Aquaculture plays a pivotal role in meeting the growing global demand for seafood. However, ensuring optimal water quality within aquaculture ponds is a pressing challenge. This project proposes a paradigm shift by in...
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This research study investigates the use of homomorphic encryption to bolster data security in multi-cloud environments. As cloud computing gains popularity, safeguarding data confidentiality, integrity, and privacy b...
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Recently, Semi-factual explanations have gained popularity in the eXplainable AI (XAI) community. They provide "even if" justifications to indicate what key input features could change without changing the o...
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Privacy concerns have led to the rise of federated recommender systems (FRS), which can create personalized models across distributed clients. However, FRS is vulnerable to poisoning attacks, where malicious users man...
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As convolutional neural networks (CNNs) have shown excellent performance in various inference tasks, it has become increasingly critical to enable Artificial Intelligence of Things (A IoT) systems to run CNN-based app...
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In the past ten years, there has been a rise in nasty behaviors on social media due to the increased use of these platforms. One of the most offensive of these behaviors is hate speech, so users must safeguard themsel...
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Grasping is essential in robotic manipulation, yet challenging due to object and gripper diversity and real-world complexities. Traditional analytic approaches often have long optimization times, while data-driven met...
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One of the primary organ is the skin. It protects and separates humans from various dangers. Nevertheless, the skin is susceptible to damage and can develop pigmented lesions. Manual classification of Pigmented Skin L...
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As the scale of the networks continually expands,the detection of distributed denial of service(DDoS)attacks has become increasingly *** propose an intelligent detection model named IGED by using improved generalized ...
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As the scale of the networks continually expands,the detection of distributed denial of service(DDoS)attacks has become increasingly *** propose an intelligent detection model named IGED by using improved generalized entropy and deep neural network(DNN).The initial detection is based on improved generalized entropy to filter out as much normal traffic as possible,thereby reducing data *** the fine detection is based on DNN to perform precise DDoS detection on the filtered suspicious traffic,enhancing the neural network’s generalization *** results show that the proposed method can efficiently distinguish normal traffic from DDoS *** with the benchmark methods,our method reaches 99.9%on low-rate DDoS(LDDoS),flooded DDoS and CICDDoS2019 datasets in terms of both accuracy and efficiency in identifying attack flows while reducing the time by 17%,31%and 8%.
The research addresses the critical issue of detecting anomalies in autonomous in-vehicle network communication, focusing on the vulnerability of infotainment systems to denial-of-service attacks. The aim is to explor...
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