Policy Enforcement System for Inter-Organizational Data Sharing

2010 ◽  
Vol 4 (3) ◽  
pp. 22-39 ◽  
Author(s):  
Mamoun Awad ◽  
Latifur Khan ◽  
Bhavani Thuraisingham
Keyword(s):  
Data Mining ◽  
Data Sharing ◽  
Information Loss ◽  
Third Parties ◽  
Third Party ◽  
Policy Enforcement ◽  
Data Set ◽  
Amount Of Information ◽  
Statistical Report ◽  
Releasing Factors

Sharing data among organizations plays an important role in security and data mining. In this paper, the authors describe a Data Sharing Miner and Analyzer (DASMA) system that simulates data sharing among N organizations. Each organization has its own enforced policy. The N organizations share their data based on trusted third party. The system collects the released data from each organization, processes it, mines it, and analyzes the results. Sharing in DASMA is based on trusted third parties. However, organizations may encode some attributes, for example. Each organization has its own policy represented in XML format. This policy states what attributes can be released, encoded, and randomized. DASMA processes the data set and collects the data, combines it, and prepares it for mining. After mining, a statistical report is produced stating the similarities between mining with data sharing and mining without sharing. The authors test, apply data sharing, enforce policy, and analyze the results of two separate datasets in different domains. The results indicate a fluctuation on the amount of information loss using different releasing factors.

scholarly journals Dark Clouds and Silver Linings: Impact of COVID-19 on Internet Users’ Privacy

JAMIA Open ◽  
2021 ◽  
Author(s):  
Ram D Gopal ◽  
Hooman Hidaji ◽  
Raymond A Patterson ◽  
Niam Yaraghi
Keyword(s):  
Data Sharing ◽  
Third Parties ◽  
Third Party ◽  
Latent Growth ◽  
Dark Clouds ◽  
Privacy Threats ◽  
Internet Users ◽  
The Us ◽  
User Data ◽  
The Impact

Abstract Objectives To examine the impact of COVID-19 pandemic on the extent of potential violations of Internet users’ privacy. Materials and Methods We conducted a longitudinal study of the data sharing practices of the top 1,000 websites in the US between April 9th and August 27th, 2020. We fitted a conditional latent growth curve model on the data to examine the longitudinal trajectory of the third-party data sharing over the 21 weeks period of the study and examine how website characteristics affect this trajectory. We denote websites that asked for permission before placing cookies on users’ browsers as "privacy-respecting". Results As the weekly number of COVID-19 deaths increased by 1,000, the average number of third parties increased by 0.26 [95%CI, 0.15 to 0.37] P<.001 units in the next week. This effect was more pronounced for websites with higher traffic as they increased their third parties by an additional 0.41 [95% CI, 0.18 to 0.64]; P<.001 units per week. However, privacy respecting websites that experienced a surge in traffic reduced their third parties by 1.01 [95% CI, -2.01 to 0]; P = 0.05 units per week in response to every 1,000 COVID-19 deaths in the preceding week. Discussion While in general websites shared their users’ data with more third parties as COVID-19 progressed in the US, websites’ expected traffic and respect for users’ privacy significantly affect such trajectory. Conclusions Attention should also be paid to the impact of the pandemic on elevating online privacy threats, and the variation in third-party tracking among different types of websites. Lay Summary As the COVID-19 pandemic progressed in the country, the demand for online services surged. As the level of Internet use increased, websites’ opportunity to track and monetize users’ data increased with it. In this research, we examine the extent to which websites increased the number of third-parties with which they share their user’ data and how such practices were moderated by a website’s level of respect for users’ privacy and traffic surge. We find that while the number of third parties increased over time, the websites with higher respect for privacy tend to decrease the number of their parties only if they also experience a significant increase in their traffic.

