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Domain generation algorithms (DGAs) are commonly used by botnets to generate domain names through which bots can establish a resilient communication channel with their command and control servers. Recent publications presented deep…

Cryptography and Security · Computer Science 2019-02-26 Lior Sidi , Asaf Nadler , Asaf Shabtai

Nowadays, malware campaigns have reached a high level of sophistication, thanks to the use of cryptography and covert communication channels over traditional protocols and services. In this regard, a typical approach to evade botnet…

Cryptography and Security · Computer Science 2021-01-25 Constantinos Patsakis , Fran Casino

Modern malware families often rely on domain-generation algorithms (DGAs) to determine rendezvous points to their command-and-control server. Traditional defence strategies (such as blacklisting domains or IP addresses) are inadequate…

Cryptography and Security · Computer Science 2017-09-22 Pierre Lison , Vasileios Mavroeidis

Many malware families utilize domain generation algorithms (DGAs) to establish command and control (C&C) connections. While there are many methods to pseudorandomly generate domains, we focus in this paper on detecting (and generating)…

Cryptography and Security · Computer Science 2016-11-04 Hyrum S. Anderson , Jonathan Woodbridge , Bobby Filar

Domain generation algorithm (DGA) is used by botnets to build a stealthy command and control (C&C) communication channel between the C&C server and the bots. A DGA can periodically produce a large number of pseudo-random algorithmically…

Cryptography and Security · Computer Science 2022-08-09 Zheng Wang

Domain generation algorithms (DGAs) are frequently employed by malware to generate domains used for connecting to command-and-control (C2) servers. Recent work in DGA detection leveraged deep learning architectures like convolutional neural…

Cryptography and Security · Computer Science 2019-01-29 Joewie J. Koh , Barton Rhodes

Modern botnets rely on domain-generation algorithms (DGAs) to build resilient command-and-control infrastructures. Recent works focus on recognizing automatically generated domains (AGDs) from DNS traffic, which potentially allows to…

Cryptography and Security · Computer Science 2013-11-25 Stefano Schiavoni , Federico Maggi , Lorenzo Cavallaro , Stefano Zanero

New malware emerges at a rapid pace and often incorporates Domain Generation Algorithms (DGAs) to avoid blocking the malware's connection to the command and control (C2) server. Current state-of-the-art classifiers are able to separate…

Cryptography and Security · Computer Science 2022-05-31 Arthur Drichel , Justus von Brandt , Ulrike Meyer

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) server. In order to block DGA C&C traffic, security organizations must…

Cryptography and Security · Computer Science 2016-11-04 Jonathan Woodbridge , Hyrum S. Anderson , Anjum Ahuja , Daniel Grant

A crucial technical challenge for cybercriminals is to keep control over the potentially millions of infected devices that build up their botnets, without compromising the robustness of their attacks. A single, fixed C&C server, for…

Cryptography and Security · Computer Science 2021-08-03 Fran Casino , Nikolaos Lykousas , Ivan Homoliak , Constantinos Patsakis , Julio Hernandez-Castro

Domain Generation Algorithms (DGAs) are frequently used to generate numerous domains for use by botnets. These domains are often utilized as rendezvous points for servers that malware has command and control over. There are many algorithms…

Machine Learning · Computer Science 2020-02-18 Isaac Corley , Jonathan Lwowski , Justin Hoffman

Malware applications typically use a command and control (C&C) server to manage bots to perform malicious activities. Domain Generation Algorithms (DGAs) are popular methods for generating pseudo-random domain names that can be used to…

Cryptography and Security · Computer Science 2020-03-13 Raaghavi Sivaguru , Jonathan Peck , Femi Olumofin , Anderson Nascimento , Martine De Cock

Domain generation algorithms (DGAs) are commonly leveraged by malware to create lists of domain names which can be used for command and control (C&C) purposes. Approaches based on machine learning have recently been developed to…

DGA-based botnet, which uses Domain Generation Algorithms (DGAs) to evade supervision, has become a part of the most destructive threats to network security. Over the past decades, a wealth of defense mechanisms focusing on domain features…

Cryptography and Security · Computer Science 2020-09-22 Xin Fang , Xiaoqing Sun , Jiahai Yang , Xinran Liu

Domain generation algorithms (DGAs) prevent the connection between a botnet and its master from being blocked by generating a large number of domain names. Promising single-data-source approaches have been proposed for separating benign…

Cryptography and Security · Computer Science 2021-09-27 Arthur Drichel , Benedikt Holmes , Justus von Brandt , Ulrike Meyer

Modern malware typically makes use of a domain generation algorithm (DGA) to avoid command and control domains or IPs being seized or sinkholed. This means that an infected system may attempt to access many domains in an attempt to contact…

Cryptography and Security · Computer Science 2019-06-24 Ryan R. Curtin , Andrew B. Gardner , Slawomir Grzonkowski , Alexey Kleymenov , Alejandro Mosquera

Domain Generation Algorithms (DGAs) are used by adversaries to establish Command and Control (C\&C) server communications during cyber attacks. Blacklists of known/identified C\&C domains are often used as one of the defense mechanisms.…

Cryptography and Security · Computer Science 2021-01-05 Ibrahim Yilmaz , Ambareen Siraj , Denis Ulybyshev

An important aspect of many botnets is their capability to generate pseudorandom domain names using Domain Generation Algorithms (DGAs). A cyber criminal can register such domains to establish periodically changing rendezvous points with…

Cryptography and Security · Computer Science 2023-01-13 Nils Weissgerber , Thorsten Jenke , Elmar Padilla , Lilli Bruckschen

In this work, we conduct a comprehensive study on the robustness of domain generation algorithm (DGA) classifiers. We implement 32 white-box attacks, 19 of which are very effective and induce a false-negative rate (FNR) of $\approx$ 100\%…

Cryptography and Security · Computer Science 2024-04-10 Arthur Drichel , Marc Meyer , Ulrike Meyer

Domain Generation Algorithms (DGAs) evolve continuously to evade botnet detection, posing a persistent challenge for dependable network defense. While deep learning-based detectors achieve strong performance under static conditions, they…

Cryptography and Security · Computer Science 2026-05-12 Chaeyoung Lee , Chaeri Jung , Seonghoon Jeong
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