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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 +6 more
wiley +1 more source
Malware Classification Using Ensemble Classifiers [PDF]
, 2018 Antimalware offers detection mechanism to detect and take appropriate action against malware detected. To evade detection, malware authors had introduced polymorphism to malware.
Mohd Hanafi Ahmad Hijazi +6 more
core +1 more source
Engineering Reports, Volume 8, Issue 7, July 2026.Overview of the paper organization, illustrating the hierarchical structure of cybersecurity domains in ICS and CPS, including attack analysis, security approaches, offensive tactics, career guidance, and concluding discussions. ABSTRACT The convergence of operational technology (OT) with IP‐based information systems has exposed industrial control ...
M. A. Khalifa +2 more
wiley +1 more source
Malware Classification with Deep Convolutional Neural Networks [PDF]
, 2018 © 2018 IEEE. In this paper, we propose a deep learning framework for malware classification. There has been a huge increase in the volume of malware in recent years which poses a serious security threat to financial institutions, businesses and ...
Rochan, Mrigank +11 more
core +1 more source
Engineering Reports, Volume 8, Issue 7, July 2026.We propose the Powerful‐but‐Limited Generative AI theorem, demonstrating that embedding human‐inspired constraints, such as fixed utility functions and neuro‐symbolic submission layers, ensures generative AI remains controllable by preventing self‐improvement beyond designer intent.
Saeed Banaeian Far +3 more
wiley +1 more source
Hidden Markov Models for Malware Classification [PDF]
, 2013 Malware is a software which is developed for malicious intent. Malware is a rapidly evolving threat to the computing community. Although many techniques for malware classification have been proposed, there is still the lack of a comprehensible and useful
Annachhatre, Chinmayee
core +1 more source
GRASE: Granulometry Analysis With Semi Eager Classifier to Detect Malware.
International Journal of Interactive Multimedia and Artificial IntelligenceTechnological advancement in communication leading to 5G, motivates everyone to get connected to the internet including ‘Devices’, a technology named Web of Things (WoT).
Mahendra Deore +3 more
doaj +1 more source
EXAMINING THREAT GROUPS FROM THE OUTSIDE: GENERATING HIGH-LEVEL OVERVIEWS OF PERSISTENT AND TRADITIONAL COMPROMISES [PDF]
, 2014 Analyzing threats that have compromised electronic devices is important to compromised organizations, researchers, and law enforcement. Examination of network and host based logs and network traffic is effective in identifying threats, the impact, and ...
Horneman, Angela
core
Mi-maml: classifying few-shot advanced malware using multi-improved model-agnostic meta-learning
CybersecurityMalware classification has been successful in utilizing machine learning methods. However, it is limited by the reliance on a large number of high-quality labeled datasets and the issue of overfitting. These limitations hinder the accurate classification
Yulong Ji, Kunjin Zou, Bin Zou
doaj +1 more source
Efficient malware detection using NLP and deep learning model
Alexandria Engineering JournalMalware has emerged as a significant challenge in contemporary society, growing in tandem with technological advancements. Consequently, the classification of malware has become a pressing concern for various services.
Umesh Gupta +6 more
doaj +1 more source