A review on social spam detection: Challenges, open issues, and future directions
Abstract Online Social Networks are perpetually evolving and used in plenteous
applications such as content sharing, chatting, making friends/followers, customer …
applications such as content sharing, chatting, making friends/followers, customer …
A survey of deep learning methods for cyber security
DS Berman, AL Buczak, JS Chavis, CL Corbett - Information, 2019 - mdpi.com
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 …
security applications. A short tutorial-style description of each DL method is provided …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
The role of machine learning in cybersecurity
Machine Learning (ML) represents a pivotal technology for current and future information
systems, and many domains already leverage the capabilities of ML. However, deployment …
systems, and many domains already leverage the capabilities of ML. However, deployment …
Deep reinforcement learning for cyber security
The scale of Internet-connected systems has increased considerably, and these systems are
being exposed to cyberattacks more than ever. The complexity and dynamics of …
being exposed to cyberattacks more than ever. The complexity and dynamics of …
Evaluating the robustness of neural networks: An extreme value theory approach
The robustness of neural networks to adversarial examples has received great attention due
to security implications. Despite various attack approaches to crafting visually imperceptible …
to security implications. Despite various attack approaches to crafting visually imperceptible …
How machine learning changes the nature of cyberattacks on IoT networks: A survey
The Internet of Things (IoT) has continued gaining in popularity and importance in everyday
life in recent years. However, this development does not only present advantages. Indeed …
life in recent years. However, this development does not only present advantages. Indeed …
Performance comparison and current challenges of using machine learning techniques in cybersecurity
Cyberspace has become an indispensable factor for all areas of the modern world. The
world is becoming more and more dependent on the internet for everyday living. The …
world is becoming more and more dependent on the internet for everyday living. The …
“real attackers don't compute gradients”: bridging the gap between adversarial ml research and practice
Recent years have seen a proliferation of research on adversarial machine learning.
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …
Deep learning for phishing detection: Taxonomy, current challenges and future directions
Phishing has become an increasing concern and captured the attention of end-users as well
as security experts. Existing phishing detection techniques still suffer from the deficiency in …
as security experts. Existing phishing detection techniques still suffer from the deficiency in …