Adversarial machine learning attacks and defense methods in the cyber security domain
In recent years, machine learning algorithms, and more specifically deep learning
algorithms, have been widely used in many fields, including cyber security. However …
algorithms, have been widely used in many fields, including cyber security. However …
Tight arms race: Overview of current malware threats and trends in their detection
Cyber attacks are currently blooming, as the attackers reap significant profits from them and
face a limited risk when compared to committing the “classical” crimes. One of the major …
face a limited risk when compared to committing the “classical” crimes. One of the major …
Understanding the mirai botnet
The Mirai botnet, composed primarily of embedded and IoT devices, took the Internet by
storm in late 2016 when it overwhelmed several high-profile targets with massive distributed …
storm in late 2016 when it overwhelmed several high-profile targets with massive distributed …
A visualized botnet detection system based deep learning for the internet of things networks of smart cities
R Vinayakumar, M Alazab, S Srinivasan… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Internet of Things applications for smart cities have currently become a primary target for
advanced persistent threats of botnets. This article proposes a botnet detection system …
advanced persistent threats of botnets. This article proposes a botnet detection system …
On the effectiveness of machine and deep learning for cyber security
Machine learning is adopted in a wide range of domains where it shows its superiority over
traditional rule-based algorithms. These methods are being integrated in cyber detection …
traditional rule-based algorithms. These methods are being integrated in cyber detection …
Malicious URL detection using machine learning: A survey
Malicious URL, aka malicious website, is a common and serious threat to cybersecurity.
Malicious URLs host unsolicited content (spam, phishing, drive-by exploits, etc.) and lure …
Malicious URLs host unsolicited content (spam, phishing, drive-by exploits, etc.) and lure …
Realtime robust malicious traffic detection via frequency domain analysis
Machine learning (ML) based malicious traffic detection is an emerging security paradigm,
particularly for zero-day attack detection, which is complementary to existing rule based …
particularly for zero-day attack detection, which is complementary to existing rule based …
Detection of malicious web activity in enterprise computer networks
A processing device in one embodiment comprises a processor coupled to a memory and is
configured to obtain internal log data of a computer network of an enterprise, to extract …
configured to obtain internal log data of a computer network of an enterprise, to extract …
Poirot: Aligning attack behavior with kernel audit records for cyber threat hunting
Cyber threat intelligence (CTI) is being used to search for indicators of attacks that might
have compromised an enterprise network for a long time without being discovered. To have …
have compromised an enterprise network for a long time without being discovered. To have …
A comprehensive measurement study of domain generating malware
Recent years have seen extensive adoption of domain generation algorithms (DGA) by
modern botnets. The main goal is to generate a large number of domain names and then …
modern botnets. The main goal is to generate a large number of domain names and then …