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Digital Forensics For Investigating Control-Logic Attacks In Industrial Control Systems, Nauman Zubair
Digital Forensics For Investigating Control-Logic Attacks In Industrial Control Systems, Nauman Zubair
University of New Orleans Theses and Dissertations
Programmable logic controllers (PLC) are required to handle physical processes and thus crucial in critical infrastructures like power grids, nuclear facilities, and gas pipelines. Attacks on PLCs can have disastrous consequences, considering attacks like Stuxnet and TRISIS. Those attacks are examples of exploits where the attacker aims to inject into a target PLC malicious control logic, which engineering software compiles as a reliable code. When investigating a security incident, acquiring memory can provide valuable insight such as runtime system activities and memory-based artifacts which may contain the attacker's footprints. The existing memory acquisition tools for PLCs require a hardware-level debugging …
Convolutional Neural Networks For Deflate Data Encoding Classification Of High Entropy File Fragments, Nehal Ameen
Convolutional Neural Networks For Deflate Data Encoding Classification Of High Entropy File Fragments, Nehal Ameen
University of New Orleans Theses and Dissertations
Data reconstruction is significantly improved in terms of speed and accuracy by reliable data encoding fragment classification. To date, work on this problem has been successful with file structures of low entropy that contain sparse data, such as large tables or logs. Classifying compressed, encrypted, and random data that exhibit high entropy is an inherently difficult problem that requires more advanced classification approaches. We explore the ability of convolutional neural networks and word embeddings to classify deflate data encoding of high entropy file fragments after establishing ground truth using controlled datasets. Our model is designed to either successfully classify file …