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Connecting Robust Shuffle Privacy and Pan-Privacy [article]

Victor Balcer, Albert Cheu, Matthew Joseph, Jieming Mao
2020 arXiv   pre-print
Focusing on the dependence on the domain size k, we find that robust approximate shuffle privacy and approximate pan-privacy have additive error Θ(√(k)) for counting distinct elements.  ...  Finally, we show that this connection is useful in both directions: we give a pan-private adaptation of recent work on shuffle private histograms and use it to recover further separations between pan-privacy  ...  Acknowledgments We thank Clément Canonne for simplifying the form of the uniformity testing lower bound and Adam Smith for useful discussions regarding the pan-privacy definition.  ... 
arXiv:2004.09481v4 fatcat:wiwpkpu32fgpzgfweqw65aez6e

Uniformity Testing in the Shuffle Model: Simpler, Better, Faster [article]

Clément L. Canonne, Hongyi Lyu
2021 arXiv   pre-print
central differential privacy (DP), local privacy (LDP), pan-privacy, and, very recently, the shuffle model of differential privacy.  ...  In this work, we considerably simplify the analysis of the known uniformity testing algorithm in the shuffle model, and, using a recent result on "privacy amplification via shuffling," provide an alternative  ...  Building on a connection between robust shuffle private algorithms and pan-private algorithms, they use ideas from [13] to derive both upper and lower bounds on the sample complexity of shuffle private  ... 
arXiv:2108.08987v2 fatcat:mzarcifg3fevrb2672337bftbq

Privacy Amplification by Decentralization [article]

Edwige Cyffers, Aurélien Bellet
2022 arXiv   pre-print
Analyzing data owned by several parties while achieving a good trade-off between utility and privacy is a key challenge in federated learning and analytics.  ...  We prove that the privacy-utility trade-offs of our algorithms under network DP significantly improve upon what is achievable under LDP, and often match the utility of the trusted curator model.  ...  This work was supported by grants ANR-16-CE23-0016 (Project PAMELA) and ANR-20-CE23-0015 (Project PRIDE). The PhD scholarship of Edwige Cyffers is funded in part by Région Hauts-de-France.  ... 
arXiv:2012.05326v4 fatcat:zn6sio2be5b6dhg3wxkk6gb4mq

RECENT PROGRESS OF DIFFERENTIALLY PRIVATE FEDERATED LEARNING WITH THE SHUFFLE MODEL

Moushira Abdallah Mohamed Ahmed, Shuhui Wu, Laure Deveriane Dushime, Yuanhong Tao
2021 International Journal of Engineering Technologies and Management Research  
between privacy and utility in central and local model.  ...  We focused on the role of shuffle model for solving the problem between privacy and accuracy by summarizing the recent researches about shuffle model and its practical results.  ...  Jieming Mao. (2020), Connecting robust shuffle privacy and pan-privacy. arXiv:2004.09481.  ... 
doi:10.29121/ijetmr.v8.i11.2021.1028 fatcat:2dlseelznndq3aoau64dcrnaby

IoT Security via Address Shuffling: The Easy Way

Francesca Nizzi, Tommaso Pecorella, Flavio Esposito, Laura Pierucci, Romano Fantacci
2019 IEEE Internet of Things Journal  
In this paper, we propose a novel method to perform a network-wide (IP and MAC) address shuffling procedure, called Address Shuffling Algorithm with HMAC (AShA), which is simple to implement, and whose  ...  Securing Internet of Things (IoT) devices and protecting their applications from privacy leaks is a challenge, due to their weak (computational and storage) capabilities, and their proximity with sensitive  ...  ACKNOWLEDGMENT This work has been supported by the project "GAUChO -A Green Adaptive Fog Computing and Networking Architecture" funded by Ministero dell'Istruzione, dell'Università e della Ricerca (MIUR  ... 
doi:10.1109/jiot.2019.2892003 fatcat:ovryz4bx3fbojgtwupi4bp6q2e

On the Round Complexity of the Shuffle Model [article]

Amos Beimel, Iftach Haitner, Kobbi Nissim, Uri Stemmer
2020 arXiv   pre-print
The shuffle model of differential privacy was proposed as a viable model for performing distributed differentially private computations.  ...  Focusing on the round complexity of the shuffle model, we ask in this work what can be computed in the shuffle model of differential privacy with two rounds. Ishai et al.  ...  Acknowledgments The authors thank Rachel Cummings and Naty Peter for discussions of the shuffle model at an early stage of this research. Work of A. B. and K. N. was supported by NSF  ... 
arXiv:2009.13510v1 fatcat:kawh2rerpbbanaludfrb2q6zum

A Study on Authentication Mechanisms in Bitcoin

Shruthi N, Sowmyarani C N
2019 Zenodo  
The latest development of or concept of colored coins and coin shuffle can be used to protect the users who are connected to the network without compromising or leaking any information.  ...  The bitcoin blockchain is very impressive and robust that will help to manage the user information and also very helpful to determine the possession of the users framework.  ...  CURRENT AUTHENTICATION METHODS Coin Shuffle Bitcoin mixing is done for users to exchange credentials among the network anonymously and securely [5] .  ... 
doi:10.5281/zenodo.3358342 fatcat:gfbrgjbq4neyjinb7nivhkuvl4

Improved Utility Analysis of Private CountSketch [article]

