With the rapid development and widespread application of information, computer, and communication technologies, Cyber-Physical-Social systems (CPSS) have gained increasing importance and attention. To enable intellige...
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A capsule neural network faces significant challenges in achieving high accuracy on complex datasets due to its high computational complexity and limited ability to represent features. To overcome these limitations, t...
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Concept drift is a main security issue that has to be resolved since it presents a significant barrier to the deployment of machine learning(ML)*** to attackers’(and/or benign equivalents’)dynamic behavior changes,t...
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Concept drift is a main security issue that has to be resolved since it presents a significant barrier to the deployment of machine learning(ML)*** to attackers’(and/or benign equivalents’)dynamic behavior changes,testing data distribution frequently diverges from original training data over time,resulting in substantial model *** to their dispersed and dynamic nature,distributed denial-of-service attacks pose a danger to cybersecurity,resulting in attacks with serious consequences for users and *** paper proposes a novel design for concept drift analysis and detection of malware attacks like Distributed Denial of Service(DDOS)in the *** goal of this architecture combination is to accurately represent data and create an effective cyber security prediction *** intrusion detection system and concept drift of the network has been analyzed using secure adaptive windowing with website data authentication protocol(SAW_WDA).The network has been analyzed by authentication protocol to avoid malware *** data of network users will be collected and classified using multilayer perceptron gradient decision tree(MLPGDT)*** on the classification output,the decision for the detection of attackers and authorized users will be *** experimental results show output based on intrusion detection and concept drift analysis systems in terms of throughput,end-end delay,network security,network concept drift,and results based on classification with regard to accuracy,memory,and precision and F-1 score.
Dengue shock syndrome (DSS) is an infectious disease that affects millions of people every year all over the world. Early detection of DSS is essential for providing effective therapy and promoting patient recovery. I...
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Breast cancer is the most prevalent cancer among women and can be deadly, necessitating early detection to enhance patient outcomes and treatment effectiveness. Recently, Machine Learning (ML) techniques have shown po...
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Machine learning-based systems have emerged as the primary means for achieving the highest levels of productivity and efficiency. They have become the most influential competitive factor for many technologies and busi...
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Accurate land cover classification is essential for effective environmental monitoring and resource management. This study aims to evaluate the performance of different machine learning algorithms for land cover class...
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In recent years, there has been a growing interest in Speech Emotion Recognition (SER) due to its wide-ranging applications. To enhance the accuracy of emotion recognition systems, this paper employs a combination of ...
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This paper put forward an embedded scheme to execute image watermarking in light of the discrete wavelet transform (DWT), singular value decomposition (SVD) and Charge system Search (CSS) method. In the proposed schem...
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Digital video watermarking research has yielded numerous promising breakthroughs in recent years. As more people grow interested in videos, the copyright protection of videos has become an urgent issue that must be ad...
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Digital video watermarking research has yielded numerous promising breakthroughs in recent years. As more people grow interested in videos, the copyright protection of videos has become an urgent issue that must be addressed. Digital video watermarking is a significant method for copyright protection of videos because of the growing need to safeguard video data’s intellectual property. Some existing works cannot resist geometric attacks effectively, while others fail to address the balance between robustness and visual imperceptibility. Significant progress has been made in studying fractional orthogonal moments due to their geometric invariance and beneficial image description capabilities. For these reasons, this paper proposes a robust watermarking algorithm for color video using accurate quaternion fractional Gegenbauer moments (QFrGMs), which are constructed relying on a combination of quaternion theory and accurate fractional Gegenbauer moments (FrGMs). The proposed algorithm is designed to address existing deficiencies in some related works and improve resilience. This algorithm is imperceptibly invisible and resistant to various kinds of attacks. In the proposed algorithm, the watermark information is embedded into accurately selected coefficients of QFrGMs for the selected frame of the cover video. This algorithm is robust to geometric attacks due to the outstanding geometric invariance of QFrGMs. To ensure security and improve the suggested algorithm’s security, we employed a chaotic map termed a one-dimensional Logistic Sine Cosine (LSC) map with superior chaotic characteristics to scramble the watermark. Numerical experiments were performed regarding imperceptibility and robustness to test the effectiveness. The experimental results demonstrated that the proposed method provides high visual quality and robustness against common signal processing, geometric, frame averaging, frame swapping, and frame dropping attacks. Furthermore, the proposed algorithm e
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