Lightweight and Secure Face-based Active Authentication for Mobile Users

Keykhaie, Sepehr; Pierre, Samuel

doi:10.1109/tmc.2021.3106256

Cited by 7 publications

(3 citation statements)

References 40 publications

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“…• Training the entire model: In this approach, the entire pre-trained model is used as a starting point, and all the parameters of the model are fine-tuned for the new task. This is suitable when the new task is similar to the original task for which the pretrained model was trained [92].…”

Section: Practical Perspective and Fine-tuning Of Transfer Learning T...mentioning

confidence: 99%

“…From a practical point of view, transfer learning techniques for image classification problems are mainly based on the size and similarity of the dataset. The strategies are summarized into four categories as follows [92] A learning model that is subject to supervision, either for classification or regression problems, must learn from training data to produce accurate predictions. Unfortunately, the problem arises that whenever we make an effort to train a complicated model with an insufficient amount of data for training purposes, overfitting occurs [114].…”

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confidence: 99%

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A Study of CNN and Transfer Learning in Medical Imaging: Advantages, Challenges, Future Scope

et al. 2023

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This paper presents a comprehensive study of Convolutional Neural Networks (CNN) and transfer learning in the context of medical imaging. Medical imaging plays a critical role in the diagnosis and treatment of diseases, and CNN-based models have demonstrated significant improvements in image analysis and classification tasks. Transfer learning, which involves reusing pre-trained CNN models, has also shown promise in addressing challenges related to small datasets and limited computational resources. This paper reviews the advantages of CNN and transfer learning in medical imaging, including improved accuracy, reduced time and resource requirements, and the ability to address class imbalances. It also discusses challenges, such as the need for large and diverse datasets, and the limited interpretability of deep learning models. What factors contribute to the success of these networks? How are they fashioned, exactly? What motivated them to build the structures that they did? Finally, the paper presents current and future research directions and opportunities, including the development of specialized architectures and the exploration of new modalities and applications for medical imaging using CNN and transfer learning techniques. Overall, the paper highlights the significant potential of CNN and transfer learning in the field of medical imaging, while also acknowledging the need for continued research and development to overcome existing challenges and limitations.

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Section: Practical Perspective and Fine-tuning Of Transfer Learning T...mentioning

confidence: 99%

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confidence: 99%

A Study of CNN and Transfer Learning in Medical Imaging: Advantages, Challenges, Future Scope

et al. 2023

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“…This paper proposes a lightweight and secure authentication protocol for mobile networks that uses EAP-TLS and ECDSA. The protocol is designed to provide e cient and secure authentication while minimizing the computational overhead and reducing the communication overhead [13].This paper proposes a lightweight authentication protocol for global mobility networks that uses EAP-TLS and ECDSA. The protocol is designed to provide e cient and secure authentication while ensuring privacy and con dentiality [14].…”

Section: Introductionmentioning

confidence: 99%

Global Mobility Networks: Design and Development of a Secure and Lightweight Authentication Protocol

V¹,

Kanimozhi²

2023

Preprint

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The increasing use of mobile devices and wireless networks has led to the development of global mobility networks, which enable users to access services and data from anywhere in the world. However, ensuring the security of these networks is a major challenge, as they are vulnerable to various attacks such as eavesdropping, impersonation, and data tampering. To address this challenge, this paper proposes a secure and lightweight authentication protocol for global mobility networks, based on two established cryptographic techniques: the Extensible Authentication Protocol - Transport Layer Security (EAP-TLS) and the Elliptic Curve Digital Signature Algorithm (ECDSA). The proposed authentication protocol consists of several key steps, including user registration, certificate distribution, mutual authentication, and session key generation. The protocol uses EAP-TLS to establish a secure channel between the client and the server, and ECDSA to provide secure digital signatures and key generation. The use of ECDSA ensures that the protocol is resistant to various attacks, such as replay attacks and man-in-the-middle attacks. Additionally, the use of EAP-TLS provides mutual authentication between the client and the server, preventing impersonation attacks. The proposed authentication protocol is designed to be lightweight and efficient, making it practical for use in resource-constrained environments such as mobile devices and wireless networks. The protocol has been evaluated through simulations, and the results demonstrate that it provides strong security guarantees while also being efficient in terms of computational resources and communication overhead. Overall, the proposed authentication protocol provides a practical solution for ensuring the security of global mobility networks, while also being lightweight and efficient enough to be used in resource-constrained environments.

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A trusted authentication scheme based on super SIM card for mobile office for industry 4.0

Kong

Zhang

et al. 2023

Neural Comput & Applic

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Lightweight and Secure Face-based Active Authentication for Mobile Users

Cited by 7 publications

References 40 publications

A Study of CNN and Transfer Learning in Medical Imaging: Advantages, Challenges, Future Scope

A Study of CNN and Transfer Learning in Medical Imaging: Advantages, Challenges, Future Scope

Global Mobility Networks: Design and Development of a Secure and Lightweight Authentication Protocol

A trusted authentication scheme based on super SIM card for mobile office for industry 4.0

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