Helpful Behavior and the Durability of Collaborative Ties

2021 ◽  
Author(s):  
Sampsa Samila ◽  
Alexander Oettl ◽  
Sharique Hasan
Keyword(s):  
Active Agent ◽  
Third Parties ◽  
Third Party ◽  
Unexpected Death ◽  
Traditional Role ◽  
Data Set ◽  
Unique Data ◽  
Random Loss ◽  
Scientific Collaborations

Long-term collaborations are crucial in many creative domains. Although there is ample research on why people collaborate, our knowledge about what drives some collaborations to persist and others to decay is still emerging. In this paper, we extend theory on third-party effects and collaborative persistence to study this question. We specifically consider the role that a third party’s helpful behavior plays in shaping tie durability. We propose that when third parties facilitate helpfulness among their group, the collaboration is stronger, and it persists even in the third’s absence. In contrast, collaborations with third parties that are nonhelpful are unstable and dissolve in their absence. We use a unique data set comprising scientific collaborations among pairs of research immunologists who lost a third coauthor to unexpected death. Using this quasi-random loss as a source of exogenous variation, we separately identify the effect of third parties’ traditional role as an active agent of collaborative stability and the enduring effect of their helpful behavior—as measured by acknowledgments—on the persistence of the remaining authors’ collaboration. We find support for our hypotheses and find evidence that one mechanism driving our effect is that helpful thirds make their coauthors more helpful.

Three's a Crowd: Third Parties and WTO Dispute Settlement

2006 ◽  
Vol 58 (3) ◽  
pp. 446-477 ◽  
Author(s):  
Marc L. Busch ◽  
Eric Reinhardt
Keyword(s):  
World Trade ◽  
Dispute Settlement ◽  
Selection Effect ◽  
Third Parties ◽  
Third Party ◽  
Data Set ◽  
Wto Dispute Settlement ◽  
Early Settlement ◽  
The World ◽  
Party Support

Disputes filed at the World Trade Organization (WTO) are attracting a growing number of third parties. Most observers argue that their participation influences the institution's rulings. The authors argue that third parties undermine pretrial negotiations; their influence on rulings is conditioned by this selection effect. They test their hypotheses, along with the conventional wisdom, using a data set of WTO disputes initiated through 2002. Consistent with the authors' argument, they find that third-party participationlowersthe prospects for early settlement. Controlling for this selection effect, the evidence also suggests that third-party support increases the chances of a legal victory at the WTO.

War and Third-party Trade

2016 ◽  
Vol 62 (1) ◽  
pp. 119-142 ◽  
Author(s):  
Nizan Feldman ◽  
Tal Sadeh
Keyword(s):  
Fixed Effects ◽  
Third Parties ◽  
Third Party ◽  
Trade Policies ◽  
High Definition ◽  
Data Set ◽  
Dyadic Data ◽  
Business Partners ◽  
Fixed Effects Regression ◽  
Almost All

Few studies explain how wars affect trade with third parties. We argue that wartime trade policies should raise trade with friendly and enemy-hostile third parties but reduce trade with hostile and enemy-friendly third parties. At the same time, the private motivation of firms and households may be incompatible with national wartime trade policies and constrain the effectiveness of wartime trade policies. Our directed dyadic data set consists of almost all of the states from 1885 to 2000. Running a high definition fixed effects regression with two-way clustering of standard errors, we find that hostile third parties tended to reduce trade with a combatant state by roughly 30 percent. In addition, trade with third parties friendly to the enemy fell by a similar magnitude. In contrast, on average, war hardly affected trade with third parties because of substitution of war-ridden markets with third-party business partners.

scholarly journals A Federated Record Linkage Algorithm for Secure Medical Data Sharing

2021 ◽  
Author(s):  
Christian M. Heidt ◽  
Hauke Hund ◽  
Christian Fegeler
Keyword(s):  
Data Sharing ◽  
Record Linkage ◽  
Medical Records ◽  
Data Privacy ◽  
Medical Data ◽  
Third Party ◽  
Bloom Filters ◽  
Data Set ◽  
Optimal Weights ◽  
Linkage Algorithm

The process of consolidating medical records from multiple institutions into one data set makes privacy-preserving record linkage (PPRL) a necessity. Most PPRL approaches, however, are only designed to link records from two institutions, and existing multi-party approaches tend to discard non-matching records, leading to incomplete result sets. In this paper, we propose a new algorithm for federated record linkage between multiple parties by a trusted third party using record-level bloom filters to preserve patient data privacy. We conduct a study to find optimal weights for linkage-relevant data fields and are able to achieve 99.5% linkage accuracy testing on the Febrl record linkage dataset. This approach is integrated into an end-to-end pseudonymization framework for medical data sharing.

scholarly journals Illicit tobacco trade is ‘booming’: UK newspaper coverage of data funded by transnational tobacco companies

