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The influence of differential privacy on short term electric load forecasting

Günther Eibl, Kaibin Bao, Philip-William Grassal, Daniel Bernau, Hartmut Schmeck
2018 Energy Informatics  
We illustrate along the use case of privacy preserving load forecasting that Differential Privacy is indeed a valuable addition that unlocks novel information flows for optimization.  ...  There has been a large number of contributions on privacy-preserving smart metering with Differential Privacy, addressing questions from actual enforcement at the smart meter to billing at the energy provider  ...  Differential Privacy Differential Privacy, originally proposed by (Dwork 2006) , is the current gold standard for data privacy.  ... 
doi:10.1186/s42162-018-0025-3 fatcat:5kqzkgtorrdtxnfgr2geb7up3i

The Influence of Differential Privacy on Short Term Electric Load Forecasting [article]

Günther Eibl, Kaibin Bao, Philip-William Grassal, Daniel Bernau, Hartmut Schmeck
2018 arXiv   pre-print
We illustrate along the use case of privacy preserving load forecasting that Differential Privacy is indeed a valuable addition that unlocks novel information flows for optimization.  ...  There has been a large number of contributions on privacy-preserving smart metering with Differential Privacy, addressing questions from actual enforcement at the smart meter to billing at the energy provider  ...  Differential Privacy Differential Privacy, originally proposed by Dwork [8] , is the current gold standard for data privacy.  ... 
arXiv:1807.02361v1 fatcat:kesfj45orrgm5dvbc7gpwsui4y

Differential Privacy for Industrial Internet of Things: Opportunities, Applications and Challenges [article]

Bin Jiang, Jianqiang Li, Guanghui Yue, Houbing Song
2021 arXiv   pre-print
Then we focus on the metrics of industrial data privacy, and analyze the contradiction between data utilization for deep models and individual privacy protection.  ...  In conclusion, this survey is dedicated to complete comprehensive summary and lay foundation for the follow-up researches on industrial differential privacy.  ...  Specially, authors discussed this issue along two directions: data publishing and data analysis on differential privacy.  ... 
arXiv:2101.10569v2 fatcat:xwebjbcvcjhbbaehajhdfjocia

Correlated Data in Differential Privacy: Definition and Analysis [article]

Tao Zhang, Tianqing Zhu, Renping Liu, Wanlei Zhou
2021 arXiv   pre-print
Differential privacy is a rigorous mathematical framework for evaluating and protecting data privacy.  ...  Roughly, we classify existing literature into three lines: 1) using parameters to describe data correlation in differential privacy, 2) using models to describe data correlation in differential privacy  ...  There is no direction for data correlation and can represent cyclic dependencies.  ... 
arXiv:2008.00180v2 fatcat:gkjmzw77fvgy7fx52nqv3wwil4

Analysis of Privacy Protection Methods for DNA Motif Finding

Xiang Wu
2019 American Journal of Biomedical Science & Research  
For instance, in [24] , author proposed a high-utility motif finding algorithm based on -differential privacy.  ...  These can be solved by -differential privacy, which is a powerful method for current applications in the field of DNA motif finding privacy protection.  ... 
doi:10.34297/ajbsr.2019.06.001023 fatcat:25vukuxbxrg7nepl4h5ecrhcwi

Rejoinder: Gaussian Differential Privacy [article]

Jinshuo Dong, Aaron Roth, Weijie J. Su
2021 arXiv   pre-print
Taking a practical viewpoint, we next discuss how f-differential privacy (f-DP) and Gaussian differential privacy (GDP) can make a difference in a range of applications.  ...  First, we discuss some theoretical aspects of our work and comment on how this work might impact the theoretical foundation of privacy-preserving data analysis.  ...  We see all these as interesting future directions for broadening the scope of the hypothesis testing viewpoint on differential privacy.  ... 
arXiv:2104.01987v2 fatcat:qrwqsrtklnbsvcriibay3egrau

Game Analysis of Privacy Protection Based on Nash Equilibrium in Big Data Environment

Yuting Zhang
2021 DEStech Transactions on Materials Science and Engineering  
On the basis of differential privacy knowledge, based on the Nash equilibrium privacy protection mechanism, this paper constructs an interrelated differential privacy model, analyzes and evaluates the  ...  The traditional privacy protection mechanism protects the privacy of users, at the same time, it will inevitably reduce the data utility[1].  ...  Differential privacy of data sets The data record relationship of users can be divided into direct relationship and indirect relationship.  ... 
doi:10.12783/dtmse/ameme2020/35557 fatcat:sppbinzvpzebrk2u6sieaap6dq

