Results 11 to 20 of about 5,992 (166)

Botnet detection based on generative adversarial network [PDF]

open access: yesTongxin 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   +3 more
doaj   +4 more sources

Multilayer Framework for Botnet Detection Using Machine Learning Algorithms

open access: yesIEEE Access, 2021
A botnet is a malware program that a hacker remotely controls called a botmaster. Botnet can perform massive cyber-attacks such as DDOS, SPAM, click-fraud, information, and identity stealing. The botnet also can avoid being detected by a security system.
Hamido Fujita   +2 more
exaly   +3 more sources

Detecting A Botnet By Reverse Engineering [PDF]

open access: yesIJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2013
— Botnet malware is a malicious program. Botnet that infects computers, called bots, will be controlled by a botmaster to do various things such as: spamming, phishing, keylogging Distributed Denial of Service (DDoS) and other activities that are ...
Oesman Hendra Kelana, Khabib Mustofa
doaj   +2 more sources

Explainable artificial intelligence for botnet detection in internet of things [PDF]

open access: yesScientific Reports
The proliferation of internet of things (IoT) devices has led to unprecedented connectivity and convenience. However, this increased interconnectivity has also introduced significant security challenges, particularly concerning the detection and ...
Mohamed Saied, Shawkat Guirguis
doaj   +2 more sources

A Two-Fold Machine Learning Approach to Prevent and Detect IoT Botnet Attacks

open access: yesIEEE Access, 2021
The botnet attack is a multi-stage and the most prevalent cyber-attack in the Internet of Things (IoT) environment that initiates with scanning activity and ends at the distributed denial of service (DDoS) attack.
Ubaid Ullah Fayyaz   +2 more
exaly   +3 more sources

Adaptive secure malware efficient machine learning algorithm for healthcare data

open access: yesCAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed   +8 more
wiley   +1 more source

BOTNET DETECTION USING INDEPENDENT COMPONENT ANALYSIS

open access: yesInternational 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   +3 more
doaj   +1 more source

Botnet Identification Technology Based on Fuzzy Clustering [PDF]

open access: yesJisuanji gongcheng, 2018
A Botnet that combining worms,backdoors,and Trojans has become the backing of Advanced Persistent Threat(APT) attacks because it can be used by attackers to send spam,perform denial of service attacks,and steal sensitive information.Existing Botnet ...
CHEN Ruidong,ZHAO Lingyuan,ZHANG Xiaosong
doaj   +1 more source

Enhancing the security in cyber-world by detecting the botnets using ensemble classification based machine learning

open access: yesMeasurement: Sensors, 2023
With various malware, botnets are the legitimate risk increasing against cybersecurity providing criminal operations like malware dispersal, distributed denial of service attacks, fraud clicking, phishing, and identification of theft. Existing techniques
Sathiyandrakumar Srinivasan   +1 more
doaj   +1 more source

An Automated Behaviour-Based Clustering of IoT Botnets

open access: yesFuture Internet, 2021
The leaked IoT botnet source-codes have facilitated the proliferation of different IoT botnet variants, some of which are equipped with new capabilities and may be difficult to detect.
Tolijan Trajanovski, Ning Zhang
doaj   +1 more source

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