A New Flow-Based Approach for Enhancing Botnet Detection Efficiency Using Convolutional Neural Networks and Long Short-Term Memory
Sign Up to like & getrecommendations! Published in 2025 at "Knowledge and Information Systems"
DOI: 10.1007/s10115-025-02410-9
Abstract: Despite the growing research and development of botnet detection tools, an ever-increasing spread of botnets and their victims is being witnessed. Due to the frequent adaptation of botnets to evolving responses offered by host-based and… read more here.
Keywords: detection; botnet; convolutional neural; botnet detection ... See more keywords
Multi feature behavior approximation model based efficient botnet detection to mitigate financial frauds
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-020-01677-w
Abstract: Money laundering and other financial frauds are increasing day by day and the financial industries face various challenges from them. They construct botnets to generate such fraudulent attacks towards financial sectors. To mitigate such threats… read more here.
Keywords: behavior approximation; multi feature; feature behavior; botnet ... See more keywords
A Novel Traffic Analysis Model for Botnet Discovery in Dynamic Network
Sign Up to like & getrecommendations! Published in 2019 at "Arabian Journal for Science and Engineering"
DOI: 10.1007/s13369-018-3319-7
Abstract: In this paper, we propose a collaborative pattern-based filtering algorithm which is a behavior-based approach to detect bots in association with case-based reasoning and fuzzy pattern recognition techniques. Network traces are used as a pivotal… read more here.
Keywords: analysis model; network; novel traffic; botnet ... See more keywords
Botnet detection in internet of things using stacked ensemble learning model
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-02008-9
Abstract: Botnets are used for malicious activities such as cyber-attacks, spamming, and data theft and have become a significant threat to cyber security. Despite existing approaches for cyber attack detection, botnets prove to be a particularly… read more here.
Keywords: botnet; detection; botnet detection; cyber attacks ... See more keywords
Analysis of Botnet Domain Names for IoT Cybersecurity
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2927355
Abstract: Botnets are widespread nowadays with the expansion of the Internet and commonly occur in many cyber-attacks, resulting in serious threats to network services and users’ properties. With the rapid development of the Internet of Things… read more here.
Keywords: domain names; botnet domain; names iot; botnet ... See more keywords
V-Sandbox for Dynamic Analysis IoT Botnet
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3014891
Abstract: With the increasing use of resource-constrained IoT devices, the number of IoT Botnets has exploded with many variations and ways of penetration. Nowadays, studies based on machine learning and deep learning have focused on dealing… read more here.
Keywords: iot botnet; sandbox dynamic; botnet; dynamic analysis ... See more keywords
Applications of artificial intelligence to detect android botnets: A Survey
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3187094
Abstract: With the growing popularity of Android smart devices, and especially with the recent advances brought on by the COVID-19 pandemic on digital adoption and transformation, the importance of protecting these devices has grown, as they… read more here.
Keywords: android botnets; applications artificial; android botnet; botnet detection ... See more keywords
In-Depth Feature Selection for the Statistical Machine Learning-Based Botnet Detection in IoT Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3204001
Abstract: Attackers compromise insecure IoT devices to expand their botnets in order to launch more influential attacks against their victims. In various studies, machine learning has been used to detect IoT botnet attacks. In this paper,… read more here.
Keywords: machine; machine learning; iot; feature selection ... See more keywords
Traffic Based Sequential Learning During Botnet Attacks to Identify Compromised IoT Devices
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3226700
Abstract: A novel online Compromised Device Identification System (CDIS) is presented to identify IoT devices and/or IP addresses that are compromised by a Botnet attack, within a set of sources and destinations that transmit packets. The… read more here.
Keywords: auto associative; iot devices; traffic based; traffic ... See more keywords
Reliable Machine Learning Model for IIoT Botnet Detection
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3253432
Abstract: Due to the growing number of Industrial Internet of Things (IoT) devices, network attacks like denial of service (DoS) and floods are rising for security and reliability issues. As a result of these attacks, IoT… read more here.
Keywords: iot devices; machine learning; proposed model; reliable machine ... See more keywords
Diving Deep With BotLab-DS1: A Novel Ground Truth-Empowered Botnet Dataset
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3367122
Abstract: Cyberspace faces unparalleled threats due to the rapid rise in botnet attacks and their profound repercussions. Utilizing AI-assisted systems emerges as a potent solution for detecting and neutralizing such attacks. Existing research on botnet attack… read more here.
Keywords: botnet; ground truth; botlab ds1;