Graduate School of Informatics

Msc. Candidate: Muhsin Aldemir

Program: Information Systems

Date: 02.09.2019 15:30 p.m

Place: A-108

Abstract: Malicious websites pose major risks to users and businesses including economic damages, privacy breaches and loss of valuable data. Malicious actors use websites as a spreading medium for their motives. Analyzing the relationships between malicious websites and comparing them to benign ones can help understand the problem better, and enable detection and prevention of these websites more accurately. This thesis focuses on detection and characterization of malicious websites using Social Network Analysis (SNA). SNA provides powerful methodologies for discovering and visualizing the relationships between actors. By utilizing the links in between and among malicious and benign websites, graphs were constituted, whose nodes were websites and ties were hyperlinks between them. For this purpose, the data which included the snapshot of the pairwise links amongst millions of websites, the list of malicious websites and their types were obtained from the web. First, the same size networks of malicious and benign websites were characterised and compared using their descriptive properties. Then, using these networks new analyses were carried out to determine malicious websites and their types based on their network structures and link similarities. Results were presented showing the detection accuracies of applied methods.

Related to the applications made to the Department of Modelling and Simulation Multimedia Informatics PhD and MS Programs for 2019-2020 Acadeic Year Fall Term, 2^nd group interviews will be held on Tuesday, September 3, 2019.

Candidates listed below are expected to be present in front of Classroom II-01 (S-01) 15 minutes before of their scheduled time of interview.

Msc. Candidate: Ahmet Serhat Demir

Program: Cyber Security

Date: 04.09.2019 15:00 p.m

Place: A-212

Abstract: Blockchain technology is first known as the secure, immutable, distributed public ledger of the Bitcoin network, which enables value transfer without the need of a trusted third party. Besides cryptocurrencies and finance, blockchain technology has the potential to disrupt several industries, which is made possible with the advance of the smart contracts and decentralized applications. This thesis explores the blockchain technology, Ethereum smart contracts, and investigates the potential of Ethereum Web 3.0 stack for secure information and file sharing in a fully decentralized architecture. It is aimed to discard the need of a central authority in every layer of the application, and cope with the drawbacks of centralized content exchange platforms. Accordingly, a proof-of-concept of a decentralized application is designed. This design is implemented in Ethereum Web 3.0 stack using blockchain for the immutable distributed ledger, Ether for cash transfers, and smart contracts for application logic. Since data storage in blockchain is expensive, Swarm is used for decentralized reliable content storage system. Nevertheless, according to our research, permissionless systems in the Ethereum ecosystem lack necessary data privacy, which causes a risk for secure information exchange. In order to provide a secure way of content exchange, public key encryption is utilized to enable sensitive content delivery without the need of a pre-shared secret. Also, to protect both buyer and seller, a double escrow functionality is implemented. According to the validation and evaluation of our proof-of-concept, we successfully show that Ethereum Web 3.0 stack is applicable for securely sharing digital contents.

Msc. Candidate: Burak Çelik

Program: Cyber Security

Date: 04.09.2019 14:00 p.m

Place: A-212

Abstract: This thesis presents several optimization techniques of AES implementations on CUDA. 6 different CUDA kernels are implemented for AES-128 exhaustive search with different software designs and they are compared with each other using Nsight experiment results. Outcome of these results are used for finding the best CUDA implementation and from it, AES-128, AES-192 and AES-256 versions are created for exhaustive search, on the fly CTR and file encryption. They are compared with CPU implementations in order to decide whether GPU or CPU is the fastest considering these topics. For this comparison, two different type of CPU implementations are created which are AES-NI, using new instruction set of Intel, and basic C++. 1, 2, 4 and 8 threads versions of these implementations are compared with CUDA and results are shared. According to them, CUDA is 21, 19 and 18 times faster than the best CPU implementations for exhaustive search with respect to key length. These ratios are 4 times for CTR implementations in which 37.52 GBs of data can be encrypted each second while using CUDA. File encryption for CUDA is 22, 19 and 17 times faster than the best CPU implementations. CUDA can encrypt 31.24 GBs of data per second in this regard without considering I/O operations.

Related to the applications for Cognitive Sciences PhD Program in 2019-2020 Academic Year Fall Term, 2^nd group interviews will be held on Tuesday, September 3, 2019.

Candidates whose names are listed below are expected to be ready in front of Informatics Classroom II-03 at 10:00 AM.

Lejla Hasandecic-Dapo

Aida Ben Halima

Related to the 2019-2020 Fall applications for Information Systems (MS/PhD) programs:

Interviews for MS and PhD in Information Systems will be held on August 29, 2019.

Note: Candidates who attended to interviews on June 27/28 don’t have obligation to attend the interview again.

Candidates listed below are expected to be present at II-02 and II-03.