A Review of Differential Privacy in Individual Data Release

Jun Wang, Shubo Liu, Yongkai Li
2015 International Journal of Distributed Sensor Networks  
Differential privacy is a relatively new notion of privacy and has become the de facto standard for a security-controlled privacy guarantee.  ...  Finally, shortcomings of existing methods and suggested directions for future research are presented.  ...  Research Direction for Differential Privacy.  ... 
doi:10.1155/2015/259682 fatcat:ieh3v7zgb5gqfnima3wsywcef4

An Advanced Private Social Activity Invitation Framework with Friendship Protection

Weitian Tong, Lei Chen, Scott Buglass, Weinan Gao, Jeffrey Li
2017 Wireless Communications and Mobile Computing  
To the best of our knowledge, it is the first work to publish a directed graph in a differentially private manner with an untrustworthy server.  ...  Our main contributions are (1) defining a novel friendship to reduce the communication/update cost within the social network and enhance the privacy guarantee at the same time; (2) designing a strong privacy-preserving  ...  Injecting noises to different data field with different -differentially private algorithms M 1 , . . . , M , (max{ })-differential privacy will be guaranteed if data fields are independent; otherwise,  ... 
doi:10.1155/2017/1393026 fatcat:4uxruw4curfxfi2p6slbqianv4

Differential Privacy Techniques for Cyber Physical Systems: A Survey [article]

Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen
2019 arXiv   pre-print
Furthermore, we present open issues, challenges, and future research direction for differential privacy techniques for CPSs.  ...  Meanwhile, differential privacy emerged as an efficient technique to protect CPSs data privacy. In this paper, we present a comprehensive survey of differential privacy techniques for CPSs.  ...  • We outline certain open issues, challenges, and possible future research direction for differential privacy based CPSs. C.  ... 
arXiv:1812.02282v3 fatcat:bnapnprldnaetjnjedz473lrme

The Promise of Differential Privacy: A Tutorial on Algorithmic Techniques

Cynthia Dwork
2011 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science  
This rules out direct viewing of raw data.  ...  The tutorial closes with a discussion of directions for future research.  ... 
doi:10.1109/focs.2011.88 dblp:conf/focs/Dwork11 fatcat:kkbwanjiynhkhiajkyxr7e3ym4

Directed Networks with a Differentially Private Bi-degree Sequence

Ting Yan
2021 Statistica sinica  
Although many approaches have been developed for releasing network data with a differential privacy guarantee, inference in many network models with differential privacy data is still unknown or has not  ...  In this paper, we propose to release the bi-degree sequences of directed networks using the Laplace mechanism and make inference in the p0 model, which is an exponential random graph model with the bi-degree  ...  Dwork et al. (2006) developed a rigorous privacy standard-differential privacy for randomized data releasing mechanisms to achieve privacy protection.  ... 
doi:10.5705/ss.202019.0215 fatcat:tcihoy2ugvadraypmqx2bjacdu

Buying private data at auction

Aaron Roth
2012 ACM SIGecom Exchanges  
However, because this is a statistic over sensitive data, individuals experience a cost for participating in the survey as a function of their loss in privacy.  ...  A curious data analyst wishes to survey a population to obtain an accurate estimate of a simple population statistic: for example, the fraction of the population testing positive for syphilis.  ...  DIRECT REVELATION MECHANISMS Armed with a means of quantifying an agent i's loss for allowing his data to be used by an -differentially-private algorithm (c i ( ) = · v i ), we are almost ready to describe  ... 
doi:10.1145/2325713.2325714 fatcat:zknafjsazbhspdzdvyh36umqpm

DP-Cryptography: Marrying Differential Privacy and Cryptography in Emerging Applications [article]

Sameer Wagh, Xi He, Ashwin Machanavajjhala, Prateek Mittal
2020 arXiv   pre-print
There are two popular models for deploying differential privacy - standard differential privacy (SDP), where a trusted server aggregates all the data and runs the DP mechanisms, and local differential  ...  Differential privacy (DP) has arisen as the state-of-the-art metric for quantifying individual privacy when sensitive data are analyzed, and it is starting to see practical deployment in organizations  ...  These lines of work both reflect exciting directions for the computer science community. We begin by giving a brief technical introduction to differential privacy in Section 2.  ... 
arXiv:2004.08887v1 fatcat:xkwpazhrd5gyndl2sbs3pquxni

Differential Privacy in Blockchain Technology: A Futuristic Approach [article]

Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen
2020 arXiv   pre-print
Protecting privacy of blockchain data using data perturbation strategy such as differential privacy could be a novel approach to overcome privacy issues in blockchain.  ...  Blockchain works over peer-to-peer (P2P) phenomenon for its operation and does not require any trusted-third party authorization for data tracking and storage.  ...  . • We highlight current challenges, future directions, and prospective solutions for integration of differential privacy in blockchain.  ... 
arXiv:1910.04316v3 fatcat:u2fdtysuszburar73b5pdd4ezu
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