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 …

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 …

Artificial neural network for cybersecurity: A comprehensive review

P Podder, S Bharati, M Mondal, PK Paul… - arxiv preprint arxiv …, 2021 - arxiv.org
Cybersecurity is a very emerging field that protects systems, networks, and data from digital
attacks. With the increase in the scale of the Internet and the evolution of cyber attacks …

Adversarial defense: DGA-based botnets and DNS homographs detection through integrated deep learning

V Ravi, M Alazab, S Srinivasan… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Cybercriminals use domain generation algorithms (DGAs) to prevent their servers from
being potentially blacklisted or shut down. Existing reverse engineering techniques for DGA …

Character level based detection of DGA domain names

B Yu, J Pan, J Hu, A Nascimento… - 2018 international joint …, 2018 - ieeexplore.ieee.org
Recently several different deep learning architectures have been proposed that take a string
of characters as the raw input signal and automatically derive features for text classification …

A novel fully convolutional neural network approach for detection and classification of attacks on industrial IoT devices in smart manufacturing systems

M Shahin, FF Chen, H Bouzary… - … International Journal of …, 2022 - Springer
Abstract Recently, Internet of things (IoT) devices have been widely implemented and
technologically advanced in manufacturing settings to monitor, collect, exchange, analyze …

Performance analysis of DGA-driven botnets using artificial neural networks

N Manikandan, D Ruby, S Murali… - 2022 10th International …, 2022 - ieeexplore.ieee.org
A botnet is a network of devices infected with malware and controlled remotely by a person
with malicious intent. Botnets can launch attacks to steal data, perform phishing, spamming …

Algorithmically generated malicious domain names detection based on n-grams features

A Cucchiarelli, C Morbidoni, L Spalazzi… - Expert Systems with …, 2021 - Elsevier
Botnets are one of the major cyber infections used in several criminal activities. In most
botnets, a Domain Generation Algorithm (DGA) is used by bots to make DNS queries aimed …

Dictionary extraction and detection of algorithmically generated domain names in passive DNS traffic

M Pereira, S Coleman, B Yu, M DeCock… - Research in Attacks …, 2018 - Springer
Automatic detection of algorithmically generated domains (AGDs) is a crucial element for
fighting Botnets. Modern AGD detection systems have benefited from the combination of …

Replacedga: Bilstm based adversarial dga with high anti-detection ability

X Hu, H Chen, M Li, G Cheng, R Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Botnets extensively leverage Domain Generation Algorithms (DGAs) to establish reliable
communication channels between bots and Command and Control (C&C) servers …