Personally Identifiable Information Research Articles

Multidimensional Point Transform for Public Health Practice

With increases in spatial information and enabling technologies, location-privacy concerns have been on the rise. A commonly proposed solution in public health involves random perturbation, however consideration for individual dimensions (attributes) has been weak. The current study proposes a multidimensional point transform (MPT) that integrates the spatial dimension with other dimensions of interest to comprehensively anonymise data. The MPT relies on the availability of a base population, a subset patient dataset, and shared dimensions of interest. Perturbation distance and anonymity thresholds are defined, as are allowable dimensional perturbations. A preliminary implementation is presented using sex, age and location as the three dimensions of interest, with a maximum perturbation distance of 1 kilometre and an anonymity threshold of 20%. A synthesised New York county population is used for testing with 1000 iterations for each of 25, 50, 100, 200 and 400 patient dataset sizes. The MPT consistently yielded a mean perturbation distance of 46 metres with no sex or age perturbation required. Displacement of the spatial mean decreased with patient dataset size and averaged 5.6 metres overall. The MPT presents a flexible, customisable and adaptive algorithm for perturbing datasets for public health, allowing tweaking and optimisation of the trade-offs for different datasets and purposes. It is not, however, a substitute for secure and ethical conduct, and a public health framework for the appropriate disclosure, use and dissemination of data containing personal identifiable information is required. The MPT presents an important component of such a framework.

Towards A Differential Privacy and Utility Preserving Machine Learning Classifier

Many organizations transact in large amounts of data often containing personal identifiable information (PII) and various confidential data. Such organizations are bound by state, federal, and international laws to ensure that the confidentiality of both individuals and sensitive data is not compromised. However, during the privacy preserving process, the utility of such datasets diminishes even while confidentiality is achieved--a problem that has been defined as NP-Hard. In this paper, we investigate a differential privacy machine learning ensemble classifier approach that seeks to preserve data privacy while maintaining an acceptable level of utility. The first step of the methodology applies a strong data privacy granting technique on a dataset using differential privacy. The resulting perturbed data is then passed through a machine learning ensemble classifier, which aims to reduce the classification error, or, equivalently, to increase utility. Then, the association between increasing the number of weak decision tree learners and data utility, which informs us as to whether the ensemble machine learner would classify more correctly is examined. As results, we found that a combined adjustment of the privacy granting noise parameters and an increase in the number of weak learners in the ensemble machine might lead to a lower classification error.

Facebook and User-Controlled Privacy: Evaluating Privacy Settings as Notice-and-Consent

“Notice and consent” is a widely-used model of privacy protection that relies on users’ ability to interpret an organization’s written description of its information practices through a privacy policy and choose whether to participate. In the past, organizations using this model have fallen under harsh criticism for providing long, legalistic notices and confusing, unclear choices. In the past few years, Facebook has sought to address these issues through privacy settings such as the “Privacy Publisher tool.” These mechanisms are new and untested, but they could potentially vindicate notice-and-consent by using graphics, metrics and other mechanisms to better inform and facilitate privacy decisions. The study will test the efficacy of these mechanisms for providing appropriate protection. In doing so, it will evaluate their feasibility as a model for notice and consent. To conduct this evaluation, the thesis will conduct a behavioral survey of how site visitors use these settings to understand their privacy risk and make decisions based on personal preferences. The study hypothesizes that, while privacy settings may provide some protection, they leave most users unprotected from many significant privacy harms. The survey itself will consist of three sections. The first section will test respondents’ ability to use the privacy settings to protect against specific harms. The survey will present the respondents with the mock privacy pages and prompt them to choose settings in response to a privacy issue. One prompt may be: “Choose Facebook settings that would only allow friends to tag photos of you.” The results could indicate whether the settings discourage certain kinds of protections, such as content sharing restrictions on Facebook. The second section will examine how respondents currently apply their privacy preferences on Facebook. Respondents will begin by submitting their Facebook privacy settings via multiple choice answers. Respondents will then answer questions about their preferences for each privacy practice. This section will permit the study to compare users’ opinion on the issues with how they actually selected their settings and will be an important indicator for evaluating the privacy settings. Finally, the third section will collect information of demographics and Facebook usage, such as how often a user checks Facebook for updates or posts to his or her wall. The final report will include a statistical analysis of these results and an examination of the conclusion. The study will conduct an analysis of variance, for instance, to understand how significant the gaps were between respondents’ selected settings and the settings that actually protect their preferences. The study will also employ regression techniques to understand which privacy settings face similar usability obstacles and which demographics face greater risks to privacy. David Krone is a recent graduate of Georgetown University’s Communications, Culture and Technology Program. David conducted research on Facebook Privacy as part of his thesis, with Georgetown Professors Mark MacCarthy and Diana Owen as advisors. In addition, David works full time as a Cybersecurity and Privacy Analyst at the Office of Personnel Management where he holds several privacy-related responsibilities. These include assessing IT system security risks to conducting system privacy threshold analyses (PTAs) and compiling reports on breaches involving personally identifiable information (PII). David holds the certification for the CIPP/G (Certified Information Privacy Professional – Government). Finally, as a Georgetown undergraduate, David studied the intersection of society and information and communications technologies by majoring in Science, Technology and International Affairs and minoring in Computer Science.

