A privacy-preserving aggregation scheme based on immunological negative surveys for smart meters

Jiang, Hao; Luo, Wenjian; Zhang, Zhenya

doi:10.1016/j.asoc.2019.105821

Cited by 13 publications

(4 citation statements)

References 24 publications

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“…To preserve the privacy of users' location information when they move, Jiang et al [31] proposed a negative survey-based location information collection method to find the population gathering places. In addition, Jiang et al [32] designed a real-value negative survey model to obtain data on users' electricity consumption.…”

Section: Negative Representation Of Information 221 Negative Surveymentioning

confidence: 99%

“…In addition to the structured data, a new method called NetNS, which is based on negative surveys, was created recently to preserve the topological privacy of social networks without node attributes [33]. In NetNS, the social network (called positive social network) is first divided into several subnetworks (called positive subnetworks) with M nodes.…”

Section: Negative Representation Of Information 221 Negative Surveymentioning

confidence: 99%

“…For the first question, the noise nodes directly participate in the division of social networks. The relationship between it and the other nodes is determined by the steps of disturbing the structure of the subnetwork, where the connection between each pair of nodes in the subnetwork is randomly disturbed by the method based on developed in [33]. Here, it is worth mentioning that if there are isolated nodes, namely the nodes without any edge connected to them, in the disturbed network, the AttNetNRI will disturb the subnetwork again.…”

Section: Steps Of Disturbing Topology Structurementioning

confidence: 99%

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A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

Jiang,

Liao,

Zhao

et al. 2024

CMES

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Due to the presence of a large amount of personal sensitive information in social networks, privacy preservation issues in social networks have attracted the attention of many scholars. Inspired by the self-nonself discrimination paradigm in the biological immune system, the negative representation of information indicates features such as simplicity and efficiency, which is very suitable for preserving social network privacy. Therefore, we suggest a method to preserve the topology privacy and node attribute privacy of attribute social networks, called AttNetNRI. Specifically, a negative survey-based method is developed to disturb the relationship between nodes in the social network so that the topology structure can be kept private. Moreover, a negative database-based method is proposed to hide node attributes, so that the privacy of node attributes can be preserved while supporting the similarity estimation between different node attributes, which is crucial to the analysis of social networks. To evaluate the performance of the AttNetNRI, empirical studies have been conducted on various attribute social networks and compared with several state-of-the-art methods tailored to preserve the privacy of social networks. The experimental results show the superiority of the developed method in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topology disturbing and attribute hiding parts. The experimental results show the superiority of the developed methods in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topological interference and attribute-hiding components.

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Section: Negative Representation Of Information 221 Negative Surveymentioning

confidence: 99%

Section: Negative Representation Of Information 221 Negative Surveymentioning

confidence: 99%

Section: Steps Of Disturbing Topology Structurementioning

confidence: 99%

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A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

Jiang,

Liao,

Zhao

et al. 2024

CMES

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“…Jiang et al [37] propose a protocol based on negative survey. The aggregator divides the valid range into several classes and lets users submit one of these classes in each round.…”

Section: Protocols With Range Validationmentioning

confidence: 99%

Privacy-Preserving Data Aggregation with Probabilistic Range Validation

Erkin

2021

Applied Cryptography and Network Security

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Privacy-preserving data aggregation protocols have been researched widely, but usually cannot guarantee correctness of the aggregate if users are malicious. These protocols can be extended with zero-knowledge proofs and commitments to work in the malicious model, but this incurs a significant computational cost on the end users, making adoption of such protocols less likely.We propose a privacy-preserving data aggregation protocol for calculating the sum of user inputs. Our protocol gives the aggregator confidence that all inputs are within a desired range. Instead of zero-knowledge proofs, our protocol relies on an asynchronous probabilistic hypergraph-based detection algorithm with which the aggregator can quickly pinpoint malicious users. Our protocol is robust to user dropouts and is non-interactive apart from the registration phase. We describe several optional extensions to our protocol for temporal aggregation, dynamic user joins and leaves, and differential privacy. We analyse our protocol in terms of security, privacy, and detection rate. Finally, we compare the runtime complexity of our protocol with a selection of related protocols.iii Preface This thesis describes my alternative solution to detecting malicious users in a privacy-preserving data aggregation protocol. My decision to dive into this field of research came after following the Privacy-Enhancing Technologies course by dr. ir. Erkin-who would later supervise this very thesis-and being inspired by the almost-magical properties of homomorphic encryption and oblivious transfer, amongst others. During my thesis, I first read up on privacy-preserving data aggregation for three months. Then, I decided to research the issue of detecting malicious users because the solutions I found were more like workarounds than proper solutions. So, I came up with my own solution, and then spent four months investigating my own solution to find out if it was any good. Luckily for me, it was, so I spent the final three months writing my thesis. Meanwhile, I wrote a paper about my solution, the second attempt of which is yet to be reviewed. All in all, this thesis is the culmination of 310 days of work, an estimated 1.063% of my entire life until my projected death. It is the crowning jewel on my 1846 days (6.189%) as a computer science student at TU Delft, and while it is neither perfect nor exhaustive, it is something I am proud of.I thank Zekeriya Erkin especially for keeping me engaged and motivated, particularly during my time in isolation because of some sort of worldwide pandemic; working from home does not suit me in the least. I thank Oguzhan Ersoy for his mathematical and cryptographic help during both the design and the analysis of my solution. I thank Dion Gijswijt for his mathematical insights, even though I was too late to process them into this work. Finally, I thank my family, girlfriend, friends, and colleagues for their patience on the occasions when I prioritised my thesis over them.

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A Review on Security and Privacy Issues in Smart Metering Infrastructure and Their Solutions in Perspective of Distribution Utilities

Yadav

Kumar

2022

Lecture Notes in Electrical Engineering

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A privacy-preserving aggregation scheme based on immunological negative surveys for smart meters

Cited by 13 publications

References 24 publications

A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

Privacy-Preserving Data Aggregation with Probabilistic Range Validation

A Review on Security and Privacy Issues in Smart Metering Infrastructure and Their Solutions in Perspective of Distribution Utilities

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