4.5 Article

A trust infrastructure based authentication method for clustered vehicular ad hoc networks

期刊

PEER-TO-PEER NETWORKING AND APPLICATIONS
卷 14, 期 4, 页码 2537-2553

出版社

SPRINGER
DOI: 10.1007/s12083-020-01010-4

关键词

Vehicular ad hoc networks (VANETs); Authentication; Trust management; Clustering; Monitoring

向作者/读者索取更多资源

This paper proposes a trust-based authentication method to enhance the security of clustered vehicular ad hoc networks, maintaining stability of the entire network through trust estimation and cluster head selection. Messages are digitally signed and encrypted by the sender, decrypted and authenticated by the receiver to improve the accuracy in detecting malicious nodes and reduce authentication delay and overhead.
Vehicular Ad hoc Networks (VANETs) as a subset of mobile ad hoc networks which allow communication between any vehicle with other adjacent vehicles, road side units and infrastructure. In these networks, the purpose is to enhance the security, improve the management of urban and road traffic and provide services to the passenger. Due to problems such as reliability and privacy, messages that are exchanged in the network should be confidential and secure. Therefore, we need a secure topology to maintain trust, which enables the cryptographic process. In this paper, a trust based authentication method for clustered vehicular ad hoc networks is proposed. The efficient authentication method should be able to accurately detect malicious nodes and reduced delay and overhead. The main purpose of the proposed method is to create trustworthy and stable clusters that lead to the stability of the entire network. For this purpose, we estimate the trust degree of each vehicle by combining the trust between vehicles and the trust between the vehicle and Road Side Units (RSUs), and Cluster Heads (CHs) are selected based on this estimated trust degree. Cluster Heads along with verifiers are responsible for monitoring each vehicle. On the other hand, the cluster heads provide an optimal and secure route for transmitting messages. Messages are digitally signed by the sender and encrypted using a public/private key as distributed by a Trusted Authority (TA) and decrypted by the destination; so that each message contains a certificate from a trusted authority. In this identification, the sender and receiver of the message are verified and authentication will be achieved. By simulation results, it is proves that the proposed method increases the accuracy in detecting malicious nodes and the packet delivery ratio, and decreases the delay of authentication and overhead.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Computer Science, Information Systems

Privacy protection framework for face recognition in edge-based Internet of Things

Yun Xie, Peng Li, Nadia Nedjah, Brij B. Gupta, David Taniar, Jindan Zhang

Summary: Edge computing provides a solution to the limited storage and computing resources of IoT-based face recognition systems, but data privacy leak remains a problem. This study proposes a general privacy protection framework, utilizing local differential privacy algorithm and identity authentication technology to protect the privacy of face data.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2023)

Article Engineering, Electrical & Electronic

A Context-Aware Multi-Event Identification Method for Nonintrusive Load Monitoring

Runhai Jiao, Chengyang Li, Gangyi Xun, Tianle Zhang, Brij B. Gupta, Guangwei Yan

Summary: This paper proposes an end-to-end NILM method for multi-event identification by using convolutional neural networks and multi-head self-attention mechanism. It also introduces a multi-scale anchor detection framework and a novel data augmentation method. Experimental results show that the proposed method achieves a higher average F-1 score of 0.96 compared to other methods.

IEEE TRANSACTIONS ON CONSUMER ELECTRONICS (2023)

Article Computer Science, Information Systems

A Caching-Based Dual K-Anonymous Location Privacy-Preserving Scheme for Edge Computing

Shiwen Zhang, Biao Hu, Wei Liang, Kuan-Ching Li, Brij B. Gupta

Summary: This article proposes a caching-based dual K-anonymous (CDKA) location privacy-preserving scheme in edge computing environments. The scheme uses an edge server to protect user location privacy by reducing device load and providing dual anonymity. Through security analysis and performance evaluation, the robustness and relatively low communication cost of the scheme are demonstrated.

