Results 111 to 120 of about 12,725 (233)

A study of the relationship of malware detection mechanisms using Artificial Intelligence

ICT Express
Implementation of malware detection using Artificial Intelligence (AI) has emerged as a significant research theme to combat evolving various types of malwares.
Jihyeon Song, Sunoh Choi, Jungtae Kim, Kyungmin Park, Cheolhee Park, Jonghyun Kim, Ikkyun Kim   +6 more
doaj   +1 more source

Optimal Weighted Voting-Based Collaborated Malware Detection for Zero-Day Malware: A Case Study on VirusTotal and MalwareBazaar

Future Internet
We propose a detection system incorporating a weighted voting mechanism that reflects the vote’s reliability based on the accuracy of each detector’s examination, which overcomes the problem of cooperative detection. Collaborative malware detection is an
Naonobu Okazaki, Shotaro Usuzaki, Tsubasa Waki, Hyoga Kawagoe, Mirang Park, Hisaaki Yamaba, Kentaro Aburada   +6 more
doaj   +1 more source

A New Approach to Malware Detection [PDF]

, 2009
Malware has become one of the most serious threats to computer users. Early techniques based on syntactic signatures can be easily bypassed using program obfuscation. A promising direction is to combine Control Flow Graph (CFG) with instruction-level information.
Hongying Tang, Bo Zhu 0001, Kui Ren 0001
openaire   +1 more source

MalVol-25: a diverse, labeled and detailed malware volatile memory dataset for detection and response testing and validation [PDF]

This Dataset addresses the critical need for high-quality malware datasets that support advanced analysis techniques, particularly reinforcement learning (RL).
Dunsin, Dipo, Almeida Palmieri, Eduardo, Kheddar, Hamza, Ghanem, Mohamed Chahine, Habchi, Yassine   +4 more
core  

The potential use of botnets in malware detection

, 2023
Manapság a kiberbűnözés hatalmas méreteket öltött. Súlyos károkat okozva mind az átlagos felhasználóknak mind az ipari és állami szereplőknek. Ennek okán a malwarek lehetséges detektálása és semlegesítése egy rendkívül fontos és aktuális témakör.
Sántha, Máté Imre
core  

Static analysis framework for permission-based dataset generation and android malware detection using machine learning

EURASIP Journal on Information Security
Since Android is the popular mobile operating system worldwide, malicious attackers seek out Android smartphones as targets. The Android malware can be identified through a number of established detection techniques.
Amarjyoti Pathak, Th. Shanta Kumar, Utpal Barman   +2 more
doaj   +1 more source

Federated Learning for Malware Detection

, 2022
In this era of computers, we encounter many problems when handling the devices around us. One of the major problems faced is malware detection. Malware is malicious software that enters a device without the user\u27s permission and accesses sensitive and
Popuri, Sri Harshini, Zhao, Liang
core  

Stateless Malware Packet Detection by Incorporating Naive Bayes with Known Malware Signatures

Applied Computational Intelligence and Soft Computing, 2014
Malware detection done at the network infrastructure level is still an open research problem ,considering the evolution of malwares and high detection accuracy needed to detect these threats.
Ismahani Ismail, Sulaiman Mohd Nor, Muhammad Nadzir Marsono   +2 more
doaj   +1 more source

MalVol-25: a diverse, labelled and detailed volatile memory dataset for malware detection and response testing and validation [paper] [PDF]

This paper addresses the critical need for high-quality malware datasets that support advanced analysis techniques, particularly machine learning and agentic AI frameworks.
Dunsin, Dipo, Almeida Palmieri, Eduardo, Kheddar, Hamza, Ghanem, Mohamed Chahine, Habchi, Yassine   +4 more
core  

Hybrid Input Model Using Multiple Features From Surface Analysis for Malware Detection

IEEE Access
Many malware detection models have been proposed to protect computers from the ever- increasing number of malware attacks. The features that are obtained from surface analysis and machine learning are often used for malware detection.
Mamoru Mimura, Satoki Kanno
doaj   +1 more source