Privacy in Control and Dynamical Systems

2018 ◽  
Vol 1 (1) ◽  
pp. 309-332 ◽  
Author(s):  
Shuo Han ◽  
George J. Pappas
Keyword(s):  
Dynamical Systems ◽  
Smart Grids ◽  
Differential Privacy ◽  
Side Information ◽  
Sensitive Information ◽  
Efficient Operation ◽  
The Public ◽  
Rigorous Approach ◽  
Trade Offs ◽  
User Data

Many modern dynamical systems, such as smart grids and traffic networks, rely on user data for efficient operation. These data often contain sensitive information that the participating users do not wish to reveal to the public. One major challenge is to protect the privacy of participating users when utilizing user data. Over the past decade, differential privacy has emerged as a mathematically rigorous approach that provides strong privacy guarantees. In particular, differential privacy has several useful properties, including resistance to both postprocessing and the use of side information by adversaries. Although differential privacy was first proposed for static-database applications, this review focuses on its use in the context of control systems, in which the data under processing often take the form of data streams. Through two major applications—filtering and optimization algorithms—we illustrate the use of mathematical tools from control and optimization to convert a nonprivate algorithm to its private counterpart. These tools also enable us to quantify the trade-offs between privacy and system performance.

scholarly journals Learning With Differential Privacy

2021 ◽  
pp. 372-395
Author(s):  
Poushali Sengupta ◽  
Sudipta Paul ◽  
Subhankar Mishra
Keyword(s):  
Privacy Protection ◽  
Differential Privacy ◽  
Intrusion Detection Systems ◽  
Sensitive Information ◽  
Detection Systems ◽  
Trade Offs ◽  
Personal Level ◽  
Encryption Decryption ◽  
Individual Trees ◽  
Prevention Methods

The leakage of data might have an extreme effect on the personal level if it contains sensitive information. Common prevention methods like encryption-decryption, endpoint protection, intrusion detection systems are prone to leakage. Differential privacy comes to the rescue with a proper promise of protection against leakage, as it uses a randomized response technique at the time of collection of the data which promises strong privacy with better utility. Differential privacy allows one to access the forest of data by describing their pattern of groups without disclosing any individual trees. The current adaption of differential privacy by leading tech companies and academia encourages authors to explore the topic in detail. The different aspects of differential privacy, its application in privacy protection and leakage of information, a comparative discussion on the current research approaches in this field, its utility in the real world as well as the trade-offs will be discussed.

scholarly journals Differential Privacy under Dependent Tuples - The Case of Genomic Privacy

2019 ◽  
Author(s):  
Nour Almadhoun ◽  
Erman Ayday ◽  
Özgür Ulusoy
Keyword(s):  
Differential Privacy ◽  
Genomic Data ◽  
Privacy Preserving ◽  
Supplementary Information ◽  
Sensitive Information ◽  
Genomic Databases ◽  
Privacy Concerns ◽  
Rigorous Approach ◽  
Genomic Studies ◽  
Inference Attack

Abstract Motivation The rapid progress in genome sequencing has led to high availability of genomic data. However, due to growing privacy concerns about the participant’s sensitive information, accessing results and data of genomic studies is restricted to only trusted individuals. On the other hand, paving the way to biomedical discoveries requires granting open access to genomic databases. Privacy-preserving mechanisms can be a solution for granting wider access to such data while protecting their owners. In particular, there has been growing interest in applying the concept of differential privacy (DP) while sharing summary statistics about genomic data. DP provides a mathematically rigorous approach but it does not consider the dependence between tuples in a database, which may degrade the privacy guarantees offered by the DP. Results In this work, focusing on genomic databases, we show this drawback of DP and we propose techniques to mitigate it. First, using a real-world genomic dataset, we demonstrate the feasibility of an inference attack on differentially private query results by utilizing the correlations between the tuples in the dataset. The results show that the adversary can infer sensitive genomic data about a user from the differentially private query results by exploiting correlations between genomes of family members. Second, we propose a mechanism for privacy-preserving sharing of statistics from genomic datasets to attain privacy guarantees while taking into consideration the dependence between tuples. By evaluating our mechanism on different genomic datasets, we empirically demonstrate that our proposed mechanism can achieve up to 50% better privacy than traditional DP-based solutions. Availability https://github.com/nourmadhoun/Differential-privacy-genomic-inference-attack. Supplementary information Supplementary data are available at Bioinformatics online.

