Intrusion Detection Using Machine Learning for Risk Mitigation in IoT-Enabled Smart Irrigation in Smart Farming by Abhishek Raghuvanshi, Umesh Kumar Singh, Guna Sekhar Sajja, Harikumar Pallathadka, Evans Asenso, Mustafa Kamal, Abha Singh, Khongdet Phasinam

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Modeling of Bayesian machine learning with sparrow search algorithm for cyberattack detection in IIoT environment by Faten Khalid Karim, José Varela-Aldás, Mohamad Khairi Ishak, Ayman Aljarbouh, Samih M. Mostafa

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Dual-Model Synergy for Fingerprint Spoof Detection Using VGG16 and ResNet50 by Mohamed Cheniti, Zahid Akhtar, Praveen Kumar Chandaliya

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An explainable unsupervised learning approach for anomaly detection on corneal in vivo confocal microscopy images by Ningning Tang, Qi Chen, Yunyu Meng, Daizai Lei, Li Jiang, Yikun Qin, Xiaojia Huang, Fen Tang, Shanshan Huang, Qianqian Lan, Qi Chen, Lijie Huang, Rushi Lan, Xipeng Pan, Huadeng Wang, Fan Xu, Wenjing He

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Application of Blockchain and Internet of Things in Healthcare and Medical Sector: Applications, Challenges, and Future Perspectives by Pranav Ratta, Amanpreet Kaur, Sparsh Sharma, Mohammad Shabaz, Gaurav Dhiman

“…Few major reasons for using the Blockchain in healthcare systems are its prominent features, i.e., Decentralization, Immutability, Security and Privacy, and Transparency. …”
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Comparative analysis of deep learning and traditional methods for IoT botnet detection using a multi-model framework across diverse datasets by Saeed Ullah, Junsheng Wu, Zhijun Lin, Mian Muhammad Kamal, Hala Mostafa, Muhammad Sheraz, Teong Chee Chuah

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A lightweight Xray-YOLO-Mamba model for prohibited item detection in X-ray images using selective state space models by Kai Zhao, Shufan Peng, Yujin Li, Tianliang Lu

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A Modified MobileNetv3 Coupled With Inverted Residual and Channel Attention Mechanisms for Detection of Tomato Leaf Diseases by Rubina Rashid, Waqar Aslam, Romana Aziz, Ghadah Aldehim

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Hybrid deep learning model for accurate and efficient android malware detection using DBN-GRU. by Heena Kauser Sk, Maria Anu V

“…The model extracts static features (permissions, API calls, intent filters) and dynamic features (system calls, network activity, inter-process communication) from Android APKs, enabling a comprehensive analysis of application behavior.The proposed model was trained and tested on the Drebin dataset, which includes 129,013 applications (5,560 malware and 123,453 benign).Performance evaluation against NMLA-AMDCEF, MalVulDroid, and LinRegDroid demonstrated that DBN-GRU achieved 98.7% accuracy, 98.5% precision, 98.9% recall, and an AUC of 0.99, outperforming conventional models.In addition, it exhibits faster preprocessing, feature extraction, and malware classification times, making it suitable for real-time deployment.By bridging static and dynamic detection methodologies, the DBN-GRU enhances malware detection capabilities while reducing false positives and computational overhead.These findings confirm the applicability of the proposed model in real-world Android security applications, offering a scalable and high-performance malware detection solution.…”
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Blockchain Interoperability for Future Telecoms by Suha Bayraktar, Sezer Gören, Tacha Serif

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Blockchain-Based Value-Added Tax System: A Systematic Review by Vahideh Ghanooni Shishavan, Shaban Elahi, Sadegh Dorri Nogoorani, Ali Yazdian Varjani

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Sylph: An Unsupervised APT Detection System Based on the Provenance Graph by Kaida Jiang, Zihan Gao, Siyu Zhang, Futai Zou

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Enhanced Deep Autoencoder-Based Reinforcement Learning Model with Improved Flamingo Search Policy Selection for Attack Classification by Dharani Kanta Roy, Hemanta Kumar Kalita

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Cryptanalysis of hyperchaotic S-box generation and image encryption by Mohammad Mazyad Hazzazi, Gulraiz, Rashad Ali, Muhammad Kamran Jamil, Sameer Abdullah Nooh, Fahad Alblehai

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VdaBSC: A Novel Vulnerability Detection Approach for Blockchain Smart Contract by Dynamic Analysis by Rexford Nii Ayitey Sosu, Jinfu Chen, Edward Kwadwo Boahen, Zikang Zhang

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Boosting Cyberattack Detection Using Binary Metaheuristics With Deep Learning on Cyber-Physical System Environment by Alanoud Al Mazroa, Fahad R. Albogamy, Mohamad Khairi Ishak, Samih M. Mostafa

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Hybrid Deep Learning Framework for Continuous User Authentication Based on Smartphone Sensors by Bandar Alotaibi, Munif Alotaibi

“…This research proposes a hybrid deep learning framework that combines techniques from computer vision and sequence modeling, namely, ViT-inspired patch extraction, multi-head attention, and BiLSTM networks, to authenticate users continuously from smartphone sensor data. …”
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SwinTCS: A Swin Transformer Approach to Compressive Sensing with Non-Local Denoising by Xiuying Li, Haoze Li, Hongwei Liao, Zhufeng Suo, Xuesong Chen, Jiameng Han

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Cancelable finger vein authentication using multidimensional scaling based on deep learning by Mohamed Hammad, Mohammed ElAffendi, Ahmed A. Abd El-Latif

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Efficient Deep Learning-Based Cyber-Attack Detection for Internet of Medical Things Devices by Abigail Judith, G. Jaspher W. Kathrine, Salaja Silas, Andrew J

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