4.6 Article

Privacy-Preserving Collaborative Sharing for Sharing Economy in Fog-Enhanced IoT

Related references

Note: Only part of the references are listed.
Article Computer Science, Information Systems

Toward Trustworthy AI: Blockchain-Based Architecture Design for Accountability and Fairness of Federated Learning Systems

Sin Kit Lo et al.

Summary: Federated learning is a privacy-preserving AI technique that involves training models locally and aggregating them without transferring data externally. However, accountability and fairness are major challenges in federated learning systems due to stakeholder involvement and data distribution heterogeneity. To address these challenges, a blockchain-based architecture is proposed, incorporating a smart contract-based registry for accountability and a fair data sampler algorithm. Evaluation using a COVID-19 X-ray detection use case demonstrates the feasibility of this approach, with improved model performance compared to default federated learning settings.

IEEE INTERNET OF THINGS JOURNAL (2023)

Article Engineering, Electrical & Electronic

Practical Privacy-Preserving Federated Learning in Vehicular Fog Computing

Yiran Li et al.

Summary: This article presents a framework called GALAXY, the first of its kind in the regime of privacy-preserving FL under the setting of non-cloud-assisted fog computing. Based on the secure multi-party computation technology, the framework boasts high scalability, processing efficiency, and low resource overhead.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2022)

Article Computer Science, Hardware & Architecture

SCALABLE ON-CHAIN AND OFF-CHAIN BLOCKCHAIN FOR SHARING ECONOMY IN LARGE-SCALE WIRELESS NETWORKS

Ting Cai et al.

Summary: This study proposes a real-time and reliable sharing framework with fine-grained transaction support based on blockchain technology, using a two-layer scaling blockchain design. In the on-chain layer, sharing-oriented sharding is employed for secure and efficient processing of macro-transactions. In the off-chain layer, cross-zone off-chain channels are set up to enable real-time sharing transactions with high-frequency micro-trading scenarios.

IEEE WIRELESS COMMUNICATIONS (2022)

Article Computer Science, Information Systems

Secure Hot Path Crowdsourcing With Local Differential Privacy Under Fog Computing Architecture

Mengmeng Yang et al.

Summary: This article discusses the crowdsourcing problem in data collection for the Internet of Things (IoT) and proposes a trie-based iterative statistic method that combines additive secret sharing and local differential privacy technologies to protect the location information of workers. The effectiveness of the proposed method is theoretically analyzed and extensively experimented, demonstrating its ability to provide strict privacy guarantee while improving performance.

IEEE TRANSACTIONS ON SERVICES COMPUTING (2022)

Article Computer Science, Hardware & Architecture

Enabling Privacy-Preserving Geographic Range Query in Fog-Enhanced IoT Services

Yu Guo et al.

Summary: This article presents a geographic range-match scheme for fog-enhanced services that securely collects sensed data while protecting the location privacy of IoT devices. By formulating the problem as range-based pattern matching and designing security schemes in the ciphertext domain, efficient range queries can be performed with reduced accessible information.

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING (2022)

Proceedings Paper Computer Science, Hardware & Architecture

Multi-Party Computation in IoT for Privacy-Preservation

Himanshu Goyal et al.

Summary: Privacy preservation is a major concern in the increasing use of IoT-assisted smart systems. Existing strategies for privacy-preserving data aggregation are not suitable for resource-constrained IoT systems. In this research, we propose a strategy based on concurrent-transmission and multi-party computation to efficiently preserve privacy in real-world IoT systems.

2022 IEEE 42ND INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2022) (2022)

Article Computer Science, Information Systems

Cloud-Based Privacy-Preserving Collaborative Consumption for Sharing Economy

Lingjuan Lyu et al.

Summary: This study proposes a novel cloud-based privacy-preserving solution to support collaborative consumption applications in the sharing economy. By utilizing the homomorphic Paillier cryptosystem, the cloud-based operator can only obtain aggregate data without tracking individual users' private information.

IEEE TRANSACTIONS ON CLOUD COMPUTING (2022)

Article Computer Science, Information Systems

Bias and Unfairness of Collaborative Filtering Based Recommender Systems in MovieLens Dataset

Alvaro Gonzalez et al.

Summary: Recommender Systems, an essential tool in streaming and marketplace systems, have been found to exhibit clear bias and unfairness towards minorities and underrepresented groups. This paper analyzes the demographic characteristics of a gold standard dataset and proposes Soft Matrix Factorization (SoftMF) to balance predictions and reduce existing inequality.

IEEE ACCESS (2022)

Review Business

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Mohammad Fakhar Manesh et al.

Summary: Modern organizations rely on knowledge management to sustain long-term competitive advantage, especially in the era of Industry 4.0. Studying the intellectual structure and trends of knowledge management in this context can help identify future research directions and meaningful advances in managerial knowledge of Industry 4.0.

IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT (2021)

Article Computer Science, Information Systems

Using Reduced Paths to Achieve Efficient Privacy-Preserving Range Query in Fog-Based IoT

Hassan Mahdikhani et al.

Summary: The article proposes a new efficient and privacy-preserving range query scheme in fog-based IoT, utilizing decomposition technique and symmetric homomorphic encryption for privacy protection and improved query efficiency. Security analysis shows the scheme is privacy preserving, and performance evaluations demonstrate its higher efficiency compared to previous schemes in terms of computational overhead and communication complexity.

IEEE INTERNET OF THINGS JOURNAL (2021)

Article Computer Science, Information Systems

Privacy-Preserving Location-Based Data Queries in Fog-Enhanced Sensor Networks

Hongcheng Xie et al.

Summary: This article presents a privacy-preserving-location-based data query scheme in fog-enhanced sensor networks by utilizing somewhat homomorphic encryption technology to protect user privacy while allowing cloud and fog devices to collect sensor data from specific areas. It implements a secure and efficient matched data extraction scheme and system prototype, and evaluates it in the software guard extension environment.

IEEE INTERNET OF THINGS JOURNAL (2021)

Article Computer Science, Hardware & Architecture

Efficient and Privacy-Preserving Ridesharing Organization for Transferable and Non-Transferable Services

Mahmoud Nabil et al.

Summary: Ridesharing is a way for multiple individuals to share one vehicle for trips, reducing vehicle numbers, air pollution, and traffic congestion. Existing ridesharing organization schemes lack flexibility, scalability, and raise privacy concerns. This paper proposes two privacy-preserving ridesharing organization schemes, suitable for non-transferable and transferable services, respectively.

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING (2021)

Article Engineering, Electrical & Electronic

Enabling Efficient and Privacy-Preserving Aggregation Communication and Function Query for Fog Computing-Based Smart Grid

Jia-Nan Liu et al.

IEEE TRANSACTIONS ON SMART GRID (2020)

Article Engineering, Electrical & Electronic

Privacy-Preserved Data Sharing Towards Multiple Parties in Industrial IoTs

Xu Zheng et al.

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2020)

Article Computer Science, Information Systems

An Efficient, Accountable, and Privacy-Preserving Access Control Scheme for Internet of Things in a Sharing Economy Environment

Yu Liu et al.

IEEE INTERNET OF THINGS JOURNAL (2020)

Article Computer Science, Artificial Intelligence

A Secure Federated Transfer Learning Framework

Yang Liu et al.

IEEE INTELLIGENT SYSTEMS (2020)

Proceedings Paper Computer Science, Hardware & Architecture

Privacy Preserving Data Aggregation in Fog Computing using Homomorphic Encryption: An Analysis

R. Sendhil et al.

2020 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI - 2020) (2020)

Article Computer Science, Information Systems

Differential Privacy Techniques for Cyber Physical Systems: A Survey

Muneeb Ul Hassan et al.

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2020)

Article Computer Science, Theory & Methods

Federated Learning With Differential Privacy: Algorithms and Performance Analysis

Kang Wei et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2020)

Article Computer Science, Information Systems

Swarm Economy: A Model for Transactions in a Distributed and Organic IoT Platform

Laisa Caroline Costa De Biase et al.

IEEE INTERNET OF THINGS JOURNAL (2019)

Article Computer Science, Information Systems

A New Communication-Efficient Privacy-Preserving Range Query Scheme in Fog-Enhanced IoT

Rongxing Lu

IEEE INTERNET OF THINGS JOURNAL (2019)

Article Computer Science, Information Systems

Blockchain and IoT-Based Cognitive Edge Framework for Sharing Economy Services in a Smart City

Md Abdur Rahman et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

An Efficient Fog as-a-Power-Economy-Sharing Service

Rasool Bukhsh et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

Achieving Privacy-Preserving Subset Aggregation in Fog-Enhanced IoT

Hassan Mahdikhani et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

Privacy Ensured e-Healthcare for Fog-Enhanced IoT Based Applications

Rahul Saha et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

Demystifying IoT Security: An Exhaustive Survey on IoT Vulnerabilities and a First Empirical Look on Internet-Scale IoT Exploitations

Nataliia Neshenko et al.

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2019)

Article Computer Science, Information Systems

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges

Carla Mouradian et al.

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2018)

Article Automation & Control Systems

PPFA: Privacy Preserving Fog-Enabled Aggregation in Smart Grid

Lingjuan Lyu et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2018)

Article Computer Science, Information Systems

A Privacy-Preserving Fog Computing Framework for Vehicular Crowdsensing Networks

Jiannan Wei et al.

IEEE ACCESS (2018)

Article Computer Science, Information Systems

A Lightweight Privacy-Preserving Data Aggregation Scheme for Fog Computing-Enhanced IoT

Rongxing Lu et al.

IEEE ACCESS (2017)

Article Computer Science, Information Systems

A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications

Jie Lin et al.

IEEE INTERNET OF THINGS JOURNAL (2017)