Rooting Evaluation Guidelines in Relational Ethics: Lessons From Africa

2019 ◽  
Vol 41 (3) ◽  
pp. 404-419
Author(s):  
Caitlin Blaser Mapitsa ◽  
Tara Polzer Ngwato
Keyword(s):  
Culturally Responsive ◽  
Social Research ◽  
Relational Ethics ◽  
Developed Country ◽  
Evaluation Standards ◽  
The Public ◽  
Trade Offs ◽  
Context Specific ◽  
Ethical Clearance ◽  
Made In

As global discussions of evaluation standards become more contextually nuanced, culturally responsive conceptions of ethics have not been sufficiently discussed. In academic social research, ethical clearance processes have been designed to protect vulnerable people from harm related to participation in a research project. This article expands the ambit of ethical protection thinking and proposes a relational ethics approach for evaluation practitioners. This centers an analysis of power relations among and within all the different stakeholder groups in order to establish, in a context-specific manner, which stakeholders are vulnerable and in need of protection. The approach also contextualizes the nature of “the public good,” as part of an ethical consideration of interest trade-offs during evaluations. The discussion is informed by our experiences in African contexts and speaks to the “Made in Africa” research agenda but is also relevant to other global contexts where alternatives to “developed country” ontological assumptions about the roles of researchers and participations and the nature of vulnerability are being reconsidered.

scholarly journals Manipulation Attacks in Local Differential Privacy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Albert Cheu ◽  
Adam Smith ◽  
Jonathan Ullman
Keyword(s):  
Systematic Study ◽  
Differential Privacy ◽  
Domain Size ◽  
User Data ◽  
Large Systems ◽  
Cryptographic Techniques ◽  
Fundamental Limitation ◽  
Theoretical Results ◽  
Different Levels ◽  
Privacy Level

Local differential privacy is a widely studied restriction on distributed algorithms that collect aggregates about sensitive user data, and is now deployed in several large systems. We initiate a systematic study of a fundamental limitation of locally differentially private protocols: they are highly vulnerable to adversarial manipulation. While any algorithm can be manipulated by adversaries who lie about their inputs, we show that any noninteractive locally differentially private protocol can be manipulated to a much greater extent---when the privacy level is high, or the domain size is large, a small fraction of users in the protocol can completely obscure the distribution of the honest users' input. We also construct protocols that are optimally robust to manipulation for a variety of common tasks in local differential privacy. Finally, we give simple experiments validating our  theoretical results, and demonstrating that protocols that are optimal without manipulation can have dramatically different levels of robustness to manipulation. Our results suggest caution when deploying local differential privacy and reinforce the importance of efficient cryptographic  techniques for the distributed emulation of centrally differentially private mechanisms.

scholarly journals Cybersecurity: Toward a Meaningful Policy Framework

2018 ◽  
Author(s):  
Peter M. Shane
Keyword(s):  
Cyber Security ◽  
Security Policy ◽  
Legal Framework ◽  
Public Understanding ◽  
Policy Framework ◽  
Military Effectiveness ◽  
The Public ◽  
Trade Offs ◽  
National Debate ◽  
Sharing Responsibility

This critique of Karson K. Thompson’s note, "Not Like an Egyptian: Cybersecurity and the Internet Kill Switch Debate," argues that the U.S. lacks a framework of laws and regulations, "smart" or otherwise, that adequately incentivizes the parties with the greatest capacity to improve our cyber security to do so. It attributes the poor state of U.S. cyber policy to the "bewildering array of overlapping responsibilities" scattered among government offices and departments; the difficult imperative of sharing responsibility among military and civilian authorities; the fact that most of the networks (and the dependent critical infrastructures) that need protecting are in private hands; and the lack of public understanding of the kinds of regulation that are necessary or appropriate. The essay argues that meaningful progress towards an adequate legal framework depends on a broad national debate aimed at defining the public good with regard to cyber-security, and the inevitable trade-offs among security, privacy, productivity, economic growth, organizational flexibility, military effectiveness, government transparency, and accountability that must be confronted in making sensible cyber-security policy.

scholarly journals Efficient and Privacy-Preserving Multi-User Outsourced K-Means Clustering

2021 ◽  
Vol 14 (2) ◽  
pp. 26
Author(s):  
Na Li ◽  
Lianguan Huang ◽  
Yanling Li ◽  
Meng Sun
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Clustering Algorithm ◽  
Privacy Preserving ◽  
Locality Sensitive Hashing ◽  
Sensitive Information ◽  
The Public ◽  
Big Data Mining ◽  
Euclidean Distances ◽  
Computational Resources

