Adversarial examples: A survey of attacks and defenses in deep learning-enabled cybersecurity systems

M Macas, C Wu, W Fuertes - Expert Systems with Applications, 2024 - Elsevier
Over the last few years, the adoption of machine learning in a wide range of domains has
been remarkable. Deep learning, in particular, has been extensively used to drive …

Adversarial machine learning attacks and defense methods in the cyber security domain

I Rosenberg, A Shabtai, Y Elovici… - ACM Computing Surveys …, 2021 - dl.acm.org
In recent years, machine learning algorithms, and more specifically deep learning
algorithms, have been widely used in many fields, including cyber security. However …

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 …

Predicting domain generation algorithms with long short-term memory networks

J Woodbridge, HS Anderson, A Ahuja… - arXiv preprint arXiv …, 2016 - arxiv.org
Various families of malware use domain generation algorithms (DGAs) to generate a large
number of pseudo-random domain names to connect to a command and control (C&C) …

A LSTM based framework for handling multiclass imbalance in DGA botnet detection

D Tran, H Mac, V Tong, HA Tran, LG Nguyen - Neurocomputing, 2018 - Elsevier
In recent years, botnets have become a major threat on the Internet. Most sophisticated bots
use Domain Generation Algorithms (DGA) to pseudo-randomly generate a large number of …

A survey on malicious domains detection through DNS data analysis

Y Zhauniarovich, I Khalil, T Yu, M Dacier - ACM Computing Surveys …, 2018 - dl.acm.org
Malicious domains are one of the major resources required for adversaries to run attacks
over the Internet. Due to the important role of the Domain Name System (DNS), extensive …

DeepDGA: Adversarially-tuned domain generation and detection

HS Anderson, J Woodbridge, B Filar - … of the 2016 ACM workshop on …, 2016 - dl.acm.org
Many malware families utilize domain generation algorithms (DGAs) to establish command
and control (C&C) connections. While there are many methods to pseudorandomly generate …

SoK: cryptojacking malware

E Tekiner, A Acar, AS Uluagac, E Kirda… - 2021 IEEE European …, 2021 - ieeexplore.ieee.org
Emerging blockchain and cryptocurrency-based technologies are redefining the way we
conduct business in cyberspace. Today, a myriad of blockchain and cryp-tocurrency …

Phoenix: DGA-based botnet tracking and intelligence

S Schiavoni, F Maggi, L Cavallaro, S Zanero - International Conference on …, 2014 - Springer
Modern botnets rely on domain-generation algorithms (DGAs) to build resilient command-
and-control infrastructures. Given the prevalence of this mechanism, recent work has …

Hincti: A cyber threat intelligence modeling and identification system based on heterogeneous information network

Y Gao, X Li, H Peng, B Fang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Cyber attacks have become increasingly complicated, persistent, organized, and
weaponized. Faces with this situation, drives a rising number of organizations across the …