Results 61 to 70 of about 1,097,826 (233)

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

Encrypted malicious traffic detection based on neural network

Dianzi Jishu Yingyong
With the widespread application of encrypted communications, traditional malicious traffic detection methods based on content analysis have gradually become ineffective.
Xia Longfei, Zhang Qihao, Wu Xianyun, Zhu Xuetian, Gu Xin, Tian Min   +5 more
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

Enabling pandemic‐resilient healthcare: Narrowband Internet of Things and edge intelligence for real‐time monitoring

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract The Internet of Things (IoT) in deploying robotic sprayers for pandemic‐associated disinfection and monitoring has garnered significant attention in recent research. The authors introduce a novel architectural framework designed to interconnect smart monitoring robotic devices within healthcare facilities using narrowband Internet of Things ...
Md Motaharul Islam, Mohammad Kamrul Hasan, Shayla Islam, Mohammed Balfaqih, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Nurhizam Safie, Zaheed Ahmed Bhuiyan, Rahul Thakkar, Taher M. Ghazal   +9 more
wiley   +1 more source

HSS: enhancing IoT malicious traffic classification leveraging hybrid sampling strategy

Cybersecurity
Using deep learning models to deal with the classification tasks in network traffic offers a new approach to address the imbalanced Internet of Things malicious traffic classification problems.
Yuantu Luo, Jun Tao, Yuehao Zhu, Yifan Xu   +3 more
semanticscholar   +1 more source

Dynamic Resource Allocation Optimisation and Security‐Resilient Control for Bandwidth‐Limited Network Control Systems With Data Conflicts

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Networked control systems (NCSs) often suffer from performance degradation due to limited communication bandwidth, which can cause data transmission conflicts and packet loss. Existing scheduling strategies may fail to simultaneously meet the real‐time requirements and the importance of multisensor data, and they are particularly vulnerable ...
Da Chen, Kaibo Shi, Bin Guo, Kangkang Sun, Huaicheng Yan, Xiao Cai   +5 more
wiley   +1 more source

USING SUPPORT VECTORS TO BUILD A RULE-BASED SYSTEM FOR DETECTING MALICIOUS PROCESSES IN AN ORGANISATION'S NETWORK TRAFFIC

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
The growing complexity and sophistication of cyberattacks on organisational information resources and the variety of malware processes in unprotected networks necessitate the development of advanced methods for detecting malicious processes in network ...
Halyna Haidur, Sergii Gakhov, Dmytro Hamza   +2 more
doaj   +1 more source

AI‐Powered Anomaly Detection for Secure Internet of Things (IoT): Optimising XGBoost and Deep Learning With Bayesian Optimisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim, Lal Hussain, Mohammed A. Alqarni, Faisal S. Alsubaei, Rasha Jamal Atwah   +4 more
wiley   +1 more source

A Probability‐Aware AI Framework for Reliable Anti‐Jamming Communication

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐hopping techniques. Nevertheless, these techniques become vulnerable when facing intelligent jammers.
Tawfeeq Shawly, Ahmed A. Alsheikhy
wiley   +1 more source

MT-FBERT: Malicious Traffic Detection Based on Efficient Federated Learning of BERT

Future Internet
The rising frequency of network intrusions has significantly impacted critical infrastructures, leading to an increased focus on the detection of malicious network traffic in recent years.
Jian Tang, Zhao Huang, Chunqiang Li
doaj   +1 more source