Commentary: The Good, the Bad, and the Ugly of Social Media

Commentary: The Good, the Bad, and the Ugly of Social Media

Standard Implementation for Privacy Framework and Privacy Reference Architecture for Protecting Personally Identifiable Information

Personal Identifiable Information (PII) is considered information that identifies or can be used to identify, contact, or locate a person to whom such information pertains or that is or might be linked to a natural person directly or indirectly. In order to recognize such data processed within information and communication technologies such as PII, it should be determined at which stage the information identifies, or can be associated with, an individual. For this, there has been ongoing research for privacy protection mechanism to protect PII, which now becomes one of hot issues in the International Standard as privacy framework and privacy reference architecture. Data processing flow models should be developed as an integral component of privacy risk assessments. Such diagrams are also the basis for categorizing PII. The data processing flow may not only show areas where the PII has a certain level of sensitivity or importance and, as a consequence, requires the implementation of stronger safeguarding measures. This paper propose a standard format for satisfying the ISO/IEC 29100 “Privacy Framework” and shows an implementation example for privacy reference architecture implementing privacy controls for the processing of PII in information and communication technology.

Social media and cookies: challenges for online privacy

PurposeThe advent of Web 2.0 or so‐called social media have enabled a new kind of communication, called mass self‐communication. These tools and the new form of communication are believed to empower users in everyday life. The authors of this paper observe a paradox: if this positive potential is possible, the negative downside is also possible. There is often a denial of this downside and it is especially visible in social media at the level of privacy and dataveillance. The purpose of this paper is to illustrate this point through an analysis of cookies.Design/methodology/approachThe paper illustrates how mass self‐communication in social media enables a new form of vulnerability for privacy. This is best shown by redefining privacy as flows of Personal Identifiable Information (PII) that are regulated by informational norms of Nissenbaum's concept of contextual integrity. Instead of analysing these contexts on a general level, the paper operationalises them on the user level to illustrate the lack of user awareness regarding cookies. The results of the research were gathered through desk research and expert interviews.FindingsThe positive aspects of cookies, unobtrusiveness and ease of use, are also the main challenges for user privacy. This technology can be disempowering because users are often hardly aware of its existence. In that way cookies can obfuscate the perceived context of personal data exposure.Originality/valueThe research shows how user disempowerment in social media is often overlooked by overstressing their beneficial potential.

Personal Identifiable Information and Laws: The Case of Financial Services

The ability of information and communication technology to gather, process, and distribute vast amounts of information has magnified privacy concerns. Information privacy laws regulate the handling of personal identifiable information (PII) by recognizing the rights that persons should have and the responsibilities organizations should accept. This paper proposes a conceptual foundation for drafting such laws that takes into consideration the unique features of information, and it include definitions for identification of generic phases of handling of PII. The results are applied to the US Gramm-Leach-Bliley Act as a study case for building a basic framework for drafting of legal texts in the context of information privacy.

