Classification and Analysis of Android Malware Images Using Feature Fusion Technique
IEEE Access, 2021 The super packed functionalities and artificial intelligence (AI)-powered applications have made the Android operating system a big player in the market.
Jaiteg Singh +5 more
doaj +1 more source
Efficient Malware Analysis Using Subspace-Based Methods on Representative Image Patterns
IEEE Access, 2023 In this paper, we propose a new framework for classifying and visualizing malware files using subspace-based methods. The rise of advanced malware poses a significant threat to internet security, increasing the pressure on traditional cybersecurity ...
Djafer Yahia M Benchadi +2 more
doaj +1 more source
A Practical Approach to Protect IoT Devices against Attacks and Compile Security Incident Datasets [PDF]
, 2019 open access articleThe Internet of Things (IoT) introduced the opportunity of remotely manipulating home appliances (such as heating systems, ovens, blinds, etc.) using computers and mobile devices.
Cruz, Bruno +5 more
core +1 more source
Cybercopters Swarm: Immersive analytics for alerts classification based on periodic data
Frontiers in Virtual Reality, 2023 This paper assesses the usefulness of an interactive and navigable 3D environment to help decision-making in cybersecurity. Malware programs frequently emit periodic signals in network logs; however, normal periodical network activities, such as software
Nicolas Delcombel +2 more
doaj +1 more source
Decentralised firewall for malware detection
, 2017 This paper describes the design and development of a decentralized firewall system powered by a novel malware detection engine. The firewall is built using blockchain technology.
Panigrahi, Rudrakh +3 more
core +1 more source
Android Malware Family Classification Based on Resource Consumption over Time
, 2017 The vast majority of today's mobile malware targets Android devices. This has pushed the research effort in Android malware analysis in the last years.
Aniello, Leonardo +5 more
core +1 more source
Visualization techniques for malware behavior analysis
SPIE Proceedings, 2011 Malware spread via Internet is a great security threat, so studying their behavior is important to identify and classify them. Using SSDT hooking we can obtain malware behavior by running it in a controlled environment and capturing interactions with the target operating system regarding file, process, registry, network and mutex activities.
André R. A. Grégio +1 more
openaire +2 more sources
MalVis: Large-Scale Bytecode Visualization Framework for Explainable Android Malware Detection
Journal of Cybersecurity and PrivacyAs technology advances, developers continually create innovative solutions to enhance smartphone security. However, the rapid spread of Android malware poses significant threats to devices and sensitive data.
Saleh J. Makkawy +2 more
doaj +1 more source
Enhancing Malware Analysis Using Data Visualization Through Shared Code and Attribute Analysis
IEEE AccessMalware analysis is a crucial area of cybersecurity, focusing on identifying, categorizing, and studying malicious software to prevent it from posing a threat to computer systems.
Narayandas Sai Ramana Vashista +1 more
doaj +1 more source
Malware in the Future? Forecasting of Analyst Detection of Cyber Events
, 2018 There have been extensive efforts in government, academia, and industry to anticipate, forecast, and mitigate cyber attacks. A common approach is time-series forecasting of cyber attacks based on data from network telescopes, honeypots, and automated ...
Barabasi +51 more
core +1 more source