Results 101 to 110 of about 24,379 (232)
Malware's Impact on e-Business & m-Commerce: they mean business!
, 2009 Malware is a dominant issue in the e-Business arena. It is affecting many of the key e-Business actors from the end users, to businesses offering online services to intermediaries and critical essential infrastructure needed to ensure continued e ...
Fung, C.C., Pan, J.Y.
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
IoT Malware Detection with Machine Learning [PDF]
, 2022 Embedded devices are increasingly connected to the Internet to provide new and innovative applications in many domains. However, these IoT devices can also contain security vulnerabilities, which allow attackers to compromise them using malware.
Buttyán Levente, Ferenc Rudolf
core
Finding Minimum‐Cost Explanations for Predictions Made by Tree Ensembles
Software: Practice and Experience, Volume 56, Issue 6, Page 615-642, June 2026.ABSTRACT The ability to reliably explain why a machine learning model arrives at a particular prediction is crucial when used as decision support by human operators of critical systems. The provided explanations must be provably correct, and preferably without redundant information, called minimal explanations.
John Törnblom +2 more
wiley +1 more source
, 2017 Malware analysts, besides being tasked to create signatures, are also called upon to generate indicators of compromise, to disrupt botnets, to attribute an attack to an actor, and to understand the adversary's intent.
Lakhotia, Arun +3 more
core +1 more source
Generating Pattern‐Based Datasets for Cyber Attack Detection Using Machine‐Learning Techniques
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.The aim of this work is to review the state of the art in the design, generation, and labeling of attack pattern datasets for training of detection systems based on machine learning. ABSTRACT This work aims to review the state of the art in the design, generation, and labeling of attack pattern datasets for the training of detection systems based on ...
Pedro Díaz García +4 more
wiley +1 more source
Canadian Public Administration, Volume 69, Issue 2, Page 250-277, June 2026.Abstract The war in Ukraine and Israel's successful operations have demonstrated the apparent shift in military operations, strategic defence spending, and innovations. Drawing parallels to the industrial revolution and how it slowly transferred military procurement, training, and deployment, the current study also highlights the AI revolution and the ...
Ehsan Jozaghi
wiley +1 more source
MalSSL—Self-Supervised Learning for Accurate and Label-Efficient Malware Classification
IEEE AccessMalware classification with supervised learning requires a large dataset, which needs an expensive and time-consuming labeling process. In this paper, we explore the efficacy of self-supervised learning techniques for malware classification.
Setia Juli Irzal Ismail +4 more
doaj +1 more source
Proceedings of the 8th International Conference on Information Systems Security and Privacy, 2022 Robert Choudhury +2 more
openaire +1 more source
A Data Mining Classification Approach for Behavioral Malware Detection
Journal of Computer Networks and Communications, 2016 Data mining techniques have numerous applications in malware detection. Classification method is one of the most popular data mining techniques. In this paper we present a data mining classification approach to detect malware behavior.
Monire Norouzi +2 more
doaj +1 more source