Differentiated security levels for personal identifiable information in identity management system

With the rapid development of Internet services, identity management (IdM) has got widely attraction as the credit agency between users and service providers. It facilitates users to use the Internet service, promotes service providers to enrich services, and makes Internet more security. Personally identifiable information (PII) is the most important information asset with which identity provider (IdP) can provide various services. Since PII is sensitive to users, it has become a serious problem that PII is leaked, illegal selected, illegal accessed. In order to improve security of PII, this study develops a novel framework using data mining to forecast information asset value and find appropriate security level for protecting user PII. The framework has two stages. In the first stage, user information asset is forecasted by data mining tool (decision tree) from PII database. Then security level for user PII is determined by the information asset value assuming that the higher information asset is, the more security requirement of PII is. In the second stage, with time being, number of illegal access and attack can be accumulated. It can be used to reconstruct the decision tree and update the knowledge base combined with the result of the first stage. Thus security level of PII can be timely adjusted and the protection of PII can be guaranteed even when security threat changes. Furthermore, an empirical case was studied in a user dataset to demonstrate the protection decision derived from the framework for various PII. Simulation results show that the framework with data mining can protect PII effectively. Our work can benefit the development of e-business service.

Experimentation with the Design of Databases of Personal Identifiable Information

A database of personal identifiable information (PII) is designed based on PII, analogous to normalizing relational database schema using data dependencies. A PII database with its own conceptual scheme, system management, and physical structure can be justified according to security and privacy considerations. In this paper, we experiment with the design of conceptual schema for two actual relational databases: a training center database, and a hospital database. The resultant picture creates a schema that includes only privacy-significant data.

Information Privacy

In the Web dependent world, companies must respect and protect individuals’ information privacy. Companies develop and implement corporate information privacy policies to comply with the domestic and international information privacy laws and regulations. This paper investigates: (a) the approach used by multinational and domestic companies to develop and implement corporate information privacy policies; and (b) the perception of corporate managers/professionals toward information privacy legislation and secondary use of personally identifiable information (PII) that organizations collect. A survey was conducted to collect data from corporate CEOs, managers, and technical professionals of national and multinational companies. Findings indicate the following: 1) Views regarding the practicality and effectiveness of information privacy legislations are similar for respondents from the national and multinational companies. 2) Respondents are undecided about whether the privacy laws of the United States and foreign countries are equally restrictive. 3) Multinational companies do not favor developing and implementing uniform information privacy policies or different information privacy policies across countries of operations. 4) Respondents strongly agreed that unauthorized secondary use of personal information is unacceptable.

Identity Analytics And Belief Structures

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="color: black; font-size: 10pt; mso-themecolor: text1;"><span style="font-family: Times New Roman;">Personal identity is an important topic in information systems in general and data analytics in particular.<span style="mso-spacerun: yes;">  </span>Normally associated with digital security and privacy, the scope of identity is much greater and affects most aspects of everyday life.<span style="mso-spacerun: yes;">  </span>Related subjects are behavioral tracking, personal-identifiable information (PII), privacy data relevance, data repurposing, identity theft, and homeland security.<span style="mso-spacerun: yes;">  </span>The purpose of this paper is to establish a context for using analytics to combine evidence to categorize certain subjects based on belief structures.<span style="mso-spacerun: yes;">  </span><span style="mso-spacerun: yes;"> </span></span></span></p>

Identity And Privacy Services

Personal identity and privacy are important topics in information systems in general and data analytics in particular. Normally associated with digital security, the scope of identity and privacy is much greater and affects most aspects of everyday life. Related subjects are behavioral tracking, personal-identifiable information (PII), privacy data relevance, data repurposing, identity theft, and homeland security. Identity and Privacy Services is an admixture of the major issues in the area of personal identity and privacy and the security of individual rights in a complex societal environment. This is a general paper on this important subject, intended to give exposure to the constituent topics.

Conceptualizing privacy

I often lead discussions and give presentations where I need to get the audience in the mindset to start thinking about privacy in a way to which they could personally relate, understand others' privacy expectations, and discover for themselves that privacy is about more than just technical security controls for personally identifiable information (PII). Below are an approach and an exercise I took my audience through in a few presentations last year; they both have been well received and I think others might find them useful.