2020 ◽  
pp. tobaccocontrol-2018-054902 ◽  
Author(s):  
Karen Evans-Reeves ◽  
Jenny Hatchard ◽  
Andy Rowell ◽  
Anna B Gilmore
Keyword(s):  
Media Coverage ◽  
Tobacco Industry ◽  
Third Parties ◽  
Third Party ◽  
Freedom Of Information ◽  
Industry Funding ◽  
Data Set ◽  
Illicit Trade ◽  
Illicit Tobacco Trade ◽  
Transnational Tobacco Companies

BackgroundTransnational tobacco companies (TTCs) have heavily publicised their argument that standardised tobacco packaging will increase the illicit tobacco trade. Leaked Philip Morris International (PMI) documents suggest that the company may have intended to use third parties to promulgate this argument in the UK.MethodsWe examined articles in UK newspapers (1 April 2013 to 31 March 2015) from LexisNexis for presence and nature of tobacco industry data. We also examined documents released by Freedom of Information requests made to Scottish Councils for evidence of how PMI operationalised its third-party strategy.FindingsTwo-thirds of newspaper articles (63%, 99/157) mentioned a PMI consultant; 36% of which did not disclose this industry funding. Most articles mentioned counterfeit tobacco, illicit whites or both (72%, 113/157), while few (4%, 7/157) specifically mentioned tobacco industry illicit tobacco and none explained that the latter can include tobacco-company involvement. Freedom of Information documents revealed that the PMI consultant sought to build relationships with Trading Standards officers, conducted undercover test purchases (UTPs) in illicit tobacco ‘hotspots’ and may have promoted unrepresentative findings in the media. While the data set featured PMI data predominantly, other TTCs also engaged in third-party techniques to promulgate messages on illicit tobacco.InterpretationPMI engaged a third party, seemingly with the aim of securing media coverage on illicit tobacco positing that standardised packaging would worsen the problem. The predominant focus of articles which featured industry-funded data and information was on counterfeit tobacco despite official data showing tobacco-industry illicit tobacco as the most prevalent. Other jurisdictions considering the policy should anticipate that third parties will promote the illicit-trade argument.

scholarly journals PRESERVING PRIVACY FOR PAGERANK ALGORITHM

2020 ◽  
Vol 1 (2) ◽  
pp. 58-60
Author(s):  
Tho Thi Ngoc Le
Keyword(s):  
Data Mining ◽  
Third Parties ◽  
Third Party ◽  
Cyber Attack ◽  
Pagerank Algorithm ◽  
The Third ◽  
Sharing Scheme ◽  
Huge Data ◽  
Data Owner ◽  
Design Systems

Data mining has been emergingly applied in many fields to discover the knowledge from the huge data. To do that, information has been sent forward and backward among data owners, users, and maybe third parties. In this situation, it is necessary to design systems to exchange the data between the data owner, the client and third parties during data mining process without scarifying the sensitiveness of data. Hence, we need a privacy preserving mechanism while mining to protect the data as in the situation of sophisticated cyber-attack. In this work, we describe a model for ensuring the privacy in ranking on the graph using PageRank and Shamir Secure Sharing scheme. Specifically, Shamir Secure Sharing scheme has been applied to share the information of graph from the data owner to many servers (i.e. third party). Then, the share of graph on each server will be ranked separately. When the users need the results of ranking and make a request, the information from servers will be combined for the users. Doing this way, the third party doesn’t know the meaning of data but still run analyzing the data. Hence, data owner preserves the privacy of his data while users still retrieve a piece of the information as needed.

Intervention in Conflicts from a Network Perspective

2012 ◽  
Vol 29 (3) ◽  
pp. 314-340 ◽  
Author(s):  
Renato Corbetta ◽  
Keith A. Grant
Keyword(s):  
Third Parties ◽  
Third Party ◽  
Dyadic Relationships ◽  
Data Set ◽  
Interstate Disputes ◽  
Interstate Conflicts ◽  
Events Data ◽  
Militarized Interstate Disputes ◽  
Structural Theories ◽  
Hostility Scale

