Results 51 to 60 of about 36,905 (167)

Reviewer Integration and Performance Measurement for Malware Detection

, 2016
We present and evaluate a large-scale malware detection system integrating machine learning with expert reviewers, treating reviewers as a limited labeling resource.
Afroz, Sadia, Bachwani, Rekha, Faizullabhoy, Riyaz, Huang, Ling, Joseph, Anthony D., Kantchelian, Alex, Miller, Brad, Shankar, Vaishaal, Tschantz, Michael Carl, Tygar, J. D., Wu, Tony, Yiu, George   +11 more
core   +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

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

From Ambiguous Queries to Verifiable Insights: A Task‐Driven Framework for LLM‐Powered SOC Analysis⋆

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Security operations centre (SOC) analysts must investigate alerts, correlate threat intelligence and interpret heterogeneous telemetry under tight timing constraints. Although large language models (LLMs) offer strong understanding capabilities, directly applying them to SOC environments remains challenging due to semantic ambiguity in analyst
Huan Zhang, Haiyan Wang, Hao Tan, Liyi Zeng, Jingnan Li, Zhaoquan Gu   +5 more
wiley   +1 more source

Obfuscated Malware Detection and Classification in Network Traffic Leveraging Hybrid Large Language Models and Synthetic Data

Sensors
Android malware detection remains a critical issue for mobile security. Cybercriminals target Android since it is the most popular smartphone operating system (OS). Malware detection, analysis, and classification have become diverse research areas.
Mehwish Naseer, Farhan Ullah, Samia Ijaz, Hamad Naeem, Amjad Alsirhani, Ghadah Naif Alwakid, Abdullah Alomari   +6 more
doaj   +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

DCmal-2025: A Novel Routing-Based DisConnectivity Malware—Development, Impact, and Countermeasures

Applied Sciences
Operating systems such as Windows, Linux, and macOS include built-in commands that enable administrators to perform essential tasks. These same commands can be exploited by attackers for malicious purposes that may go undetected by traditional security ...
Mai Abu-Jazoh, Iman Almomani, Khair Eddin Sabri   +2 more
doaj   +1 more source

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

Applied AI Letters, Volume 7, Issue 2, June 2026.
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

Android Kötücül Yazılım Tespit Sistemleri İncelemesi

Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2017
Akıllı telefonların hayatımıza girmesiyle birlikte akıllı telefonları kullanan kullanıcı sayısı her geçen gün artarak devam etmektedir. Akıllı telefonların fazla talep görmesindeki neden, insanların bir cihazla istedikleri işleri tek dokunuşla kolaylıkla
Ömer KİRAZ, İbrahim Alper DOĞRU
doaj   +4 more sources

Generating Pattern‐Based Datasets for Cyber Attack Detection Using Machine‐Learning Techniques

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.
The aim of this work is to review the state of the art in the design, generation, and labeling of attack pattern datasets for training of detection systems based on machine learning. ABSTRACT This work aims to review the state of the art in the design, generation, and labeling of attack pattern datasets for the training of detection systems based on ...
Pedro Díaz García, Diego López Abril, Javier Bermejo Higuera, Víctor Gonzalez Llorente, Miguel Angel Sicilia Urbán   +4 more
wiley   +1 more source