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Academic Articles & Research Papers
Showing 9 of 9 academic articles
Kalyan Chakradhar Regula • Advances in computational intelligence and robotics book series
(2025)
Artificial Intelligence (AI) and Cybersecurity have become deeply intertwined, shaping the future of digital safety and resilience. As AI-driven solutions enhance threat detection, automation, and response mechanisms, cybersecurity safeguar...
OPENALEX
DOI: https://doi.org/10.4018/979-8-3373-1142-5.ch015
Anand Handa, Ashu Sharma, Sandeep K. Shukla • Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
(2019)
Machine learning technology has become mainstream in a large number of domains, and cybersecurity applications of machine learning techniques are plenty. Examples include malware analysis, especially for zero‐day malware detection, threat a...
OPENALEX
DOI: https://doi.org/10.1002/widm.1306
Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi, Chenliang Li • ACM Transactions on Intelligent Systems and Technology
(2020)
With the development of high computational devices, deep neural networks (DNNs), in recent years, have gained significant popularity in many Artificial Intelligence (AI) applications. However, previous efforts have shown that DNNs are vulne...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3374217
Wei Xue, Xiaoyan Xia, Pengcheng Wan, Ping Zhong et al. • Tsinghua Science and Technology
(2025)
Deep neural networks are commonly used in computer vision tasks, but they are vulnerable to adversarial samples, resulting in poor recognition accuracy. Although traditional algorithms that craft adversarial samples have been effective in a...
DOAJ
Open Access (DOAJ)
DOI: 10.26599/TST.2024.9010029
Khaled Abud, Sergey Lavrushkin, Dmitry Vatolin • Big Data and Cognitive Computing
(2025)
Neural-network-based models have made considerable progress in many computer vision areas over recent years. However, many works have exposed their vulnerability to malicious input data manipulation—that is, to adversarial attacks. Although...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bdcc9070166
Václav Diviš, Bastian Spatz, Marek Hrúz • AI
(2024)
Recent research has drawn attention to the ambiguity surrounding the definition and learnability of Out-of-Distribution recognition. Although the original problem remains unsolved, the term “Out-of-Model Scope” detection offers a clearer pe...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/ai5040104
Boris Galitsky • Entropy
(2023)
It is well known that deep learning (DNN) has strong limitations due to a lack of explainability and weak defense against possible adversarial attacks. These attacks would be a concern for autonomous teams producing a state of high entropy ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/e25111496
Chen Xinyu, Hui Tianfang, Li Yanlin, Yang Haoyuan • ITM Web of Conferences
(2025)
As artificial intelligence (AI) is increasingly integrated into society, people are relying on it more and more, and higher requirements are put forward for the safety and ethical standards of AI. This article explores the development of ar...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/itmconf/20257004031
Urslla Uchechi Izuazu, Cosmas Ifeanyi Nwakanma, Dong-Seong Kim, Jae Min Lee • Discover Internet of Things
(2025)
Abstract Deep learning-based intrusion detection systems (DL-IDS) have proven effective in detecting cyber threats. However, their vulnerability to adversarial attacks and environmental noise, particularly in industrial settings, limits pra...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s43926-025-00100-0