Privacy preservation in the internet of vehicles using local differential privacy and IOTA ledger

Iftikhar, Zainab; Anjum, Adeel; Khan, Abid; Shah, Munam Ali; Jeon, Gwanggil

doi:10.1007/s10586-023-04002-0

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…One of the most commonly used technology in such approach is the differential privacy where perturbation is designed to limit the statistical information of the sensitive dataset. Such approach can be found, for example in the works in [34][35][36][37].…”

Section: Related Workmentioning

confidence: 99%

Decentralized Data Sharing Using Searchable Encryption Database with Selective Data Retrieval

Gunawan,

Tjuawinata,

Lam

et al. 2023

2023 10th International Conference on ICT for Smart Society (ICISS)

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Secure data sharing platform is an essential component in various elds, including smart cities, AI technologies as well as big data analysis where sensitive data may be owned by a large amount of entities with their own respective privacy concerns. In addition to the privacy issue, data sharing scheme needs to also preserve the data owner's sovereignty where the data owner should always have the ability to decide how the data can be shared. Moreover, in most cases, data sharing may not require the whole dataset to be shared to the requester, which implies that selective retrieval of parts of the data to be shared should also be a feature that can benet the scheme. In this work, we propose a data sharing infrastructure and a scheme following such infrastructure which is constructed based on the recently proposed MongoDB Queryable encryption. In our scheme, we show that privacy and sovereignty can be guaranteed, which addresses all the concerns that we have previously identied.

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Section: Related Workmentioning

confidence: 99%

Decentralized Data Sharing Using Searchable Encryption Database with Selective Data Retrieval

Gunawan,

Tjuawinata,

Lam

et al. 2023

2023 10th International Conference on ICT for Smart Society (ICISS)

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“…AI is mainly used in financial systems to provide appropriate services and schemes to customers. AI reduces error and threats levels in financial security systems (Iftikhar et al, 2023). AI-driven security measures are used in financial systems that maximize trustworthiness and reliability.…”

mentioning

confidence: 99%

An introduction of transaction session‐induced security scheme using blockchain technology: Understanding the features of Internet of Things–based financial security systems

Wen,

Han

2024

Manage Decis Econ

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Internet of Things (IoT)–based financial systems leverage the capabilities of blockchain and artificial intelligence (AI) to enable seamless transactions and data exchange between devices. IoT‐based financial systems involve interconnected devices and services, such as payment terminals, wearables, and smart appliances, which collect, transmit, and process sensitive financial information. The study explores security methods incorporated in the financial systems designed using IoT and blockchain technologies to improve the background features. The study data were gathered from Complaint Data from the Consumer Financial Protection Bureau 2018–2022, and data‐based analysis is used in this study for detecting illegitimate interrupted transactions. Propensity Score Matching (PSM) is used for the robustness and endogeneity test; descriptive statistics is utilized in this study. Financial security systems are introduced to reduce the forging and breaching of intruders amid transactions. This study offers a novel contribution to the field of blockchain technology by furnishing a comprehensive analysis of the features of IoT‐based financial security systems from the perspective of the transaction, broadening the understanding of the feature focusing on financial security, and providing practical recommendations to address the features of IoT‐based financial security systems in blockchain technology. The study highlights how IoT devices can securely record and verify financial transactions by leveraging the blockchain's distributed ledger, preventing tampering or unauthorized access. The results of the study identify that the TS3 program relies on the transaction gaps between financial sessions, security requests between successive transactions, and sessions saved depending on the time delay. The study finds that sessions were analyzed for violations and fraud using information stored on the blockchain. The study suggests the design and building of devices and sensors in an IoT in financial security systems. Transparency should contribute to setting data privacy and safety problems in financial security systems.

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A Local Differential Privacy Preservation Method for High-dimensional Data Based on Big Data Mining

Su,

Hong

2024

2024 International Conference on Intelligent Computing and Data Mining (ICDM)

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Privacy preservation in the internet of vehicles using local differential privacy and IOTA ledger

Cited by 3 publications

References 26 publications

Decentralized Data Sharing Using Searchable Encryption Database with Selective Data Retrieval

Decentralized Data Sharing Using Searchable Encryption Database with Selective Data Retrieval

An introduction of transaction session‐induced security scheme using blockchain technology: Understanding the features of Internet of Things–based financial security systems

A Local Differential Privacy Preservation Method for High-dimensional Data Based on Big Data Mining

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