Rida Khatoun

The results demonstrate that grounding Mistral-7B within empirically cloned interaction networks produces a realistic simulation framework capable of reproducing complex social dynamics.

Delphi Scanner is introduced, a static malware detection system for Windows PE files that balances efficiency with behavioral interpretation that uses a convolutional neural network to model Windows API sequences to classify PE and a decoupled interpretation layer based on a rule-based layer to categorize APIs into high-level malicious capabilities.

Adaptive Uncertainty-Routed Analysis is introduced, a multimodal email threat detection system that analyzes both the content of an email and its embedded URLs and quantifies prediction uncertainty from a URL classifier.

The scalable and efficient solution against adversarial DDoS attacks, introduced in this work, paves the way towards more resilient and adaptive network defense systems that combine generative adversarial augmentation with recent advances in learning models.

Experimental results show that short browsing sessions are highly identifiable, while future navigation actions are highly predictable from long-term interaction structure combined with recent behavioral context, indicating that repeated interaction patterns remain the dominant predictive signal in the evaluated web-browsing setup.

The findings show that even the presence of a small percentage of biased agents in such a system leads to significant shifts in the opinions of non-biased agents, and semantic analysis demonstrates that rhetorical consistency in textual explanations increases systematically with biased exposure and is partially decoupled from numerical convergenumericalutral agents.

Zorya can now automatically find previously undetected vulnerabilities in compiled Go binaries, even silent integer overflows that other tools miss.