Certificateless aggregate signcryption scheme with multi-ciphertext equality test for the internet of vehicles. by Xiaodong Yang, Xilai Luo, Ruixia Liu, Songyu Li, Ke Yao

“…When compared to similar schemes, this approach exhibits reduced computational overhead while providing superior security features.…”
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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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Leveraging self attention driven gated recurrent unit with crocodile optimization algorithm for cyberattack detection using federated learning framework by Manal Abdullah Alohali, Hatim Dafaalla, Mohammed Baihan, Sultan Alahmari, Achraf Ben Miled, Othman Alrusaini, Ali Alqazzaz, Hanadi Alkhudhayr

“…Cybersecurity includes decreasing the risk of mischievous computer, software, and network attacks. Novel techniques have been combined into emerging artificial intelligence (AI) that attains cybersecurity. …”
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Deep learning driven interpretable and informed decision making model for brain tumour prediction using explainable AI by Khan Muhammad Adnan, Taher M. Ghazal, Muhammad Saleem, Muhammad Sajid Farooq, Chan Yeob Yeun, Munir Ahmad, Sang-Woong Lee

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Review of malware detection and classification visualization techniques by Jinwei WANG, Zhengjia CHEN, Xue XIE, Xiangyang LUO, Bin MA

“…With the rapid advancement of technology, network security faces a significant challenge due to the proliferation of malicious software and its variants.These malicious software use various technical tactics to deceive or bypass traditional detection methods, rendering conventional non-visual detection techniques inadequate.In recent years, data visualization has gained considerable attention in the academic community as a powerful approach for detecting and classifying malicious software.By visually representing the key features of malicious software, these methods greatly enhance the accuracy of malware detection and classification, opening up extensive research opportunities in the field of cyber security.An overview of traditional non-visual detection techniques and visualization-based methods were provided in the realm of malicious software detection.Traditional non-visual approaches for malicious software detection, including static analysis, dynamic analysis, and hybrid techniques, were introduced.Subsequently, a comprehensive survey and evaluation of prominent contemporary visualization-based methods for detecting malicious software were undertaken.This primarily encompasses encompassed the integration of visualization with machine learning and visualization combined with deep learning, each of which exhibits distinct advantages and characteristics within the domain of malware detection and classification.Consequently, the holistic consideration of several factors, such as dataset size, computational resources, time constraints, model accuracy, and implementation complexity, is necessary for the selection of detection and classification methods.In conclusion, the challenges currently faced by detection technologies are summarized, and a forward-looking perspective on future research directions in the field is provided.…”
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YOLOv8 framework for COVID-19 and pneumonia detection using synthetic image augmentation by Uddin A Hasib, Raihan Md Abu, Jing Yang, Uzair Aslam Bhatti, Chin Soon Ku, Lip Yee Por

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Trimodal machine learning based biometrics system by Maciej Szymkowski, Khalid Saeed

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Enhancing Autism Spectrum Disorder Classification with Lightweight Quantized CNNs and Federated Learning on ABIDE-1 Dataset by Simran Gupta, Md. Rahad Islam Bhuiyan, Sadia Sultana Chowa, Sidratul Montaha, Rashik Rahman, Sk. Tanzir Mehedi, Ziaur Rahman

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Robust Face Recognition Using Deep Learning and Ensemble Classification by Pavani Chitrapu, Mahesh Kumar Morampudi, Hemantha Kumar Kalluri

“…Existing methods often struggle to strike a balance between accuracy, computational efficiency, and robustness. Deep learning has become popular for automatically learning features through convolution layers. …”
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Advancing Corn Yield Mapping in Kenya Through Transfer Learning by Ahaan Bohra, Sophie Nottmeyer, Chenchen Ren, Shuo Chen, Yuchi Ma

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Fractional Artificial Protozoa Optimization Enabled Deep Learning for Intrusion Detection and Mitigation in Cyber-Physical Systems by Shaik Abdul Rahim, Arun Manoharan

“…CPSs are gradually growing and utilized in important infrastructure and industries for attaining smart grid, smart transportation, and smart healthcare, which assists governments and citizens. Nevertheless, the network and wireless communication technology creates high complexity, and the intelligence and dynamic of network intrusions make CPS more insecure to network intrusions and provide more critical threats to human life and national security. …”
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ROSE-BOX: A Lightweight and Efficient Intrusion Detection Framework for Resource-Constrained IIoT Environments by Silin Peng, Yu Han, Ruonan Li, Lichen Liu, Jie Liu, Zhaoquan Gu

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Evaluating Lightweight Transformers With Local Explainability for Android Malware Detection by Fatima Bourebaa, Mohamed Benmohammed

“…Mobile phones have evolved into powerful handheld computers, fostering a vast application ecosystem but also increasing security and privacy risks. …”
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DMN-YOLO: A Robust YOLOv11 Model for Detecting Apple Leaf Diseases in Complex Field Conditions by Lijun Gao, Hongwu Cao, Hua Zou, Huanhuan Wu

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Enhancing anomaly detection in plant disease recognition with knowledge ensemble by Jiuqing Dong, Jiuqing Dong, Jiuqing Dong, Heng Zhou, Alvaro Fuentes, Alvaro Fuentes, Sook Yoon, Dong Sun Park, Dong Sun Park

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Constructing segmentation method for wheat powdery mildew using deep learning by Hecang Zang, Hecang Zang, Congsheng Wang, Qing Zhao, Qing Zhao, Jie Zhang, Jie Zhang, Junmei Wang, Guoqing Zheng, Guoqing Zheng, Guoqiang Li, Guoqiang Li

“…Finally, in the deep bottleneck of Swin-Unet network, ResNet network layers are used to increase the expressive power of feature. …”
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Decision-Aid Framework for Face Authentication Detection Using ResNext50 and BiLSTM to Enhance Media Integrity by Ayat Abd-Muti Alrawahneh, Siti Norul Huda Sheikh Abdullah, Tarik Abuain, Sharifah Nurul Asyikin Syed Abdullah, Sarah Khadijah Taylor, Nur Hanis Sabrina Suhaimi

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Multi-View Cluster Structure Guided One-Class BLS-Autoencoder for Intrusion Detection by Qifan Yang, Yu-Ang Chen, Yifan Shi

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Cloud-based optimized deep learning framework for automated glaucoma detection using stationary wavelet transform and improved grey-wolf-optimization with ELM approach by Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, Anuradha S. Kanade, Mohammad Shameem, Harendra S. Jangwan, P.M. Ashok Kumar, Abu Taha Zamani

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Ensemble of Chaotic and Naive Approaches for Performance Enhancement in Video Encryption by Jeyamala Chandrasekaran, S. J. Thiruvengadam

“…Although naive approaches are the most secure for video encryption, the computational cost associated with them is very high. …”
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