Results 81 to 90 of about 5,558 (210)

Malware Classification Using Machine Learning Algorithm [PDF]

, 2021
The rise of malware has resulted in many concerns and trends for future cybercriminals that infect victims\u27 computers to steal information. The majority of the devices are highly vulnerable to simple attacks based on weak passwords, unpatched ...
et. al., Ucu Nugraha,
core  

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

Survey on Visualization of Information Diffusion over Networks

Computer Graphics Forum, EarlyView.
Abstract Information Diffusion (ID) describes how a value (e.g., a pathogen, a rumor, a packet) spreads through an underlying “medium” network of elements (e.g., a social or computer network). Understanding the information diffusion process is essential to predicting trends, controlling misinformation, and enhancing decision‐making as well as ...
T. Baumgartl, M. Sondag, V. Filipov, M. Tuscher, S. Rajendran, S. Miksch, D. Archambault, A. Arleo, T. von Landesberger   +8 more
wiley   +1 more source

Cyberattacks on Small Banks and the Impact on Local Banking Markets

Journal of Money, Credit and Banking, EarlyView.
Abstract Cyberattacks on small banks have direct and spillover effects in local markets. Following successful cyberattacks, hacked small banks experience a decline in deposit growth rates. This effect of cyberattacks is not observed in hacked large banks.
FABIAN GOGOLIN, IVAN LIM, FRANCESCO VALLASCAS   +2 more
wiley   +1 more source

Genetic boosting classification for malware detection [PDF]

2016 IEEE Congress on Evolutionary Computation (CEC), 2016
In the last few years virus writers have made use of new obfuscation techniques with the aim of hindering malware in order to difficult their detection by Anti-Virus engines. Strategies to reverse this trend involve executing potentially malicious programs and monitor the actions they perform in runtime, what is known as dynamic analysis. In this paper
Alejandro Martín, Héctor D. Menéndez 0001, David Camacho   +2 more
openaire   +1 more source

Security Assessment of Private Package Repositories: An Experience on Acc‐Py at CERN

Journal of Software: Evolution and Process, Volume 38, Issue 8, August 2026.
ABSTRACT The introduction of package managers had a huge impact on software development, as they facilitate dependency management and the access to reusable code components. However, reliance on centralized repositories introduces security risks, as they are increasingly exploited in supply chain attacks.
Michele Lizzit, Francesco Pinzauti, Marino Miculan, Vincenzo Riccio   +3 more
wiley   +1 more source

MCPDS: image-based malware classification method using PE metadata alone

Cybersecurity
In response to the increasing threat posed by the exponential growth of malware in cybersecurity, researchers have developed a number of malware classification methods based on malware images and deep learning in recent years.
Yonglin Zhao, Chun Guo, Yuan Ping, Yi Chen, Yunhe Cui, Guowei Shen   +5 more
doaj   +1 more source

Android Malware Detection Technology Based on Deep Convolutional Neural Network

四川大学学报. 自然科学版, 2020
The rapid iteration of the Android system and its open source features have resulted in many variants of Android malware, which brings great challenges to the classification and detection of Android malware.
GAO Yang-Chen, Fang Yong, Liu Liang, ZHANG Lei   +3 more
doaj  

AlquistCoder: A Synthetic Data Approach to Training Compact Secure Coding Assistants and Building Security Benchmarks

Computational Intelligence, Volume 42, Issue 4, August 2026.
ABSTRACT Large language models are increasingly used as programming assistants, but their security behavior remains uneven: they may generate code with vulnerable patterns, and they may provide actionable help for malicious requests. This paper introduces AlquistCoder, a compact 3.8B‐parameter coding assistant designed to address both risks through ...
Ondřej Kobza, Adam Černý, Ivan Dostál, Jan Šedivý, Maria Rigaki, Muris Sladić, Sebastian Garcia   +6 more
wiley   +1 more source

Fast automated unpacking and classification of malware [PDF]

, 2010
"Malware is a pervasive problem in distributed computer and network systems. Identification of malware variants provides great benefit in early detection.
Silvio Cesare (9786254)
core   +3 more sources