data(Izmir Institute of Technology, 2018) Tekin, Leyla; Şahin, Serap; Şahin, SerapIn this thesis, we study the static and dynamic Searchable Symmetric Encryption (SSE) schemes (Cash et al. (2014), Kamara and Moataz (2017)). We present different approaches for secure single- and multi-keyword ranked searches, that are: Sorted, OPEBased, Paillier-Based, Embedded, and Matrix-Based. We extend the base schemes according to these approaches so that the matching documents of a search query are ranked by a relevance score calculation technique like term frequency (tf), term frequency-inverse document frequency (tf-idf) or keyword frequency, depending on the characteristics of the scheme. For this, the existing structures of the schemes are modified since they cannot be directly used for ranked searches. Therefore, the ranking facility is added to them. Further, Matrix-Based Approach is a new hybrid approach that is based on an updated structure of the static scheme (Cash et al. (2014)) and fills a matrix to rank the relevant documents for a search keyword, as in the work (Ibrahim et al. (2012)), however, computing the matrix is totally different from their work.Master Thesis An Analysis of Information Spreading and Privacy Issues on Social Networks(Izmir Institute of Technology, 2017) Sayin, Burcu; Şahin, SerapWith Social Networks (SNs), being populated by a still increasing number of people, who take advantage of the communication and collaboration capabilities that they offer, density of the information, spread over SNs is increasing steadily. Furthermore, the probability of exposure of someone’s personal moments to a wider than expected crowd is also increasing. Hence, analyzing the spreading area and privacy level of any information through a SN is an important issue in social network analysis. By studying the functionalities and characteristics that modern SNs offer, along with the people’s habits and common behavior in them, it is easy to understand that several privacy risks may exist, for many of which people may be unaware of. We address this issue, focusing on interactions with posts in a SN, using Facebook as the research domain. As a novelty, we propose an application tool which visualizes the effect of potential privacy risks in Facebook and provides users to control their privacy. The proposed (and simulated) tool allows a Post Owner to observe the spreading area of his/her post, depending on the selected privacy settings of this post. Moreover, it provides preliminary feedback for all the Facebook users that have interacted with this post, to make them aware of the possible privacy changes, aiming to give them a chance to protect the privacy of their interaction on this post by deleting it when such a privacy change takes place.