South African banks and their online privacy policy statements: A content analysis

In Internet banking and Internet-related transactions, security and privacy are of great concern. To alleviate these concerns, the South African government has promulgated the Electronic Communications and Transactions (ECT) Act No. 25 of 2002. The Act regulates all electronic communication transactions in South Africa. Business organisations implement the Act by, for example, posting a privacy policy statement on their websites, which, in accordance with the requirements of the ECT Act, states how the organisation will use any personal identifiable information provided by the client. This study investigates whether South African banks that subscribe to the ECT Act comply with the principles relating to the protection of a consumer’s personal information. The study employed the research methods of content analysis and interviews. The findings indicate that some banks only complied with a few of the ECT Act principles, which, according to the interview respondents, undermines the levels of trust which are in play between their banks and themselves. The respondents themselves were not fully aware of all the ECT Act requirements. This lack of awareness results in consumers failing to assess the comprehensiveness of their bank’s policy statements and to what extent such banks comply with the ECT Act.

Am I Safe? Exploring Relationships between Primary Territories and Online Privacy

This research analyzed 2006 Princeton survey data to investigate the relationship between Internet users' privacy concerns and types of personally identifiable information (PII) disclosed online. Drawing on Altman's primary territory theory (1975), it tested associations linking online–offline PII transferability to overall privacy concerns. For this sample, PII susceptible for spillage into offline, primary territories was most likely to engender user privacy concerns. In turn, respondents concerned about privacy self-reported limited online self-disclosures. Additional analyses uncovered age-specific effects as mediators between PII disclosure and privacy concerns. While older individuals were likely to fear negative implications of PII availability online, younger respondents highlighted uncertainty about online availability of PII as of primary concern. Theoretical relevance of online–offline transferability and the practical significance of these findings to Web site design are discussed.

Protection of Personal Information in User-centric Converged Service Platforms

The so-called User-Generated Services (UGS) provide users with the means to create and share their own advanced services that better fit their needs or those of their communities. Platforms supporting UGS for non-technically skilled users are becoming popular, both in the Internet and the Telecommunications domains. They provide creators with the means to include consumers' personal data or contextual information in order to generate attractive value-added services and also to improve the user-experience. However, the use and release of personal identifiable information poses several privacy and data protection concerns. In this paper we analyze the foreseeable problems and propose a solution for the protection of personal information on a UGS platform.

