Recurrent neural networks are effective models to process sequences. However, they are
unable to learn long-term dependencies because of their inherent sequential nature. As a …

With significant advancements in Transformers LLMs, NLP has extended its reach into many
research fields due to its enhanced capabilities in text generation and user interaction. One …

Due to the complexity of modern computer systems, novel and unexpected behaviors
frequently occur. Such deviations are either normal occurrences, such as software updates …

Host-based intrusion detection systems (HIDS) can automatically identify adversarial
applications by learning models from system events that represent normal system behaviors …

In recent years DevOps and agile approaches like microservice architectures and
Continuous Integration have become extremely popular given the increasing need for …

Several security and workflow applications require provenance information at the operating
system level for diagnostics. The resulting provenance traces are often more informative if …

Since the multi-sensor embedded systems are spread all over the urban and suburban
areas, there should be a real-time performance analysis framework to monitor the energy …

Tracing, a technique essential for unraveling the complexities of computer systems'
behavior, involves the organized collection of low-level events, enabling anomaly …

The spread of computing-systems, especially the realtime embedded ones, is rapidly
growing in the last years, since they find usage in numerous fields of application, including …

I am particularly grateful to the committee members Dr. Arpan Sainju and Dr Yeqian Liu for
their time, support, and valuable advice. Their insights and feedback have been crucial in …