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Information privacy

About: Information privacy is a research topic. Over the lifetime, 25412 publications have been published within this topic receiving 579611 citations. The topic is also known as: data privacy & data protection.


Papers
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Journal ArticleDOI
TL;DR: It is shown that the staircase mechanism is the optimal noise adding mechanism in a universal context, subject to a conjectured technical lemma, and also proves to be true for one and two dimensional data.
Abstract: Adding Laplacian noise is a standard approach in differential privacy to sanitize numerical data before releasing it In this paper, we propose an alternative noise adding mechanism: the staircase mechanism, which is a geometric mixture of uniform random variables The staircase mechanism can replace the Laplace mechanism in each instance in the literature and for the same level of differential privacy, the performance in each instance improves; the improvement is particularly stark in medium-low privacy regimes We show that the staircase mechanism is the optimal noise adding mechanism in a universal context, subject to a conjectured technical lemma (which we also prove to be true for one and two dimensional data)

133 citations

Journal ArticleDOI
TL;DR: This paper proposes a secure data storage and sharing method consisted of a selective encryption algorithm combined with fragmentation and dispersion to protect the data safety and privacy even when both transmission media and keys are compromised.
Abstract: The recent spades of cyber attacks have compromised end-users’ data security and privacy in Medical Cyber-Physical Systems (MCPS) in the era of Health 4.0. Traditional standard encryption algorithms for data protection are designed based on a viewpoint of system architecture rather than a viewpoint of end-users. As such encryption algorithms are transferring the protection on the data to the protection on the keys, data safety, and privacy will be compromised once the key is exposed. In this paper, we propose a secure data storage and sharing method consisted of a selective encryption algorithm combined with fragmentation and dispersion to protect the data safety and privacy even when both transmission media (e.g. cloud servers) and keys are compromised. This method is based on a user-centric design that protects the data on a trusted device such as the end-users’ smartphone and lets the end-user control the access for data sharing. We also evaluate the performance of the algorithm on a smartphone platform to prove efficiency.

133 citations

Journal ArticleDOI
TL;DR: The security analysis and evaluation of the scheme indicate that the protocol can effectively prevent the risk of medical privacy data being easily leaked and ensures security privacy of the collected data via secure authentication.
Abstract: Traditional medical privacy data are at a serious risk of disclosure, and many related cases have occurred over the years. For example, personal medical privacy data can be easily leaked to insurance companies, which not only compromises the privacy of individuals, but also hinders the healthy development of the medical industry. With the continuous improvement of cloud computing and big data technologies, the Internet of Things technology has been rapidly developed. Radio frequency identification (RFID) is one of the core technologies of the Internet of Things. The application of the RFID system to the medical system can effectively solve this problem of medical privacy. RFID tags in the system can collect useful information and conduct data exchange and processing with a back-end server through the reader. The whole process of information interaction is mainly in the form of ciphertext. In the context of the Internet of Things, the paper presents a lightweight RFID medical privacy protection scheme. The scheme ensures security privacy of the collected data via secure authentication. The security analysis and evaluation of the scheme indicate that the protocol can effectively prevent the risk of medical privacy data being easily leaked.

133 citations

Journal ArticleDOI
TL;DR: This paper proposes a new architecture for data synchronization based on fog computing, and designs a differential synchronization algorithm that has better performance than traditional cloud-based solutions in terms of both efficiency and security.
Abstract: With the development of Internet of Things (IoT) technologies, increasingly many devices are connected, and large amounts of data are produced. By offloading the computing-intensive tasks to the edge devices, cloud-based storage technology has become the mainstream. However, if the end IoT devices send all of their data to the cloud, then data privacy becomes a great issue. In this paper, we propose a new architecture for data synchronization based on fog computing. By offloading part of computing and storage work to the fog servers, the data privacy can be guaranteed. Moreover, to decrease the communication cost and reduce the latency, we design a differential synchronization algorithm. Furthermore, we extend the method by introducing Reed–Solomon code for security consideration. We prove that our architecture and algorithm really have better performance than traditional cloud-based solutions in terms of both efficiency and security through a series of experiments.

133 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023562
20221,226
20211,535
20201,634
20191,255
20181,277