scholarly journals Trajectory as an Identity: Privacy-Preserving and Sybil-Resistant Authentication for Internet of Vehicles

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jiangtao Li ◽  
Zhaoheng Song ◽  
Yufeng Li ◽  
Chenhong Cao ◽  
Yuanhang He
Keyword(s):  
Privacy Preserving ◽  
Cloud Services ◽  
Security And Privacy ◽  
Sybil Attack ◽  
Internet Of Vehicles ◽  
Main Challenge ◽  
Group Signatures ◽  
5G Network ◽  
Identity Privacy ◽  
Authentication Schemes

With the advancement of the 5G network, the Internet of Vehicles (IoV) is becoming more and more attractive for academic researchers and industrial. A main challenge of IoV is to guarantee the authenticity of messages and protect drivers’ privacy simultaneously. The majority of privacy-preserving authentication schemes for IoV adopt pseudonyms or group signatures to achieve a balance between security and privacy. However, defending the Sybil attacks in these schemes is challenging. In this work, we propose a novel privacy-preserving authentication scheme for announcement messages, which utilizes the trajectories of vehicles as their identities. When an authenticated message is verified, the verifier is convinced that the message is generated by a vehicle that has a unique masked trajectory. Meanwhile, the real trajectories of vehicles are kept private. In particular, our scheme achieves Sybil attack resistance without the limitation of trajectory length even when the attacker is allowed to use cloud services.

scholarly journals A Blockchain-Based Efficient, Secure and Anonymous Conditional Privacy-Preserving and Authentication Scheme for the Internet of Vehicles

2022 ◽  
Vol 12 (1) ◽  
pp. 476
Author(s):  
Kashif Naseer Qureshi ◽  
Luqman Shahzad ◽  
Abdelzahir Abdelmaboud ◽  
Taiseer Abdalla Elfadil Eisa ◽  
Bandar Alamri ◽  
...  
Keyword(s):  
Selection Process ◽  
Data Communication ◽  
Privacy Preserving ◽  
Consensus Algorithm ◽  
Security And Privacy ◽  
The Internet ◽  
Malicious Nodes ◽  
Internet Of Vehicles ◽  
Smart Vehicles ◽  
Authentication Mechanism

The rapid advancement in the area of the Internet of Vehicles (IoV) has provided numerous comforts to users due to its capability to support vehicles with wireless data communication. The exchange of information among vehicle nodes is critical due to the rapid and changing topologies, high mobility of nodes, and unpredictable network conditions. Finding a single trusted entity to store and distribute messages among vehicle nodes is also a challenging task. IoV is exposed to various security and privacy threats such as hijacking and unauthorized location tracking of smart vehicles. Traceability is an increasingly important aspect of vehicular communication to detect and penalize malicious nodes. Moreover, achieving both privacy and traceability can also be a challenging task. To address these challenges, this paper presents a blockchain-based efficient, secure, and anonymous conditional privacy-preserving and authentication mechanism for IoV networks. This solution is based on blockchain to allow vehicle nodes with mechanisms to become anonymous and take control of their data during the data communication and voting process. The proposed secure scheme provides conditional privacy to the users and the vehicles. To ensure anonymity, traceability, and unlinkability of data sharing among vehicles, we utilize Hyperledger Fabric to establish the blockchain. The proposed scheme fulfills the requirement to analyze different algorithms and schemes which are adopted for blockchain technology for a decentralized, secure, efficient, private, and traceable system. The proposed scheme examines and evaluates different consensus algorithms used in the blockchain and anonymization techniques to preserve privacy. This study also proposes a reputation-based voting system for Hyperledger Fabric to ensure a secure and reliable leader selection process in its consensus algorithm. The proposed scheme is evaluated with the existing state-of-the-art schemes and achieves better results.

