Results 21 to 30 of about 6,055 (181)

SoK: Cryptojacking Malware [PDF]

open access: yes2021 IEEE European Symposium on Security and Privacy (EuroS&P), 2021
Emerging blockchain and cryptocurrency-based technologies are redefining the way we conduct business in cyberspace. Today, a myriad of blockchain and cryptocurrency systems, applications, and technologies are widely available to companies, end-users, and even malicious actors who want to exploit the computational resources of regular users through ...
Tekiner, Ege   +4 more
openaire   +3 more sources

FastText-Based Local Feature Visualization Algorithm for Merged Image-Based Malware Classification Framework for Cyber Security and Cyber Defense

open access: yesMathematics, 2020
The importance of cybersecurity has recently been increasing. A malware coder writes malware into normal executable files. A computer is more likely to be infected by malware when users have easy access to various executables.
Sejun Jang, Shuyu Li, Yunsick Sung
doaj   +1 more source

A Hybrid Approach for Android Malware Detection and Family Classification.

open access: yesInternational Journal of Interactive Multimedia and Artificial Intelligence, 2021
With the increase in the popularity of mobile devices, malicious applications targeting Android platform have greatly increased. Malware is coded so prudently that it has become very complicated to identify.
Meghna Dhalaria, Ekta Gandotra
doaj   +1 more source

An Adaptive Behavioral-Based Incremental Batch Learning Malware Variants Detection Model Using Concept Drift Detection and Sequential Deep Learning

open access: yesIEEE Access, 2021
Malware variants are the major emerging threats that face cybersecurity due to the potential damage to computer systems. Many solutions have been proposed for detecting malware variants.
Abdulbasit A. Darem   +5 more
doaj   +1 more source

The rise of obfuscated Android malware and impacts on detection methods [PDF]

open access: yesPeerJ Computer Science, 2022
The various application markets are facing an exponential growth of Android malware. Every day, thousands of new Android malware applications emerge. Android malware hackers adopt reverse engineering and repackage benign applications with their malicious
Wael F. Elsersy   +2 more
doaj   +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

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   +5 more sources

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

Machine-Learning Classifiers for Malware Detection Using Data Features

open access: yesJournal of ICT Research and Applications, 2021
The spread of ransomware has risen exponentially over the past decade, causing huge financial damage to multiple organizations. Various anti-ransomware firms have suggested methods for preventing malware threats.
Saleh Abdulaziz Habtor   +1 more
doaj   +1 more source

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

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