Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/5612
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dc.contributor.advisorHassouneh, Yousef
dc.contributor.authorRadwan, Wafaa
dc.date.accessioned2018-07-28T08:46:12Z
dc.date.available2018-07-28T08:46:12Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/20.500.11889/5612
dc.description.abstractThis research studies heuristic search-based optimization of service compositions. We have investigated applying Genetic Algorithms (GA) to optimize service-oriented architectures in terms of security goals and cost. Service composition security risk is measured by implementing the aggregation rules from the local security risk values of the aggregated services in the composition. We adapt the DREAD model for Security risk assessment by suggesting new categorizations for calculating DREAD factors based on a proposed service structure and service attributes. We implemented the YAFA-SOA Optimizer as an extension of an existing implementation of the GA to solve multi-objective optimization problems for varying number of objectives in the context of service oriented architectures. We conducted an experiment to investigate our Research Questions. The experiment results showed that applying multi-objective GA is feasible to find the optimized security and cost in Service oriented architectures. We were able to approve that adding security services to the generated composition reduces the risk severity of the generated composition and enhances its security in terms of confidentiality, integrity and availability (CIA).en_US
dc.language.isoen_USen_US
dc.subjectCloud computing - Securityen_US
dc.subjectService-oriented architecture (Computer science)en_US
dc.subjectGenetic algorithms - Data processingen_US
dc.titleOptimizing security for software deployed on cloud environment using evolutionary searchen_US
dc.title.alternativeتحسين أمن البرمجيات التي تعمل في البيئة السحابية باستخدام الخوارزميات الجينيةen_US
dc.typeThesisen_US
newfileds.departmentGraduate Studiesen_US
newfileds.item-access-typeopen_accessen_US
newfileds.thesis-progScientific Computationen_US
newfileds.general-subjectnoneen_US
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