Results 31 to 40 of about 32,608 (204)

Packed malware variants detection using deep belief networks [PDF]

open access: yesMATEC Web of Conferences, 2020
Malware is one of the most serious network security threats. To detect unknown variants of malware, many researches have proposed various methods of malware detection based on machine learning in recent years.
Zhang Zhigang   +3 more
doaj   +1 more source

Learning and classification of malware behavior

open access: yes, 2022
S.108-125Malicious software in form of Internet worms, computer viruses, and Trojan horses poses a major threat to the security of networked systems. The diversity and amount of its variants severely undermine the effectiveness of classical signature ...
Düssel, P.   +4 more
core   +1 more source

PageRank in malware categorization [PDF]

open access: yesProceedings of the 2015 Conference on research in adaptive and convergent systems, 2015
In this paper, we propose a malware categorization method that models malware behavior in terms of instructions using PageRank. PageRank computes ranks of web pages based on structural information and can also compute ranks of instructions that represent the structural information of the instructions in malware analysis methods.
Kang, BooJoong   +3 more
openaire   +7 more sources

Design of an Automated Malware Analysis System [PDF]

open access: yes, 2010
Malware, malicious software written for the purpose of causing computer-related damage, has existed for many years. Only recently have the monetary advantages of perpetrating malware begun to gain interest from increasingly malicious groups.
Nabholz, Bradley J
core   +1 more source

Analysis of Malware Impact on Network Traffic using Behavior-based Detection Technique [PDF]

open access: yes, 2020
Malware is a software or computer program that is used to carry out malicious activity. Malware is made with the aim of harming user’s device because it can change user’s data, use up bandwidth and other resources without user\u27s permission.
Almaarif, Ahmad, Muhtadi, Adib Fakhri
core   +1 more source

Investigation of bypassing malware defences and malware detections [PDF]

open access: yes2011 7th International Conference on Information Assurance and Security (IAS), 2011
Nowadays, malware incident is one of the most expensive damages caused by attackers. Malwares are caused different attacks, so considerations and implementations of malware defences for internal networks are important. In this papers, different techniques such as repacking, reverse engineering and hex editing for bypassing host-based Anti Virus (AV ...
Farid Daryabar   +2 more
openaire   +2 more sources

A Survey and Evaluation of Android-Based Malware Evasion Techniques and Detection Frameworks

open access: yesInformation, 2023
Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware.
Parvez Faruki   +5 more
doaj   +1 more source

Malware and Malware Detection Techniques: A Survey

open access: yesInternational Journal for Research in Applied Science and Engineering Technology, 2022
Abstract: Malicious software is a kind of software or codes which took some: private data, information from the PC framework, its tasks is to do only malicious objectives to the PC framework, without authorization of the PC clients. The effect of malicious software are worsen to the client.
Sahil Sehrawat, Dr. Dinesh Singh
openaire   +1 more source

Intelligent Vision-Based Malware Detection and Classification Using Deep Random Forest Paradigm

open access: yesIEEE Access, 2020
Malware is a rapidly increasing menace to modern computing. Malware authors continually incorporate various sophisticated features like code obfuscations to create malware variants and elude detection by existing malware detection systems.
S. Abijah Roseline   +3 more
doaj   +1 more source

Task-Aware Meta Learning-Based Siamese Neural Network for Classifying Control Flow Obfuscated Malware

open access: yesFuture Internet, 2023
Malware authors apply different techniques of control flow obfuscation, in order to create new malware variants to avoid detection. Existing Siamese neural network (SNN)-based malware detection methods fail to correctly classify different malware ...
Jinting Zhu   +4 more
doaj   +1 more source

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