Whether neutral or on the side of a combatant, third-party states’ intervention in ongoing interstate conflicts is a triadic phenomenon which involves ties between a joining state and the two originators of the dispute. Existing studies on this topic have failed to fully capture the triadic nature of intervention, preferring instead to focus either on the joiner’s motivations or on the distinct dyadic relationships between joiners and the two separate combatants. Building on classic structural theories of triadic balance and on prior work by Maoz et al. (2007), in this article we address the triadic aspect of both mediation and “joining behavior”. The nature of the triadic relations among disputants and third parties influences not just the likelihood of intervention, but also the type of intervention. When triadic relations are unbalanced, third parties are more likely to intervene as intermediaries. On the contrary, when triadic relations are balanced, third parties are more likely to intervene in a partisan manner. We explore our main hypotheses by constructing a triadic data set that combines Corbetta and Dixon’s (2005) data on partisan third-party interventions and Frazier and Dixon’s (2006) data on neutral (intermediary) interventions in militarized interstate disputes with a friendship–hostility scale extracted from international events data (IDEA and COPDAB).

Privacy-Preserving Data Mining

2009 ◽  
pp. 527-536 ◽  
Author(s):  
Alexandre Evfimievski ◽  
Tyrone Grandison
Keyword(s):  
Data Mining ◽  
Privacy Preservation ◽  
Statistical Processing ◽  
Privacy Preserving ◽  
Third Party ◽  
Data Publishing ◽  
Sensitive Information ◽  
Public Servants ◽  
Data Set ◽  
Privacy Preserving Data Mining

Privacy-preserving data mining (PPDM) refers to the area of data mining that seeks to safeguard sensitive information from unsolicited or unsanctioned disclosure. Most traditional data mining techniques analyze and model the data set statistically, in aggregated form, while privacy preservation is primarily concerned with protecting against disclosure of individual data records. This domain separation points to the technical feasibility of PPDM. Historically, issues related to PPDM were first studied by the national statistical agencies interested in collecting private social and economical data, such as census and tax records, and making it available for analysis by public servants, companies, and researchers. Building accurate socioeconomical models is vital for business planning and public policy. Yet, there is no way of knowing in advance what models may be needed, nor is it feasible for the statistical agency to perform all data processing for everyone, playing the role of a trusted third party. Instead, the agency provides the data in a sanitized form that allows statistical processing and protects the privacy of individual records, solving a problem known as privacypreserving data publishing. For a survey of work in statistical databases, see Adam and Wortmann (1989) and Willenborg and de Waal (2001).

Cláusulas de franquicia o deducible en seguros de responsabilidad civil en el Derecho español: Naturaleza y efectos respecto de terceros perjudicados

2018 ◽  
pp. 101
Author(s):  
Rafael Lara González
Keyword(s):  
Civil Liability ◽  
Third Parties ◽  
Insurance Contract ◽  
Third Party ◽  
Liability Insurance ◽  
Legal Doctrine ◽  
Insurance Contracts ◽  
Spanish Law ◽  
Palabras Clave ◽  
Legal Nature

ResumenPese a su ubicuidad en la práctica contractual, las cláusulas de franquicia han recibido tratamiento incidental en la doctrina. La discusión sobre ellas se ha enfocado en los contratos de seguros de responsabilidad civil, y en la interpretación del artículo 76 de la Ley española de Contrato de Seguro. En este contexto se ha tratado de establecer si el asegurador puede o no oponer la cláusula de franquicia al tercero perjudicado. El presente trabajo analiza la cláusula de franquicia en la obligación principal del asegurador, su naturaleza jurídica, y examina su relación con los terceros perjudicados. La consideración principal a este respecto estará en si nos encontramos ante un seguro obligatorio o ante un seguro voluntario de responsabilidad civil. Palabras clave: Contrato de seguro; Cláusula de franquicia; Terceroperjudicado; Responsabilidad civil.AbstractDespite their ubiquity in contractual praxis, deductible clauses have received only incidental treatment in legal doctrine. Discussion on them has focused on civil liability insurance contracts, and the interpretation of article 76 of the Spanish Law of Insurance Contracts. In this context it has been attempted to establish whether the insurer can invoke the clause to oppose the injured third party's claim. This article examines the deductible clause included in the insurer's main obligation, its legal nature, and its relation to injured third parties. The main consideration in this regard will be whether the insurance contract is of a mandatory or voluntary nature.Keywords: Insurance contract; Deductible clause; Injured third party; Civil liability.

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