scholarly journals Secure Cloud based Privacy Preserving DataMinning Platform

2017 ◽  
Vol 7 (3) ◽  
pp. 830 ◽  
Author(s):  
S Kumaraswamy ◽  
Manjula S H ◽  
K R Venugopal
Keyword(s):  
Public Key Cryptography ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Privacy Concern ◽  
Cloud Platform ◽  
Computation Complexity ◽  
Group Signatures ◽  
User Data ◽  
Significant Performance ◽  
Area Of Concern

The adoption of cloud environment for various application uses has led to security and privacy concern of user’s data. To protect user data and privacy on such platform is an area of concern. Many cryptography strategy has been presented to provide secure sharing of resource on cloud platform.  These methods tries to achieve a secure authentication strategy to realize feature such as self-blindable access tickets, group signatures, anonymous access tickets, minimal disclosure of tickets and revocation but each one varies in realization of these features. Each feature requires different cryptography mechanism for realization. Due to this it induces computation complexity which affects the deployment of these models in practical application. Most of these techniques are designed for a particular application environment and adopt public key cryptography which incurs high cost due to computation complexity. To address these issues this work present an secure and efficient privacy preserving of mining data on public cloud platform by adopting party and key based authentication strategy. The proposed SCPPDM (Secure Cloud Privacy Preserving Data Mining) is deployed on Microsoft azure cloud platform. Experiment is conducted to evaluate computation complexity. The outcome shows the proposed model achieves significant performance interm of computation overhead and cost.

scholarly journals Security and Privacy Requirements for Electronic Consent

2021 ◽  
Vol 20 (2) ◽  
pp. 1-24
Author(s):  
Stef Verreydt ◽  
Koen Yskout ◽  
Wouter Joosen
Keyword(s):  
Security And Privacy ◽  
Inclusion Criteria ◽  
Comprehensive Overview ◽  
Privacy And Security ◽  
Pubmed Central ◽  
Privacy Requirements ◽  
Development Lifecycle ◽  
Main Challenge ◽  
Security Challenges ◽  
Server Systems

Electronic consent (e-consent) has the potential to solve many paper-based consent approaches. Existing approaches, however, face challenges regarding privacy and security. This literature review aims to provide an overview of privacy and security challenges and requirements proposed by papers discussing e-consent implementations, as well as the manner in which state-of-the-art solutions address them. We conducted a systematic literature search using ACM Digital Library, IEEE Xplore, and PubMed Central. We included papers providing comprehensive discussions of one or more technical aspects of e-consent systems. Thirty-one papers met our inclusion criteria. Two distinct topics were identified, the first being discussions of e-consent representations and the second being implementations of e-consent in data sharing systems. The main challenge for e-consent representations is gathering the requirements for a “valid” consent. For the implementation papers, many provided some requirements but none provided a comprehensive overview. Blockchain is identified as a solution to transparency and trust issues in traditional client-server systems, but several challenges hinder it from being applied in practice. E-consent has the potential to grant data subjects control over their data. However, there is no agreed-upon set of security and privacy requirements that must be addressed by an e-consent platform. Therefore, security- and privacy-by-design techniques should be an essential part of the development lifecycle for such a platform.

scholarly journals Attribute-based pseudonymity for privacy-preserving authentication in cloud services

2021 ◽  
pp. 1-1
Author(s):  
Victor Sucasas ◽  
Georgios Mantas ◽  
Maria Papaioannou ◽  
Jonathan Rodriguez
Keyword(s):  
Privacy Preserving ◽  
Cloud Services

scholarly journals A Self-Powered PMFC-Based Wireless Sensor Node for Smart City Applications

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Daniel Ayala-Ruiz ◽  
Alejandro Castillo Atoche ◽  
Erica Ruiz-Ibarra ◽  
Edith Osorio de la Rosa ◽  
Javier Vázquez Castillo
Keyword(s):  
Energy Harvesting ◽  
Low Power ◽  
Sensor Node ◽  
Smart Cities ◽  
Cloud Services ◽  
Environmental Data ◽  
Security And Privacy ◽  
Wireless Sensor ◽  
Ultra Low Power ◽  
Self Powered

