Results 11 to 20 of about 36,905 (167)
Adaptive secure malware efficient machine learning algorithm for healthcare data
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed +8 more
wiley +1 more source
Application of Distance Metric Learning to Automated Malware Detection
IEEE Access, 2021 Distance metric learning aims to find the most appropriate distance metric parameters to improve similarity-based models such as $k$ -Nearest Neighbors or $k$ -Means. In this paper, we apply distance metric learning to the problem of malware detection.
Martin Jurecek, Robert Lorencz
doaj +1 more source
A Two-Layer Deep Learning Method for Android Malware Detection Using Network Traffic
IEEE Access, 2020 Because of the characteristic of openness and flexibility, Android has become the most popular mobile platform. However, it has also become the most targeted system by mobile malware.
Jiayin Feng +4 more
doaj +1 more source
Mathematics, 2023 Android OS devices are the most widely used mobile devices globally. The open-source nature and less restricted nature of the Android application store welcome malicious apps, which present risks for such devices.
Amerah Alabrah
doaj +1 more source
MACoMal: A Multi-Agent Based Collaborative Mechanism for Anti-Malware Assistance
IEEE Access, 2020 Anti-malware tools remain the primary line of defense against malicious software. There is a wide variety of commercial anti-malware tools in the IT security market.
Mohamed Belaoued +3 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
An Analysis of Android Malware Classification Services
Sensors, 2021 The increasing number of Android malware forced antivirus (AV) companies to rely on automated classification techniques to determine the family and class of suspicious samples.
Mohammed Rashed, Guillermo Suarez-Tangil
doaj +1 more source
Survey of Machine Learning Techniques for Malware Analysis [PDF]
, 2018 Coping with malware is getting more and more challenging, given their relentless growth in complexity and volume. One of the most common approaches in literature is using machine learning techniques, to automatically learn models and patterns behind ...
Aniello, Leonardo +2 more
core +2 more sources
PowerDrive: Accurate De-Obfuscation and Analysis of PowerShell Malware [PDF]
, 2019 PowerShell is nowadays a widely-used technology to administrate and manage Windows-based operating systems. However, it is also extensively used by malware vectors to execute payloads or drop additional malicious contents.
Cara, Fabrizio +3 more
core +2 more sources
Journal of ICT, 2022 Transport Layer Security (TLS) based malware is one of the most hazardous malware types, as it relies on encryption to conceal connections. Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to ...
Kinan Keshkeh +2 more
doaj +1 more source