Review
Computer Science, Information Systems
Alfredo J. Perez, Sherali Zeadally
Summary: The development of Blockchain and smart contracts enables the automation of commerce in crowdsensing systems. However, security and privacy issues need to be addressed.
COMPUTER SCIENCE REVIEW
(2022)
Review
Computer Science, Hardware & Architecture
Jong Wook Kim, Kennedy Edemacu, Beakcheol Jang
Summary: This research comprehensively surveys the state-of-the-art mechanisms for protecting the location privacy of workers in mobile crowdsensing (MCS), one of the most successful applications of crowdsourcing. The authors categorize the location protection mechanisms into three categories and compare them based on architecture, privacy, computational overhead, and utility. The study also discusses promising future research directions in this area.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
Luca Bedogni, Federico Montori
Summary: Mobile Crowdsensing (MCS) is a paradigm where participants, called workers, use their personal devices to gather sensor data. Privacy preservation is crucial for single workers, and in this paper, we propose a privacy by design MCS framework that uses variable rewards to ensure privacy while incentivizing the submission of location data. We evaluate the framework using a metric based on k-anonymity and validate it with a real dataset, showing its effectiveness and the impact of environmental topology.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Xingfu Yan, Wing W. Y. Ng, Biao Zeng, Changlu Lin, Yuxian Liu, Lu Lu, Ying Gao
Summary: FA-MCS addresses challenges in traditional MCS model, but data aggregation may threaten privacy and correctness. Untrusted servers and FNs could compromise accuracy, and bad FNs may endanger reliability. Proposed scheme protects privacy, verifies correctness, and tolerates bad nodes.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Weizheng Wang, Yaoqi Yang, Zhimeng Yin, Kapal Dev, Xiaokang Zhou, Xingwang Li, Nawab Muhammad Faseeh Qureshi, Chunhua Su
Summary: Mobile crowdsensing (MCS) is an important approach that utilizes idle resources of portable devices to accomplish sensing tasks. Traditional MCS has security issues due to its reliance on centralized servers, and blockchain-based MCS systems have been proposed to address this. In this study, a secure, interactive, and fair blockchain-based MCS system called BSIF is proposed by integrating smart contracts and mobile devices. BSIF ensures the legitimacy and privacy of participants through identity verification and location privacy protection methods. The evaluation process is transferred to the requester side to reduce computation cost, and the Stackelberg game is used to achieve a dynamic balance between worker participation and requester rewards.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2022)
Article
Computer Science, Theory & Methods
Ankit Agrawal, Sarthak Choudhary, Ashutosh Bhatia, Kamlesh Tiwari
Summary: This paper proposes a privacy-preserving publish-subscribe-based decentralized framework for MCS systems named Pub-SubMCS. The framework allows data sharing and handles the curse of sensing issues by performing access control using smart contracts. It also ensures data privacy and validation over blockchain through data transformation and comparison measures. The implementation on the Ethereum blockchain shows the scalability, usability, and feasibility of the proposed system, and the effectiveness of the publish-subscribe model.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Computer Science, Information Systems
Mariem Brahem, Guillaume Scerri, Nicolas Anciaux, Valerie Issarny
Summary: Privacy preservation in mobile crowdsensing systems is a major challenge, with current approaches not adequately taking into account users' tolerance for data usage.
PERVASIVE AND MOBILE COMPUTING
(2022)
Article
Computer Science, Information Systems
Min Choi, Abir EL Azzaoui, Sushil Kumar Singh, Mikail Mohammed Salim, Sekione Reward Jeremiah, Jong Hyuk Park
Summary: The term "Metaverse" has gained significant attention in both industry and academia. This paper provides a comprehensive survey on current metaverse projects worldwide, highlighting the security issues associated with them and presenting recent solutions and technologies to enhance the metaverse experience and security.
HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Zhetao Li, Zhirun Zheng, Suiming Guo, Bin Guo, Fu Xiao, Kui Ren
Summary: Although crowdsensing has become popular, its security and privacy vulnerabilities are a concern. Previous research has often considered security and privacy separately, raising doubts about the impact of privacy defense methods on security. To address this, we propose DDPA, a disguise-based data poisoning attack against differentially private crowdsensing systems. We introduce a stealth strategy to evade truth discovery methods and show that enhancing privacy can increase security threats. Evaluation on real and synthetic datasets demonstrates that DDPA achieves maximum utility damage without being detected.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Review
Computer Science, Information Systems
Zhang Wenhua, Faizan Qamar, Taj-Aldeen Naser Abdali, Rosilah Hassan, Syed Talib Abbas Jafri, Quang Ngoc Nguyen
Summary: Blockchain technology provides inherent security properties through cryptography, decentralization, and consensus, ensuring trust in transactions. It has wide-ranging applications, particularly in medical health data security and privacy protection. However, security issues are becoming increasingly apparent with the development of this technology.
Article
Automation & Control Systems
Xuewen Dong, Wen Zhang, Yushu Zhang, Zhichao You, Sheng Gao, Yulong Shen, Chao Wang
Summary: This article discusses the privacy protection of task locations in mobile crowdsensing and proposes a codebook-based task allocation mechanism to address the issue of task location privacy leakage. By considering the tradeoff between local privacy and system utility, the optimal task allocation scheme is derived. Experimental results show that the introduction of the selected allocation codebook (SAC) method can improve task location privacy protection by an average of 60%.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Xuelian Cai, Lingling Zhou, Fan Li, Yuchuan Fu, Pincan Zhao, Changle Li, F. Richard Yu
Summary: This article proposes a security protection incentive mechanism with data quality assurance (SPIM-DQA) for the vehicular crowdsensing (VCS) system. It adopts a blockchain-enabled framework and smart contracts to address the contradiction between personal interests and user data security in the traditional incentive mechanism. The proposed mechanism evaluates the quality of provided data to update user reputation and incentivizes users to consistently provide high-quality data.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Bhabendu Kumar Mohanta, Debasish Jena, Somula Ramasubbareddy, Mahmoud Daneshmand, Amir H. Gandomi
Summary: The rapid growth of IoT technology presents security and privacy challenges, but blockchain technology offers some solutions. By integrating IoT and blockchain technologies, a more secure smart IoT system can be achieved.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Ankur Gupta, Habib Ullah Khan, Shah Nazir, Muhammad Shafiq, Mohammad Shabaz
Summary: The metaverse promises immersive experiences, but privacy, security, and control issues must be resolved. This paper focuses on the security issues and enabling technologies/platforms in the metaverse. It also addresses the challenges faced by developers, service providers, and stakeholders, which, if ignored, could hinder adoption and appeal. Finally, ideas for building a viable Zero-Trust Architecture model for the metaverse are presented.
Article
Computer Science, Theory & Methods
Chuan Zhang, Mingyang Zhao, Liehuang Zhu, Tong Wu, Ximeng Liu
Summary: In this paper, we propose an efficient and strong privacy-preserving truth discovery scheme, named EPTD, to protect users' task privacy and data privacy simultaneously in the truth discovery procedure.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2022)