Long power wide area networks (LPWAN) systems play an important role in monitoring environmental conditions for smart cities applications. With the development of Internet of Things (IoT), wireless sensor networks (WSN), and energy harvesting devices, ultra-low power sensor nodes (SNs) are able to collect and monitor the information for environmental protection, urban planning, and risk prevention. This paper presents a WSN of self-powered IoT SNs energetically autonomous using Plant Microbial Fuel Cells (PMFCs). An energy harvesting device has been adapted with the PMFC to enable a batteryless operation of the SN providing power supply to the sensor network. The low-power communication feature of the SN network is used to monitor the environmental data with a dynamic power management strategy successfully designed for the PMFC-based LoRa sensor node. Environmental data of ozone (O3) and carbon dioxide (CO2) are monitored in real time through a web application providing IoT cloud services with security and privacy protocols.

scholarly journals Privacy-preserving security solution for cloud services

2015 ◽  
Vol 13 (1) ◽  
pp. 20-31 ◽  
Author(s):  
L. Malina ◽  
J. Hajny ◽  
P. Dzurenda ◽  
V. Zeman
Keyword(s):  
Privacy Preserving ◽  
Cloud Services

scholarly journals MACHINE LEARNING APPROACH FOR CRYPTOSYSTEM SUGGEST IN EDUCARE OVER CLOUDS

2021 ◽  
Vol 9 (6) ◽  
pp. 98-103
Author(s):  
Ravish G K ◽  
Thippeswamy K
Keyword(s):  
Machine Learning ◽  
Research Work ◽  
Cloud Services ◽  
Learning System ◽  
Security And Privacy ◽  
Great Promise ◽  
Sensitive Information ◽  
Online Systems ◽  
Machine Learning Approach ◽  
Time Requirements

In the current situation of the pandemic, global organizations are turning to online functionality to ensure survival and sustainability. The future, even though uncertain, holds great promise for the education system being online. Cloud services for education are the center of this research work as they require security and privacy. The sensitive information about the users and the institutions need to be protected from all interested third parties. since the data delivery on any of the online systems is always time sensitive, the have to be fast. In previous works some of the algorithms were explored and statistical inference based decision was presented. In this work a machine learning system is designed to make that decision based on data type and time requirements.

scholarly journals A New Secure Model for Data Protection over Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Amr M. Sauber ◽  
Passent M. El-Kafrawy ◽  
Amr F. Shawish ◽  
Mohamed A. Amin ◽  
Ismail M. Hagag
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Protection ◽  
Cloud Services ◽  
Security And Privacy ◽  
Storage Model ◽  
Cloud Data ◽  
Security Issues ◽  
Data Owner ◽  
Proposed Model

The main goal of any data storage model on the cloud is accessing data in an easy way without risking its security. A security consideration is a major aspect in any cloud data storage model to provide safety and efficiency. In this paper, we propose a secure data protection model over the cloud. The proposed model presents a solution to some security issues of cloud such as data protection from any violations and protection from a fake authorized identity user, which adversely affects the security of the cloud. This paper includes multiple issues and challenges with cloud computing that impairs security and privacy of data. It presents the threats and attacks that affect data residing in the cloud. Our proposed model provides the benefits and effectiveness of security in cloud computing such as enhancement of the encryption of data in the cloud. It provides security and scalability of data sharing for users on the cloud computing. Our model achieves the security functions over cloud computing such as identification and authentication, authorization, and encryption. Also, this model protects the system from any fake data owner who enters malicious information that may destroy the main goal of cloud services. We develop the one-time password (OTP) as a logging technique and uploading technique to protect users and data owners from any fake unauthorized access to the cloud. We implement our model using a simulation of the model called Next Generation Secure Cloud Server (NG-Cloud). These results increase the security protection techniques for end user and data owner from fake user and fake data owner in the cloud.

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