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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Machine Learning Models Interpretability For Malware Detection Using Model Agnostic Language For Exploration And Explanation, Ikuromor Mabel Ogiriki
Machine Learning Models Interpretability For Malware Detection Using Model Agnostic Language For Exploration And Explanation, Ikuromor Mabel Ogiriki
Theses and Dissertations
The adoption of the internet as a global platform has birthed a significant rise in cyber-attacks of various forms ranging from Trojans, worms, spyware, ransomware, botnet malware, rootkit, etc. In order to tackle the issue of all these forms of malware, there is a need to understand and detect them. There are various methods of detecting malware which include signature, behavioral, and machine learning. Machine learning methods have proven to be the most efficient of all for malware detection. In this thesis, a system that utilizes both the signature and dynamic behavior-based detection techniques, with the added layer of the …
An Empirical Study On The Efficacy Of Evolutionary Algorithms For Automated Neural Architecture Search, Andrew D. Cuccinello
An Empirical Study On The Efficacy Of Evolutionary Algorithms For Automated Neural Architecture Search, Andrew D. Cuccinello
Theses and Dissertations
The configuration and architecture design of neural networks is a time consuming process that has been shown to provide significant training speed and prediction improvements. Traditionally, this process is done manually, but this requires a large amount of expert knowledge and significant investment of labor. As a result it is beneficial to have automated ways to optimize model architectures. In this thesis, we study the use of evolutionary algorithm for neural architecture search (NAS). Moreover, we investigate the effect of integrating evolutionary NAS into deep reinforcement learning to learn control policy for ATARI game playing. Empirical classification results on the …