Results 11 to 20 of about 3,020 (212)

A Survey of Botnet and Botnet Detection

2009 Third International Conference on Emerging Security Information, Systems and Technologies, 2009
Among the various forms of malware, botnets are emerging as the most serious threat against cyber-security as they provide a distributed platform for several illegal activities such as launching distributed denial of service attacks against critical targets, malware dissemination, phishing, and click fraud. The defining characteristic of botnets is the
Maryam Feily, Alireza Shahrestani, Sureswaran Ramadass   +2 more
core   +8 more sources

Botnet detection based on generative adversarial network [PDF]

Tongxin xuebao, 2021
In order to solve the problems of botnets’ strong concealment and difficulty in identification, and improve the detection accuracy of botnets, a botnet detection method based on generative adversarial networks was proposed.By reorganizing the data ...
Futai ZOU, Yue TAN, Lin WANG, Yongkang JIANG   +3 more
doaj   +4 more sources

Evading Botnet Detection

Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing
Botnet detection remains a challenging task due to many botnet families with different communication strategies, traffic encryption, and hiding techniques. Machine learning-based methods have been successfully applied, but have proven to be vulnerable to
Lisa-Marie Geiginger, Tanja Zseby
openaire   +2 more sources

MONDEO: Multistage Botnet Detection

CoRR, 2023
Mobile devices have widespread to become the most used piece of technology. Due to their characteristics, they have become major targets for botnet-related malware. FluBot is one example of botnet malware that infects mobile devices. In particular, FluBot is a DNS-based botnet that uses Domain Generation Algorithms (DGA) to establish communication with
Duarte Dias, Bruno Sousa, Nuno Antunes
openaire   +3 more sources

BOTNET DETECTION USING INDEPENDENT COMPONENT ANALYSIS

International Islamic University Malaysia Engineering Journal, 2022
Botnet is a significant cyber threat that continues to evolve. Botmasters continue to improve the security framework strategy for botnets to go undetected.
Wan Nurhidayah Ibrahim, Mohd Syahid Anuar, Ali Selamat, Ondrej Krejcar   +3 more
doaj   +3 more sources

دراسة حول الکشف عن Botne و Botnet

Al-Rafidain Journal of Computer Sciences and Mathematics, 2013
Among the various forms of malware, Botnets are emerging as the most serious threat, Botnets, remotely controlled by the attackers, and whose members are located in homes, schools, businesses, and governments around the world.
Manar Y. Ahmad, Maisireem A. Kamal
doaj   +2 more sources

On the detection and identification of botnets [PDF]

Computers & Security, 2010
We develop and discuss automated and self-adaptive systems for detecting and classifying botnets based on machine learning techniques and integration of human expertise. The proposed concept is purely passive and is based on analyzing information collected at three levels: (i) the payload of single packets received, (ii) observed access patterns to a ...
Alexander K. Seewald, Wilfried N. Gansterer   +1 more
openaire   +2 more sources

BotNet Detection on Social Media

CoRR, 2021
As our reliance on social media platforms and web services increase day by day, exploiters view these platforms as an opportunity to manipulate our thoughts ad actions. These platforms have become an open playground for social bot accounts. Social bots not only learn human conversations, manners, and presence but also manipulate public opinion, act as ...
Aniket Chandrakant Devle, Julia Ann Jose, Abhay Shrinivas Saraswathula, Shubham Mehta, Siddhant Srivastava, Sirisha Kona, Sudheera Daggumalli   +6 more
openaire   +2 more sources

Review of Botnet Attack Detection in SDN-Enabled IoT Using Machine Learning

Sensors, 2022
The orchestration of software-defined networks (SDN) and the internet of things (IoT) has revolutionized the computing fields. These include the broad spectrum of connectivity to sensors and electronic appliances beyond standard computing devices ...
Worku Gachena Negera, Friedhelm Schwenker, Taye Girma Debelee, Henock Mulugeta Melaku, Yehualashet Megeresa Ayano   +4 more
doaj   +1 more source

Botnet Detection Method Based on Graph Reconstruction and Subgraph Mining [PDF]

Zhengzhou Daxue xuebao. Gongxue ban
Aiming at the problem that disguised botnet hosts are difficult to detect, a botnet detection method based on graph reconstruction and subgraph mining (GR-SGM) was proposed. Firstly, network data was converted into graph data which was reconstructed to
JING Yongjun, WU Hui, CHEN Xu, SONG Jifei   +3 more
doaj   +1 more source