Malware - Open Access .click

Results 141 to 150 of about 81,305 (190)

A hybrid XGBoost-SVM ensemble framework for robust cyber-attack detection in the internet of medical things (IoMT). [PDF]

Sci Rep
Abdelhaq M +5 more
europepmc +1 more source

JDroid: Android malware detection using hybrid opcode feature vector. [PDF]

PeerJ Comput Sci
Arslan RS.
europepmc +1 more source

A malware detection method with function parameters encoding and function dependency modeling. [PDF]

PeerJ Comput Sci
Hou R, Liu D, Jin X, Weng J, Geng G.
europepmc +1 more source

Tackling fraud detection with an enhanced Kepler optimization and ghost opposition-based learning. [PDF]

Front Artif Intell
Egami RH +3 more
europepmc +1 more source

In-Memory Shellcode Runner Detection in Internet of Things (IoT) Networks: A Lightweight Behavioral and Semantic Analysis Framework. [PDF]

Sensors (Basel)
Dora JR, Hluchý L, Staňo M.
europepmc +1 more source

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malware classification
machine learning
malware detection

deep learning
detection
convolutional neural network

android malware
cyber security
malware visualization

Malware

2007
The Trojan horse can be used in cyber-warfare and cyber-terrorism, as recent attacks in the field of industrial espionage have shown. To coordinate methods of defence a categorisation of the threat posed by Trojan horses in the shape of a list of tuples is proposed.
Stefan Kiltz, Andreas Lang, Jana Dittmann +2 more
openaire +2 more sources

Malware

2006
In the two decades since its first significant appearance, malware has become the most prominent and costly threat to modern IT systems. This chapter examines the nature of malware evolution. It highlights that, as well as the more obvious development of propagation techniques, the nature of payload activities (and the related motivations of the ...
Steven Furnell, Jeremy Ward
openaire +1 more source

Malware behavior image for malware variant identification

2014 International Symposium on Biometrics and Security Technologies (ISBAST), 2014
Several methods have been devised by researchers to facilitate malware analysis and one of them is through malware visualization. Malware visualization is a field that focuses on representing malware features in a form of visual cues that could be used to convey more information about a particular malware.
Syed Zainudeen Mohd Shaid, Mohd Aizaini Maarof +1 more
openaire +1 more source

Optimising Malware

2006 IEEE International Performance Computing and Communications Conference, 2006
J.M. Fernandez, P. Bureau
openaire +2 more sources

malware classification
machine learning
malware detection

deep learning
detection
convolutional neural network

android malware
cyber security
malware visualization