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Deep learning: systematic review, models, challenges, and research directions
T Talaei Khoei, H Ould Slimane… - Neural Computing and …, 2023 - Springer
The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …
automation applications. This automation transition can provide a promising framework for …
[HTML][HTML] Advancing IoT security: A systematic review of machine learning approaches for the detection of IoT botnets
Abstract The Internet of Things (IoT) has transformed many aspects of modern life, from
healthcare and transportation to home automation and industrial control systems. However …
healthcare and transportation to home automation and industrial control systems. However …
Unifying the perspectives of nlp and software engineering: A survey on language models for code
Z Zhang, C Chen, B Liu, C Liao, Z Gong, H Yu… - arxiv preprint arxiv …, 2023 - arxiv.org
In this work we systematically review the recent advancements in software engineering with
language models, covering 70+ models, 40+ evaluation tasks, 180+ datasets, and 900 …
language models, covering 70+ models, 40+ evaluation tasks, 180+ datasets, and 900 …
[HTML][HTML] Explainability in AI-based behavioral malware detection systems
Nowadays, our security and privacy are strongly threatened by malware programs which
aim to steal our confidential data and make our systems out of service, among other things …
aim to steal our confidential data and make our systems out of service, among other things …
A review of state-of-the-art malware attack trends and defense mechanisms
The increasing sophistication of malware threats has led to growing concerns in the anti-
malware community, as malware poses a significant danger to online users despite the …
malware community, as malware poses a significant danger to online users despite the …
[HTML][HTML] Android malware detection and identification frameworks by leveraging the machine and deep learning techniques: A comprehensive review
The ever-increasing growth of online services and smart connectivity of devices have posed
the threat of malware to computer system, android-based smart phones, Internet of Things …
the threat of malware to computer system, android-based smart phones, Internet of Things …
Network anomaly intrusion detection based on deep learning approach
YC Wang, YC Houng, HX Chen, SM Tseng - Sensors, 2023 - mdpi.com
The prevalence of internet usage leads to diverse internet traffic, which may contain
information about various types of internet attacks. In recent years, many researchers have …
information about various types of internet attacks. In recent years, many researchers have …
Artificial intelligence-based malware detection, analysis, and mitigation
Malware, a lethal weapon of cyber attackers, is becoming increasingly sophisticated, with
rapid deployment and self-propagation. In addition, modern malware is one of the most …
rapid deployment and self-propagation. In addition, modern malware is one of the most …
Machine learning aided malware detection for secure and smart manufacturing: a comprehensive analysis of the state of the art
In the last decade, the number of computer malware has grown rapidly. Currently,
cybercriminals typically use malicious software (malware) as a means of attacking industrial …
cybercriminals typically use malicious software (malware) as a means of attacking industrial …
[HTML][HTML] A deep learning-based innovative technique for phishing detection in modern security with uniform resource locators
Organizations and individuals worldwide are becoming increasingly vulnerable to
cyberattacks as phishing continues to grow and the number of phishing websites grows. As …
cyberattacks as phishing continues to grow and the number of phishing websites grows. As …