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hesar--shokoofeh
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Analyzing and Enhancing Methodology Evaluation Methods
, M.Sc. Thesis Sharif University of Technology ; Ramsin, Raman (Supervisor)
Abstract
The emergence of various software development processes with different aspects raises the need to evaluate and measure their capabilities and deficiencies. The evaluation must consider different parameters of software development projects and their similarities, differences and features in the context of existing methodologies; therefore we need criteria that cover these needs. Apart from the research that has been done on analysis and evaluation of software development methodologies and processes, there is a need for a general multi-aspect framework for the evaluation of methodologies with different aspects. Lack of general criteria for covering different aspects and the inadequacy of...
Extended Secret Sharing Scheme in the Presence of Uncertainty and Noisy States
, M.Sc. Thesis Sharif University of Technology ; Haeri, Mohammad (Supervisor)
Abstract
In this research, the issue of outsourcing control calculations to servers or external computing parties for non-ideal situations has been discussed. Due to the confidentiality of the information of the control systems, it is necessary to guarantee and maintain the privacy of the data from sensors to the actuators. In this research, secure multi-party computation using secret sharing has been utilized to establish the privacy of these data and simultaneously outsource control computing. In other words, the goal is to design a secure controller by means of secure multi-party computations. One of the most important challenges in the design of controllers that use communication channels to send...
A Machine-Learning Content and Behaviour Anomaly Detection Model For Web
, M.Sc. Thesis Sharif University of Technology ; Jafari Siavoshani, Mahdi (Supervisor)
Abstract
Intrusion detection systems and firewalls for web applications serve as an important defensive layer for detecting attacks. These systems typically employ either signature- based or anomaly-based approaches. Signature-based methods require expert knowl- edge to generate signatures for malicious data and, therefore, cannot be used to detect unknown threats. In contrast, anomaly-based methods can detect unknown threats but generally with lower accuracy and precision. Detecting legitimate strings within packet content is challenging for anomaly-based models because not all legitimate patterns are observed during the training phase. In this research, a machine learning model is proposed to...