Semantic Web and Knowledge Management in User Data Privacy

This paper discusses knowledge representation for privacy and accountability issues. Use of personal information from customers is a common practice among companies and governments around the world. Knowing and applying current privacy legislation is an important requirement for IT projects. Inadequate procedures or data breaches can lead to lawsuits and loss of consumer trust for the company [1]. IT project managers are mainly aware of their business goals, but not of specific required actions to assure that the project is privacy-compliant. Security systems are designed to protect data from unauthorized access. On the other hand, privacy systems must empower the user providing control for its own data and limiting access to it. Slightly different from these two approaches there is the perspective of organizations over client data privacy. The main concern on privacy accountability is to handle personal identifiable information in a secure way avoiding misuse. Examples of previous work in this domain are the Rei [2] and DAML Privacy [3] ontologies. This paper 3 illustrates how ontologies can be used to model the mapping of intended actions into corresponding required actions in order to comply with privacy regulations. To this, our modeling approach uses OWL-DL [4]. In our proposed model we refer to agents and targets, similarly to Breaux and Anton [5]. An agent is the accountable part that performs “intended actions” and a target is any object that suffers or is involved in a performed intended action. Under certain specific conditions of each particular intended action, the agent will need to take other actions to be compliant with the privacy policy, which are named “required actions”. As an example consider an organization planning to transfer personal data to another country. In this case the intended action is a transborder data flow. For this kind of action 1 Pontificia Universidade Catolica do Rio Grande do Sul – PUCRS. {douglas.silva,mirian.bruckschen,paulo.bridi,roger.granada}@cpph.pucr s.br, {alexandre.agustini, renata.vieira}@pucrs.br 2 Hewlett-Packard – HP. {caio.northfleet, prasad.rao, tomas.sander}@hp.com 3 This paper was achieved in cooperation with Hewlett-Packard Brasil Ltda. using incentives of Brazilian Informatics Law (Law no 8.2.48 of 1991). Semantic Web and Knowledge Management in User Data Privacy 70 RITA • Volume XVI • Numero 2 • 2009 specific regulations apply in the European Union (EU). There are three possible cases: i) the destination country is considered adequate by the EU; ii) the destination country has a special agreement with the EU; iii) or the destination country is considered non adequate by the EU. In the special agreement case, illustrated here, it is necessary to verify if the target company has signed the special agreement. Next, an ontology excerpt that models this restriction is presented: Figure 1. OWL-DL concepts and properties modeling a subset of the privacy domain. Instances of concepts presented in Figure 1 given as an example of transborder data flow are: Organization X, Subsidiary Y, EU, Spain, USA and Safe Harbor. They are instances of Agent, Target, Geo and Agreement, respectively. In the example, Organization X is located in Spain, Subsidiary Y is located in USA and Organization X performs a transborder data flow to Subsidiary Y. Also, USA has a Safe Harbor agreement, which is an agreement with EU. Having these assertions in the ontology, some inferences can be made: Safe Harbor is classified as an EU Agreement and USA is inferred as EU Non Adequate with Agreement. The required action for case (ii) is defined by a rule. It states that if an agent located in the EU performs a transborder data flow to a non adequate country with agreement then the agent must ensure that the target has signed the agreement. In our future work, we plan to develop a model for privacy assessment as a way to guide managers on being compliant with customers’ data privacy.

RAISING AWARENESS: AN EXAMINATION OF EMBEDDED GPS DATA IN IMAGES POSTED TO THE SOCIAL NETWORKING SITE TWITTER

We live in a society that depends heavily on the use of technology, specifically the Internet, to complete our daily activities and to stay in touch with friends and family. Perhaps one of the most potentially dangerous activities on the Internet is keeping in touch with others via social media, or social networking sites. This exploratory study examined personally identifiable information (PII), of photos uploaded to TwitPic. A total of 417,056 images were downloaded and processed for the study. The data collected from the TwitPic photos will uncover the GPS location information embedded in the photo’s header, as well as, the possible impacts of that information on the user.

K-automorphism

The growing popularity of social networks has generated interesting data management and data mining problems. An important concern in the release of these data for study is their privacy, since social networks usually contain personal information. Simply removing all identifiable personal information (such as names and social security number) before releasing the data is insufficient. It is easy for an attacker to identify the target by performing different structural queries. In this paper we propose k-automorphism to protect against multiple structural attacks and develop an algorithm (called KM) that ensures k-automorphism. We also discuss an extension of KM to handle "dynamic" releases of the data. Extensive experiments show that the algorithm performs well in terms of protection it provides.

PCI and Beyond - How to Secure Data in the Most Cost Effective Manner

The Payment Card Security Industry Data Security Standard (PCI DSS), US State and federal laws encourage and require businesses to encrypt consumers' computerized personal information and payment data. Most state data breach notice laws do not require businesses to notify their customers when customers' digital personal information has been stolen or lost if the information was encrypted. A motivating factor that prompted many companies to implement data at rest encryption was the large amount of negative media attention garnered by stories of lost or stolen data. The type of asset compromised most frequently is online data. An alternative method of analyzing these results is to examine the number of records of sensitive data compromised for each asset. This view shows the same conclusion. This fact may be surprising to some given the frequent public reports of massive amounts of data at risk from lost or stolen laptops, back-up tapes, and other media. Postponing some IT security projects could lead to risky business behaviors. Dealing with a breach is more expensive than preventing one. Regulations are requiring tighter security for more of your business information and organizations must learn how to protect their business information. PCI and PII (Personally Identifiable Information) data can be secured in the most cost effective manner by following the guidance in this article. The case study in this article is about an Enterprise Data Security project that addresses key areas of focus for file and database security encompassing all major platforms.