IEEE INTERNET OF THINGS JOURNAL (2023)

Article Engineering, Electrical & Electronic

RBWCI: Robust and Blind Watermarking Framework for Cultural Images

Samrah Mehraj, Subreena Mushtaq, Shabir A. Parah, Kaiser J. Giri, Javaid A. Sheikh, Amir H. Gandomi, Mohammad Hijji, Brij B. Gupta, Khan Muhammad

Summary: Heritage multimedia is a valuable cultural asset that provides insights into earlier generations and their creative approach, lifestyle, and historical ideologies. It is also an important resource for boosting the local economy, sustainable communities, and tourism and business sectors. With the advancements in technology and 5G networks, protecting heritage media from unauthorized consumers is crucial. This study proposes a robust and blind watermarking-framework for cultural images (RBWCI) that uses the discrete cosine transform domain for ownership verification and copyright protection.

IEEE TRANSACTIONS ON CONSUMER ELECTRONICS (2023)

Article Computer Science, Artificial Intelligence

Multiround Transfer Learning and Modified Generative Adversarial Network for Lung Cancer Detection

Kwok Tai Chui, Brij B. Gupta, Rutvij H. Jhaveri, Hao Ran Chi, Varsha Arya, Ammar Almomani, Ali Nauman

Summary: This paper proposes a multiround transfer learning and modified generative adversarial network (MTL-MGAN) algorithm for lung cancer detection. The algorithm maximizes transferability through a multiround transfer learning process and avoids negative transfer through customized loss functions. The proposed algorithm significantly improves accuracy compared to related works.

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS (2023)

Editorial Material Computer Science, Artificial Intelligence

IoT-based health monitoring system to handle pandemic diseases using estimated computing

Lidia Ogiela, Arcangelo Castiglione, Brij B. Gupta, Dharma P. Agrawal

NEURAL COMPUTING & APPLICATIONS (2023)

Article Computer Science, Artificial Intelligence

A Deep Learning-based Fast Fake News Detection Model for Cyber-Physical Social Services

Qin Zhang, Zhiwei Guo, Yanyan Zhu, Pandi Vijayakumar, Aniello Castiglione, Brij B. Gupta

Summary: This paper proposes a deep learning-based fast fake news detection model for cyber-physical social services. It takes Chinese text as the objective and adopts characters as the basic processing unit. By using a convolution-based neural computing framework, it extracts feature representation for news texts, ensuring both processing speed and detection ability for Chinese short texts. Experimental results show that this model has lower training time cost and higher classification accuracy than baseline methods.

PATTERN RECOGNITION LETTERS (2023)

Article Business

Unpacking the effect of institutional support on international corporate entrepreneurship in entrepreneurial support systems

Fei Zhou, Xue Li, Chunjia Han, Lan Zhang, Brij B. Gupta

Summary: Based on an empirical analysis of 480 valid questionnaires from the Asia-Pacific region, this study found that entrepreneurial support systems have a positive impact on international corporate entrepreneurship (ICE). It also found that resource slack acts as a mediator between institutional support and ICE, and local and ultra-local network embeddedness moderate the relationship between institutional support and resource slack.

INTERNATIONAL ENTREPRENEURSHIP AND MANAGEMENT JOURNAL (2023)

Article Business

Analysis of the development of sustainable entrepreneurship practices through knowledge and smart innovative based education system

Brij B. Gupta, Akshat Gaurav, Prabin Kumar Panigrahi

Summary: Smart and innovative education is essential for the development of sustainable entrepreneurship practices and aims to teach young people to be responsible members of society and play an active role in shaping the future. However, traditional teaching techniques are insufficient, and the integration of cutting-edge technologies such as IoT, cloud computing, AI, and machine learning is required to achieve a better future.

