Results 31 to 40 of about 3,469,712 (175)

Learning and classification of malware behavior

, 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., Rieck, K., Holz, T., Willems, C., Laskov, P.   +4 more
core   +1 more source

Performance Monitoring Counter Based Intelligent Malware Detection and Design Alternatives

IEEE Access, 2022
Hardware solutions for malware detection are becoming increasingly important as software-based solutions can be easily compromised by intelligent malware.
Jordan Pattee, Shafayat Mowla Anik, Byeong Kil Lee   +2 more
doaj   +1 more source

Impact Analysis of Malware Based on Call Network API with Heuristic Detection Method [PDF]

, 2020
Malware is a program that has a negative influence on computer systems that don't have user permissions. The purpose of making malware by hackers is to get profits in an illegal way. Therefore, we need a malware analysis.
Suryati, One Tika, Suryati, O. T. (One), Budiono, Avon, Budiono, A. (Avon), Avon Budiono, One Tika Suryati   +5 more
core   +1 more source

Federated Learning for Malware Detection [PDF]

, 2022
In this era of computers, we encounter many problems when handling the devices around us. One of the major problems faced is malware detection. Malware is malicious software that enters a device without the user\u27s permission and accesses sensitive and
Popuri, Sri Harshini, Zhao, Liang
core   +2 more sources

vinayakumarr/Android-Malware-Detection v1

, 2019
Android malware detection using static and dynamic ...
Vinayakumar R
core   +1 more source

[Dataset] Detection of DGA-based Malware Communications from DoH Traffic Using Machine Learning Analysis

, 2022
DoH-DGA-Malware-Traffic-HKD (csv_files.zip, l3-malware.csv, pcap_files.zip, and README.txt): If you use the dataset, please be sure to cite the following paper.Rikima Mitsuhashi, Yong Jin, Katsuyoshi Iida, Takahiro Shinagawa, and Yoshiaki Takai ...
Jin, Yong, Takai, Yoshiaki, Iida, Katsuyoshi, Shinagawa, Takahiro, Mitsuhashi, Rikima   +4 more
core   +1 more source

SAMADroid: A Novel 3-Level Hybrid Malware Detection Model for Android Operating System

IEEE Access, 2018
For the last few years, Android is known to be the most widely used operating system and this rapidly increasing popularity has attracted the malware developer's attention.
Saba Arshad, Munam A. Shah, Abdul Wahid, Amjad Mehmood, Houbing Song, Hongnian Yu   +5 more
doaj   +1 more source

Partial Evaluation for Java Malware Detection [PDF]

, 2015
The fact that Java is platform independent gives hackers the opportunity to write exploits that can target users on any platform, which has a JVM implementation. Metasploit is a well-known source of Java exploits and to circumvent detection by Anti Virus
Andy King, King, Andy, Singh, Ranjeet, Ranjeet Singh   +3 more
core   +1 more source

Multi-Line Defense Against Windows Adversarial Malware by Using Windows PE Information

IEEE Access
Deep learning has recently been in the spotlight among malware detection researchers in the sense that its training-based robust decision process can lead to efficient and effective malware detection.
Hannah Ho, Jun-Won Ho, Sungjin Ho
doaj   +1 more source

An Overview of Modern Malware Detection

, 2022
Malware detection is crucial with malware’s prevalence on the Internet because it functions as an early warning system for the computer secure regarding malware and cyber attacks.
Swati Deshpande
core   +1 more source