Results 61 to 70 of about 4,077 (204)

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

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

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

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

Multiterminal High‐Voltage Direct Current Projects: A Comprehensive Assessment and Future Prospects

High Voltage, EarlyView.
ABSTRACT Multiterminal high‐voltage direct current (MT‐HVDC) systems are an important part of modern power systems, addressing the need for bulk power delivery and efficient renewable energy integration. This paper provides a comprehensive overview of recent advances in MT‐HVDC technology, including launched projects and ongoing initiatives.
Mohammad Hossein Mousavi, Hassan Moradi, Kumars Rouzbehi, Vijay K. Sood   +3 more
wiley   +1 more source

Encrypted Network Traffic Analysis and Classification Utilizing Machine Learning

Sensors
Encryption is a fundamental security measure to safeguard data during transmission to ensure confidentiality while at the same time posing a great challenge for traditional packet and traffic inspection.
Ibrahim A. Alwhbi, Cliff C. Zou, Reem N. Alharbi   +2 more
doaj   +1 more source

Classifying Tor Traffic Encrypted Payload Using Machine Learning

IEEE Access
Tor, a network offering Internet anonymity, presented both positive and potentially malicious applications, leading to the need for efficient Tor traffic monitoring. While most current traffic classification methods rely on flow-based features, these can
Pitpimon Choorod, George Weir, Anil Fernando   +2 more
doaj   +1 more source

Ground truth of Encrypted Traffic Detection

, 2022
Refer to our paper to find details about the way it is generated and the dataset structure. "Encrypted Traffic Detection: Beyond the Port Number Era"
Doroud, Hossein, Alaswad, Ahmad, Dressler, Falko   +2 more
openaire   +1 more source

Affordances, dread, and online fraud: Exploring and advancing social learning theory in online contexts

Criminology, EarlyView.
Abstract We investigate how the affordances of an online context shape the processes of social learning. Using a dataset of more than 11,000 posts from the fraud subdread on the dark web forum Dread, we examine how affordances of platform governance, connectivity, anonymity, invisibility, asynchronicity, and limited oversight influence the components ...
Fangzhou Wang, Timothy Dickinson
wiley   +1 more source

Encrypted DNS --> Privacy? A Traffic Analysis Perspective

, 2019
Virtually every connection to an Internet service is preceded by a DNS lookup which is performed without any traffic-level protection, thus enabling manipulation, redirection, surveillance, and censorship. To address these issues, large organizations such as Google and Cloudflare are deploying recently standardized protocols that encrypt DNS traffic ...
Siby, Sandra, Juarez, Marc, Diaz, Claudia, Vallina-Rodriguez, Narseo, Troncoso, Carmela   +4 more
openaire   +3 more sources