Results 31 to 40 of about 97,198 (223)
Research on the Construction of Malware Variant Datasets and Their Detection Method
Applied Sciences, 2022 Malware detection is of great significance for maintaining the security of information systems. Malware obfuscation techniques and malware variants are increasingly emerging, but their samples and API (application programming interface) sequences are ...
Faming Lu +4 more
doaj +1 more source
A Study of the Relationship Between Antivirus Regressions and Label Changes [PDF]
, 2013 AntiVirus (AV) products use multiple components to detect malware. A component which is found in virtually all AVs is the signature-based detection engine: this component assigns a particular signature label to a malware that the AV detects.
Cukier, M. +4 more
core +1 more source
Mathematics, 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
Applied Sciences, 2021 Malware are developed for various types of malicious attacks, e.g., to gain access to a user’s private information or control of the computer system. The identification and classification of malware has been extensively studied in academic societies and ...
Dong-Kyu Chae +4 more
doaj +1 more source
Android Malware Characterization using Metadata and Machine Learning Techniques [PDF]
, 2017 Android Malware has emerged as a consequence of the increasing popularity of smartphones and tablets. While most previous work focuses on inherent characteristics of Android apps to detect malware, this study analyses indirect features and meta-data to ...
Guzmán, Antonio +3 more
core +2 more sources
Python and Malware: Developing Stealth and Evasive Malware without Obfuscation [PDF]
Proceedings of the 18th International Conference on Security and Cryptography, 2021 To appear in SECRYPT ...
Koutsokostas, Vasilios +1 more
openaire +2 more sources
Future 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
Malware Classification based on Call Graph Clustering [PDF]
, 2010 Each day, anti-virus companies receive tens of thousands samples of potentially harmful executables. Many of the malicious samples are variations of previously encountered malware, created by their authors to evade pattern-based detection.
Kinable, Joris, Kostakis, Orestis
core +1 more source
IEEE 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
Packed malware variants detection using deep belief networks [PDF]
MATEC 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