INTERNATIONAL ENTREPRENEURSHIP AND MANAGEMENT JOURNAL (2023)

Article Business

Exploring thematic influences on theme park visitors' satisfaction: An empirical study on Disneyland China

Shizhen Bai, Hao He, Chunjia Han, Mu Yang, Dingyao Yu, Xinrui Bi, Brij B. B. Gupta, Weijia Fan, Prabin Kumar Panigrahi

Summary: This study examines the impact of thematic influences on theme park visitors' satisfaction using user-generated data. Through the analysis of 112,000 reviews posted by visitors to Shanghai Disney Resort, the study employs structural topic modeling to reveal the dynamics of user-generated data over time. The findings indicate that visitors' satisfaction is closely related to service quality and their overall playing experience, with different emphasis among early and later tourists. Furthermore, the relationship between customer reviews and ratings by tourists becomes less significant over time, suggesting that reviews are better indicators of subjective feelings or experiences. The study contributes to the literature on tourism, service, and consumer behavior, offering practical implications.

JOURNAL OF CONSUMER BEHAVIOUR (2023)

Article Business

Analysis of security and privacy issues of information management of big data in B2B based healthcare systems

Brij B. Gupta, Akshat Gaurav, Prabin Kumar Panigrahi

Summary: The implementation of a system that facilitates safe and efficient data transmission in the healthcare industry could greatly benefit various aspects of healthcare. However, there are challenges in handling the large quantity of data generated by smart devices in B2B-based healthcare systems.

JOURNAL OF BUSINESS RESEARCH (2023)

Article Communication

Analysis of stress, attention, interest, and engagement in onsite and online higher education: A neurotechnological study

David Juarez-Varon, Isabel Bellido-Garcia, Brij-B. Gupta

Summary: The aim of this study is to use neurotechnology to study the effects of onsite and online university education on the learning process. This is an innovative approach in this field. The results show that students who attended classes in person had higher levels of emotional intensity and positive brain activity (attention, interest, and engagement) compared to online students. Online students also showed less interest, attention, and emotional intensity, indicating that distance learning is less effective than classroom learning for a university master's degree class in terms of brain signals.

COMUNICAR (2023)

Article Computer Science, Information Systems

Optimal Strategies Trajectory with Multi-Local-Worlds Graph

Xiang Yu, Chonghua Wang, Xiaojing Zheng, Chaoyu Zeng, Brij B. Gupta

Summary: This paper constructs a non-cooperative/cooperative stochastic differential game model to prove that the optimal strategies trajectory of agents in a system with a topological configuration of a Multi-Local-World graph would converge into a certain attractor if the system's configuration is fixed. It is concluded that the optimal strategy trajectory with a nonlinear operator of cooperative/non-cooperative stochastic differential game between agents can make agents in a certain Local-World coordinate and make the Local-World payment maximize, and can make the all Local-Worlds equilibrated; furthermore, the optimal strategy of the coupled game can converge into a particular attractor that decides the optimal property.

CMC-COMPUTERS MATERIALS & CONTINUA (2023)

Article Computer Science, Information Systems

Age and Gender Classification Using Backpropagation and Bagging Algorithms

Ammar Almomani, Mohammed Alweshah, Waleed Alomoush, Mohammad Alauthman, Aseel Jabai, Anwar Abbass, Ghufran Hamad, Meral Abdalla, Brij B. Gupta

Summary: Voice classification is essential for creating intelligent systems that assist with student exams, criminal identification, and security systems. The research aims to develop a system that can predict and classify gender, age, and accent, resulting in the proposal of a new system called Classifying Voice Gender, Age, and Accent (CVGAA). By incorporating rhythm-based features and using backpropagation and bagging algorithms, the voice recognition system's accuracy is significantly improved, with the Bagging algorithm achieving the highest accuracy of 55.39% in the voice common dataset and 78.94% in speech accent for age classification and accent accuracy.

CMC-COMPUTERS MATERIALS & CONTINUA (2023)

Article Engineering, Civil

Identity-Based Authentication Mechanism for Secure Information Sharing in the Maritime Transport System

Brij Bhooshan Gupta, Akshat Gaurav, Ching-Hsien Hsu, Bo Jiao

Summary: The maritime transportation system is responsible for providing safe transportation in the vast area covered by water. IoT devices are used for continuous monitoring of vessel performance and secure data sharing to protect confidential information. Identity-based encryption is used for authentication management in this scheme.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2023)

暂无数据