In recent years, with the development of the Internet, the data on the network presents an outbreak trend. Big data mining aims at obtaining useful information through data processing, such as clustering, clarifying and so on. Clustering is an important branch of big data mining and it is popular because of its simplicity. A new trend for clients who lack of storage and computational resources is to outsource the data and clustering task to the public cloud platforms. However, as datasets used for clustering may contain some sensitive information (e.g., identity information, health information), simply outsourcing them to the cloud platforms can't protect the privacy. So clients tend to encrypt their databases before uploading to the cloud for clustering. In this paper, we focus on privacy protection and efficiency promotion with respect to k-means clustering, and we propose a new privacy-preserving multi-user outsourced k-means clustering algorithm which is based on locality sensitive hashing (LSH). In this algorithm, we use a Paillier cryptosystem encrypting databases, and combine LSH to prune off some unnecessary computations during the clustering. That is, we don't need to compute the Euclidean distances between each data record and each clustering center. Finally, the theoretical and experimental results show that our algorithm is more efficient than most existing privacy-preserving k-means clustering.

scholarly journals Resolve in International Politics

2016 ◽  
Author(s):  
Joshua D. Kertzer
Keyword(s):  
International Politics ◽  
Self Control ◽  
Social Scientists ◽  
Military Interventions ◽  
Daily Lives ◽  
The Public ◽  
Trade Offs ◽  
Figure Of Speech ◽  
Important Idea ◽  
War And Conflict

Why do some leaders and segments of the public display remarkable persistence in confrontations in international politics, while others cut and run? The answer given by policymakers, pundits, and political scientists usually relates to issues of resolve. Yet, though we rely on resolve to explain almost every phenomenon in international politics—from prevailing at the bargaining table to winning on the battlefield—we don't understand what it is, how it works, or where it comes from. This book draws on a growing body of research in psychology and behavioral economics to explore the foundations of this important idea. It argues that political will is more than just a metaphor or figure of speech: the same traits that social scientists and decision-making scholars use to comprehend willpower in our daily lives also shape how we respond to the costs of war and conflict. The book shows how time and risk preferences, honor orientation, and self-control help explain the ways by which leaders and members of the public define the situations they face and weigh the trade-offs between the costs of fighting and the costs of backing down. Offering a novel in-depth look at how willpower functions in international relations, the book has critical implications for understanding political psychology, public opinion about foreign policy, leaders in military interventions, and international security.

The USA Electrical Grid

2019 ◽  
pp. 659-672
Author(s):  
Eugene de Silva ◽  
Eugenie de Silva
Keyword(s):  
Smart Grids ◽  
Public Perception ◽  
Public Awareness ◽  
Community Outreach ◽  
Strong Relationship ◽  
Cyber Attacks ◽  
Intelligence Community ◽  
Electrical Grid ◽  
The Public ◽  
The Usa

This chapter provides a discussion of the United States (U.S.) electrical grid. In particular, the chapter explicates the vulnerabilities of the electrical grid by placing a focus on public perception, cyber-attacks, and the inclement weather. The authors elaborate on the necessity of contingency plans, heightened security through the utilization of smart grids and microgrids, and improved cooperation between the Intelligence Community (IC) and the public. This chapter further expands on the importance of government agencies establishing community outreach programs to raise public awareness and build a strong relationship between U.S. security agencies and the public. Overall, this chapter highlights the key issues pertaining to the electrical grid, and provides solutions and strategies to resolve them.

scholarly journals Application Level Security in a Public Library: A Case Study

2018 ◽  
Vol 37 (4) ◽  
pp. 107-118
Author(s):  
Richard Thomchick ◽  
Tonia San Nicolas-Rocca
Keyword(s):  
Secure Communication ◽  
Public Library ◽  
Transport Protocol ◽  
Sensitive Information ◽  
Privacy And Security ◽  
The Public ◽  
Security Challenges ◽  
Personally Identifiable Information ◽  
Active Attacks

Libraries have historically made great efforts to ensure the confidentiality of patron personally identifiable information (PII), but the rapid, widespread adoption of information technology and the internet have given rise to new privacy and security challenges. Hypertext Transport Protocol Secure (HTTPS) is a form of Hypertext Transport Protocol (HTTP) that enables secure communication over the public internet and provides a deterministic way to guarantee data confidentiality so that attackers cannot eavesdrop on communications. HTTPS has been used to protect sensitive information exchanges, but security exploits such as passive and active attacks have exposed the need to implement HTTPS in a more rigorous and pervasive manner. This report is intended to shed light on the state of HTTPS implementation in libraries, and to suggest ways in which libraries can evaluate and improve application security so that they can better protect the confidentiality of PII about library patrons.

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