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Threat modeling is a crucial component of cybersecurity, particularly for industries such as banking, where the security of financial data is paramount. Traditional threat modeling approaches require expert intervention and manual effort, often leadi
Externí odkaz:
http://arxiv.org/abs/2411.17058
Autor:
Chen, Fengchao, Wu, Tingmin, Nguyen, Van, Wang, Shuo, Hu, Hongsheng, Abuadbba, Alsharif, Rudolph, Carsten
Phishing remains a pervasive cyber threat, as attackers craft deceptive emails to lure victims into revealing sensitive information. While Artificial Intelligence (AI), particularly deep learning, has become a key component in defending against phish
Externí odkaz:
http://arxiv.org/abs/2411.11389
Autor:
Liu, Shigang, Sabir, Bushra, Jang, Seung Ick, Kansal, Yuval, Gao, Yansong, Moore, Kristen, Abuadbba, Alsharif, Nepal, Surya
Large Language Models (LLMs) have shown remarkable potential in code generation, making them increasingly important in the field. However, the security issues of generated code have not been fully addressed, and the usability of LLMs in code generati
Externí odkaz:
http://arxiv.org/abs/2410.14321
Indoor tracking and pose estimation, i.e., determining the position and orientation of a moving target, are increasingly important due to their numerous applications. While Inertial Navigation Systems (INS) provide high update rates, their positionin
Externí odkaz:
http://arxiv.org/abs/2409.01002
Autor:
Abuadbba, Alsharif, Rhodes, Nicholas, Moore, Kristen, Sabir, Bushra, Wang, Shuo, Gao, Yansong
Deep learning solutions in critical domains like autonomous vehicles, facial recognition, and sentiment analysis require caution due to the severe consequences of errors. Research shows these models are vulnerable to adversarial attacks, such as data
Externí odkaz:
http://arxiv.org/abs/2407.01260
Autor:
Sabir, Bushra, Yang, Shuiqiao, Nguyen, David, Wu, Nan, Abuadbba, Alsharif, Suzuki, Hajime, Lai, Shangqi, Ni, Wei, Ming, Ding, Nepal, Surya
Artificial Intelligence (AI) has advanced significantly in various domains like healthcare, finance, and cybersecurity, with successes such as DeepMind's medical imaging and Tesla's autonomous vehicles. As telecommunications transition from 5G to 6G,
Externí odkaz:
http://arxiv.org/abs/2407.10981
Text classifiers are vulnerable to adversarial examples -- correctly-classified examples that are deliberately transformed to be misclassified while satisfying acceptability constraints. The conventional approach to finding adversarial examples is to
Externí odkaz:
http://arxiv.org/abs/2405.11904
Autor:
ALSHARIF, Nour H. M.1 bkarpuz@gmail.com, KARPUZ, Başak2
Publikováno v:
Turkish Journal of Mathematics. 2024, Vol. 48 Issue 6, p1110-1126. 17p.
The increasing trend of using Large Language Models (LLMs) for code generation raises the question of their capability to generate trustworthy code. While many researchers are exploring the utility of code generation for uncovering software vulnerabi
Externí odkaz:
http://arxiv.org/abs/2404.03823