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Titlebook: Artificial Intelligence and Blockchain for Future Cybersecurity Applications; Yassine Maleh,Youssef Baddi,Imed Romdhani Book 2021 The Edit

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樓主: 候選人名單
11#
發(fā)表于 2025-3-23 10:40:57 | 只看該作者
Spark Based Intrusion Detection System Using Practical Swarm Optimization Clusterings to discover attacks from such networks. This paper proposes a new Spark based intrusion detection system using particle swarm optimization clustering, referred to as IDS-SPSO, for large scale data able to provide good tradeoff between scalability and accuracy. The use of Particle swarm optimizatio
12#
發(fā)表于 2025-3-23 15:50:41 | 只看該作者
A New Scheme for Detecting Malicious Attacks in Wireless Sensor Networks Based on Blockchain Technolhare sensitive data across multiple sensor nodes, smart devices and transceivers. These sensitive data in WSNs environment is susceptible to various cyber-attacks and threats. Therefore, an efficient security mechanism is needed to handle threats, attacks and security challenges in WSNs. This paper
13#
發(fā)表于 2025-3-23 18:48:35 | 只看該作者
14#
發(fā)表于 2025-3-23 23:49:09 | 只看該作者
Automated Methods for Detection and Classification Pneumonia Based on X-Ray Images Using Deep Learniocess hundreds of X-Ray and Computed Tomography (CT) images to accelerate the diagnosis of pneumonia such as SARS, covid-19, etc., and aid in its containment. Medical image analysis is one of the most promising research areas; it provides facilities for diagnosis and making decisions of several dise
15#
發(fā)表于 2025-3-24 02:30:49 | 只看該作者
16#
發(fā)表于 2025-3-24 08:03:04 | 只看該作者
17#
發(fā)表于 2025-3-24 11:30:42 | 只看該作者
18#
發(fā)表于 2025-3-24 15:46:56 | 只看該作者
https://doi.org/10.1007/978-981-10-5927-8cious sensor nodes. Also, CN uses important parameters such as sensor node-hash value, node-signature and voting degree for malicious to detect malicious nodes in WSNs. The overall results statistic showed that 94.9% of malicious messages were detected and identified successfully during our scheme’s simulation.
19#
發(fā)表于 2025-3-24 23:02:29 | 只看該作者
Urban Land Use Land Cover Changee 3rd person or agency about the incident. It can also manually highlight any object in a frame to keep track of its movement for security purposes. Machine and Deep Learning techniques were used to train models for object detection and facial recognition. The model achieved an accuracy of 97.33% in object detection and 90% in facial recognition.
20#
發(fā)表于 2025-3-25 01:05:03 | 只看該作者
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