Results 61 to 70 of about 1,811,594 (209)

Mobile Malware Classification

International Journal of Engineering & Technology, 2018
Android malware is growing in such an exponential pace which lead to the need of an efficient malware intrusion  detection technique. The single approach of clustering or classification technique in malware intrusion detection yield to high negative positive alarm rate..
Zolidah Kasiran, Norkhushaini Awang, Fatin Nurhanani Rusli   +2 more
openaire   +1 more source

An Efficient Boosting-Based Windows Malware Family Classification System Using Multi-Features Fusion

Applied Sciences, 2023
In previous years, cybercriminals have utilized various strategies to evade identification, including obfuscation, confusion, and polymorphism technology, resulting in an exponential increase in the amount of malware that poses a serious threat to ...
Zhiguo Chen, Xuanyu Ren
doaj   +1 more source

A Novel Feature Representation for Malware Classification

CoRR, 2022
In this study we have presented a novel feature representation for malicious programs that can be used for malware classification. We have shown how to construct the features in a bottom-up approach, and analyzed the overlap of malicious and benign programs in terms of their components.
John Musgrave, Temesguen Messay Kebede, David Kapp, Anca L. Ralescu   +3 more
openaire   +3 more sources

Devious chatbots - interactive malware with a plot [PDF]

, 2009
Many social robots in the forms of conversation agents or Chatbots have been put to practical use in recent years. Their typical roles are online help or acting as a cyber agent representing an organisation.
Wong, K.W., Fung, C.C., Pan, J.Y.
core  

CyberSentinel: A Transparent Defense Framework for Malware Detection in High-Stakes Operational Environments

Sensors
Malware classification is a crucial step in defending against potential malware attacks. Despite the significance of a robust malware classifier, existing approaches reveal notable limitations in achieving high performance in malware classification. This
Mainak Basak, Myung-Mook Han
doaj   +1 more source

Graph neural network‐based attack prediction for communication‐based train control systems

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao, Tao Tang, Bing Bu, Qichang Li   +3 more
wiley   +1 more source

Pattern for malware remediation – A last line of defence tool against Malware in the global communication platform [PDF]

, 2012
Malware is becoming a major problem to every organization that operates on the global communication platform. The malicious software programs are advancing in sophistication in many ways in order to defeat harden deployed defenses. When an organization’s
Fung, Chun Che, Fung, C.C., Pan, J.Y., Pan, Jonathan   +3 more
core  

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.
Baldoni, R., Ciccotelli, Claudio, Roberto Baldoni, Ucci, Daniele, Luca Massarelli, Massarelli, L, Claudio Ciccotelli, Baldoni, Roberto, Ucci, D., Massarelli, Luca, Querzoni, L., Leonardo Querzoni, Ciccotelli, C, Leonardo Aniello, Daniele Ucci, Querzoni, Leonardo, Aniello, L, Aniello, Leonardo   +17 more
core   +1 more source

DAEMON: Dataset/Platform-Agnostic Explainable Malware Classification Using Multi-Stage Feature Mining

IEEE Access, 2021
Numerous metamorphic and polymorphic malicious variants are generated automatically on a daily basis. In order to do that, malware vendors employ mutation engines that transform the code of a malicious program while retaining its functionality, aiming to
Ron Korine, Danny Hendler
doaj   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source