Security has always been one of the biggest challenges faced by computer systems, recent developments in the field of Machine Learning are affecting almost all aspects of computer science and Cybersecurity is no different. In this paper, we have focused on studying the possible application of deep...
This survey paper describes a literature review of deep learning (DL) methods for cyber security applications. A short tutorial-style description of each DL method is provided, including deep autoencoders, restricted Boltzmann machines, recurrent neural networks, generative adversarial networks, and ...
Deep Instinct takes a prevention-first approach to stopping ransomware and other malware using the world’s first and only purpose-built, deep learning cybersecurity framework.
Deep Instinct takes a prevention-first approach to stopping ransomware and other malware using the world’s first and only purpose-built, deep learning cybersecurity framework.
The UNSW㎞B15 database, collected from a realistic network to evaluate cybersecurity applications, was utilized for training the DL models. The study aims to design a DL architecture for the implementation of secured IoT and to assess the performance and robustness of DL algorithms for detecting ...
Different techniques and algorithms under deep reinforcement learning have shown great promise in applications ranging from games to industrial processes, where it is claimed to augment systems with general AI capabilities. These algorithms have recently also been used in cybersecurity, especially in ...
The combination of binary visualization and machine learning is a powerful technique that can provide new solutions to old problems. It is showing promise in cybersecurity, but it could also be applied to other domains. Detecting malware with deep learning ...
Deep Learning also enables intelligence gathering for better assessment of battle scenarios, and faster aerial or ground analysis. It even helps in understanding enemy behavior and communication.Examples of Deep Learning in the military: Warfare platforms, cybersecurity, logistics and transportation, ...
MEMBER: A multi-task learning model with hybrid deep features for network intrusion detection 2022 Elsevier LtdWith the continuous occurrence of cybersecurity incidents, network intrusion detection has become one of the most critical issues in cyber... J Lan,X Liu,J Sun,... - 《Computers & S...
A Novel Cyber Security Model Using Deep Transfer Learning 2024, Arabian Journal for Science and Engineering View all citing articles on ScopusJiayan Zhang received the B.S. degree in Network Engineering from Nanchang Institute of Technology, Nanchang, Jiangxi, China, in 2018. He is currently workin...