Rasmus Pagh, Mikkel Thorup
2022 arXiv   pre-print
The post-processing property of differential privacy implies that all estimates computed from the sketch can be released within the given privacy budget.  ...  It is known that sketches can be made differentially private by adding noise according to the sensitivity of the sketch, and this has been used in private analytics and federated learning settings.  ...  Finally, we note that Cohen et al. (2022) recently used differential privacy techniques in connection with CountSketch in order to achieve robustness against adaptive adversaries that attempt to find  ... 
arXiv:2205.08397v1 fatcat:qngmayquj5gazk2ncgmg2cizx4

Data Privacy Preservation and Security Approaches for Sensitive Data in Big Data [chapter]

Rohit Ravindra Nikam, Rekha Shahapurkar
2021 Advances in Parallel Computing  
We also analyze the gap between various processes and privacy preservation methods and illustrate how to overcome such issues with new innovative methods.  ...  Sensitive data contains confidential information about individuals, businesses, and governments who must not agree upon before sharing or publishing his privacy data.  ...  Ex: Social security number, pan number, adhar number, voter id, driving license number, etc. 2: Quasi Identifiers: An arrangement of traits that can be conceivably connected with outside data to re-distinguish  ... 
doi:10.3233/apc210221 fatcat:nfw2tcltyja4zlro5myt57l5ge

Federated Learning with Position-Aware Neurons [article]

Xin-Chun Li and Yi-Chu Xu and Shaoming Song and Bingshuai Li and Yinchuan Li and Yunfeng Shao and De-Chuan Zhan
2022 arXiv   pre-print
PANs are algorithm-agnostic and could universally improve existing FL algorithms. Furthermore, "FL with PANs" is simple to implement and computationally friendly.  ...  PANs couple themselves to their positions and minimize the possibility of dislocation, even updating on heterogeneous data.  ...  Thanks to Huawei Noah's Ark Lab NetMIND Research Team and CAAI-Huawei MindSpore Open Fund (CAAIXSJLJJ-2021-014B). Thanks for Professor Yang Yang's suggestions.  ... 
arXiv:2203.14666v2 fatcat:eonoc2imazci7lbvhzbffkq6tq

DIFFERENTIAL PRIVACY FOR IOT-ENABLED CRITICAL INFRASTRUCTURE: A COMPREHENSIVE SURVEY

Muhammad Akbar Husnoo, Adnan Anwar, Ripon K. Chakrabortty, Robin Doss, Mike J. Ryan
2021 IEEE Access  
Adversaries carry out privacy-oriented attacks to gain access to the sensitive and confidential data of critical infrastructure for various self-centered, political and commercial gains.  ...  This paper provides a comprehensive and extensive survey of the application and implementation of differential privacy in four major application domains of IoT-enabled critical infrastructure: Smart Grids  ...  However, this three tier architecture is very basic and is unable to sustain the growing needs of a more robust IoT architecture [69] .  ... 
doi:10.1109/access.2021.3124309 fatcat:vejtyjyrwffeffi7ob2o2svyja

Privacy Preservation for Wireless Sensor Networks in Healthcare: State of the Art, and Open Research Challenges [article]

Yasmine N. M. Saleh, Claude C. Chibelushi, Ayman A. Abdel-Hamid, Abdel-Hamid Soliman
2020 arXiv   pre-print
healthcare, including threat analysis and assessment methodologies; it also offers classification trees for the multifaceted challenge of privacy protection in healthcare, and for privacy threats, attacks  ...  However, an important barrier is that acceptance by healthcare stakeholders is influenced by the effectiveness of privacy safeguards for personal and intimate information which is collected and transmitted  ...  Furthermore, there is need for robust privacy and security safeguards and controls, which address the applicable regulatory requirements.  ... 
arXiv:2012.12958v1 fatcat:6bqeb3htibaypmbfckveiizxpm

Multi-Party Dual Learning [article]

Maoguo Gong, Yuan Gao, Yu Xie, A. K. Qin, Ke Pan, Yew-Soon Ong
2021 arXiv   pre-print
We introduce a feature-oriented differential privacy with mathematical proof, in order to avoid possible privacy leakage of raw features in the dual inference process.  ...  However, in reality, data usually reside in distributed parties such as different institutions and may not be directly gathered and integrated due to various data policy constraints.  ...  is capable of exploring and enhancing the intrinsic probabilistic connection of data.  ... 
arXiv:2104.06677v1 fatcat:neotkicajzbdlalbb6tiuvhadm

An Efficient and Anonymous Buyer-Seller Watermarking Protocol

C.-L. Lei, P.-L. Yu, P.-L. Tsai, M.-H. Chan
2004 IEEE Transactions on Image Processing  
The result is an efficient and anonymous buyer-seller watermarking protocol.  ...  The proposed watermarking protocol also provides a fix to Memon and Wong's scheme by solving the unbinding problem.  ...  in the case of Memon and Wong's one. 4) 's privacy is well protected.  ... 
doi:10.1109/tip.2004.837553 pmid:15575156 fatcat:ln63773j3zhqhgg5j3nkv7g64q

Blockchain

Riya Sapra, Parneeta Dhaliwal
2021 International Journal of Healthcare Information Systems and Informatics  
Many applications are being built using the immutability and robustness of blockchain.  ...  Blockchain is a new class of information technology that combines cryptography and a distributed ledger that already exists.  ...  Apart from cryptocurrencies, blockchain is being implemented in a variety of application areas because of its robustness and data security features.  ... 
doi:10.4018/ijhisi.20210401.oa1 fatcat:mhvffj4uvffxbccq6orzlytw7m
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