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Improving search space analysis of fuzzing mutators using cryptographic structures (2023)
Conference Proceeding
Chafjiri, S. B., Legg, P., Tsompanas, M., & Hong, J. (in press). Improving search space analysis of fuzzing mutators using cryptographic structures. In Lecture Notes in Network Security

This paper introduces a novel approach to enhance the performance of software fuzzing mutator tools, by leveraging cryptographic structures known as substitution-permutation networks and Feistel networks. By integrating these structures into the exis... Read More about Improving search space analysis of fuzzing mutators using cryptographic structures.

What will make misinformation spread: An XAI perspective (2023)
Conference Proceeding
Bo, H., Wu, Y., You, Z., McConville, R., Hong, J., & Liu, W. (2023). What will make misinformation spread: An XAI perspective. In L. Longo (Ed.), Explainable Artificial Intelligence (321-337). https://doi.org/10.1007/978-3-031-44067-0_17

Explainable Artificial Intelligence (XAI) techniques can provide explanations of how AI systems or models make decisions, or what factors AI considers when making the decisions. Online social networks have a problem with misinformation which is known... Read More about What will make misinformation spread: An XAI perspective.