Topic
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.
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01 May 2007
TL;DR: A privacy-preserving scheme is proposed that enables anonymous estimation of the cardinality of a dynamic set of RFID tags, while allowing the set membership to vary in both the spatial and temporal domains, and can accurately estimate tag populations across many orders of magnitude.
Abstract: The increasing use of RFID tags in many applications have brought forth valid concerns of privacy and anonymity among users. One of the primary concerns with RFID tags is their ability to track an individually tagged entity. While this capability is currently thought to be necessary for supporting some features of RFID systems, such practice can lead to potential privacy violations. In this paper, we propose a privacy-preserving scheme that enables anonymous estimation of the cardinality of a dynamic set of RFID tags, while allowing the set membership to vary in both the spatial and temporal domains. In addition, the proposed scheme can identify the dynamics of the changes in the tag set population. The main idea of the scheme is to avoid explicit identification of tags. We demonstrate that the proposed scheme is highly adaptive and can accurately estimate tag populations across many orders of magnitude, ranging from a few tens to millions of tags. The associated probing latency is also substantially lower (les 10%) than that of the schemes which require explicit tag identification. We also show that our proposed scheme performs well even in highly dynamic environments, where the tag set keeps changing rapidly.
150 citations
TL;DR: Detailed security analysis shows that PPMA can protect individual user's electricity consumption privacy against a strong adversary, and extensive experiments results demonstrate thatPPMA has less computation overhead and no more extra communication and storage costs.
Abstract: Privacy-preserving data aggregation has been extensively studied in smart grid. However, almost all existing schemes aggregate the total electricity consumption data of the whole user set, which sometimes cannot meet the fine-grained demands from control center in smart grid. In this paper, we propose a privacy-preserving multisubset data aggregation scheme, named PPMA, in smart grid. PPMA can aggregate users’ electricity consumption data of different ranges, while guaranteeing the privacy of individual users. Detailed security analysis shows that PPMA can protect individual user's electricity consumption privacy against a strong adversary. In addition, extensive experiments results demonstrate that PPMA has less computation overhead and no more extra communication and storage costs.
149 citations
TL;DR: Survey results that suggest a relationship between two types of user privacy concerns and how users control personal information are discussed are discussed.
Abstract: Users struggle to protect personal information while completing transactions requiring a modicum of trust in today's e-business environment. E-businesses argue that they need personal information t...
149 citations
TL;DR: The findings indicate that during technology-mediated communication on social network sites, not only do traditional privacy factors relate to the technological boundaries people enact, but people's experiences with the mediating technology itself do, too.
149 citations
30 May 2005
TL;DR: In this article, a new algorithm, k-Same-Select, is proposed, which is a formal privacy protection schema based on k-anonymity that provably protects privacy and preserves data utility.
Abstract: With the proliferation of inexpensive video surveillance and face recognition technologies, it is increasingly possible to track and match people as they move through public spaces. To protect the privacy of subjects visible in video sequences, prior research suggests using ad hoc obfuscation methods, such as blurring or pixelation of the face. However, there has been little investigation into how obfuscation influences the usability of images, such as for classification tasks. In this paper, we demonstrate that at high obfuscation levels, ad hoc methods fail to preserve utility for various tasks, whereas at low obfuscation levels, they fail to prevent recognition. To overcome the implied tradeoff between privacy and utility, we introduce a new algorithm, k-Same-Select, which is a formal privacy protection schema based on k-anonymity that provably protects privacy and preserves data utility. We empirically validate our findings through evaluations on the FERET database, a large real world dataset of facial images.
149 citations