Analyzing Privacy Policies Based on a Privacy-Aware Profile: The Facebook and LinkedIn Case Studies

Software Quality Control (SQC) techniques are widely used throughout the software development process with the objective of assessing and detecting anomalies that affect the quality of an information system. Privacy is one quality attribute of software systems for which several SQC techniques have been proposed in recent years. However, research has been carried out from different perspectives and, consequently, it has led to a growing body of knowledge scattered across different domains. To bridge this gap, we have carried out a systematic mapping study to provide practitioners and researchers with an overview of the state-of-the-art techniques to carry out software quality control of information systems focusing on aspects of privacy. Our results show a steady growth in the research efforts in this field. The European General Data Protection Regulation seems to have a significant influence on this growth, since 37% of techniques that focus on assessing compliance derive their assessment criteria from this legal framework. The maturity of the techniques varies between the type of technique: Formal verification techniques exhibit the lowest level of maturity while the combination of techniques has demonstrated its successful application in real-world scenarios. The latter seems a promising avenue of research as it provides better results in terms of coverage, precision and effectiveness than the application of individual, isolated techniques. In this paper, we describe the existing SQC techniques focusing on privacy and provide a suitable basis for identifying future research directions.

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“…[41]- [44]), privacy policies (e.g. [45]- [47]), business processes (e.g. [48]- [50]), network protocols (e.g.…”

Section: Inclusion and Exclusion Proceduresmentioning

confidence: 99%

A Systematic Mapping Study on Software Quality Control Techniques for Assessing Privacy in Information Systems

2020

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“…A few hours before of her death, she tweeted, ''Have the house to myself everybody gone'' [8]. Therefore, the posted information in online may cause the user in danger [9]- [11].…”

Section: Introductionmentioning

confidence: 99%

Reliable Decision Making of Accepting Friend Request on Online Social Networks

et al. 2018

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Online social network (OSN) is a platform, where users are able to share information among them easily and instantly. The sensitive information of an user can be misused by his/her friends or friends of friends due to the lack of reliable friend request acceptance (FRA), which is one of the key issues in OSNs. The existing FRA techniques are functioning based on either blind (i.e., without knowing information of a user, who sends the friend request to become a new friend, referred to as friend-to-be) or manual search method. Although, in the second method, the OSN user accepts a new friend based on his/her profile, however, it is not guaranteed that the profile is not fake. A approach is to bring down the misused information by filtering FRA using a reliable method to find out more information about the friend-to-be. This paper has proposed such a method for reliable decision making (RDM) of accepting friend request on OSNs in order to identify the attributes of a friend-to-be. RDM is a function with several parameters, such as security, flexibility, effectiveness, and satisfaction. To prove the reliability of the proposed method, an extensive quantitative study was carried out, which results indicated user's preferences for proposed method compared with the existing FRA methods.INDEX TERMS Friend request acceptance, online social networks (OSNs), reliable decision making.

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“…As suggested in Fig. 1, a RSL-IL4Privacy policy is represented as a set of privacy Statements and other related constructs such as Services, Recipients, Private Data and Enforcements (Caramujo and Silva, 2015). The Statement is the key concept of the privacy-aware profile.…”

Section: Rslingo and Rsl-il4privacymentioning

confidence: 99%

“…Each attribute of X receives a value from a feature function that associates such attribute with a possible label. Each feature holds a weight that represents its strength for the proposed label (Ceri et al, 2013): positive values mean a good association between the function and the label, negative values mean otherwise, and a value of 0 means that the feature function does not have an influence on the label identification. In short, CRFs provide a powerful and flexible mechanism for exploiting arbitrary feature sets along with dependency in the labels of neighbouring words (Sarawagi, 2008).…”

Section: Automatic Text Extractionmentioning

confidence: 99%

“…It is also noteworthy that one Statement may refer several services and several privacy data (Service and PrivateData elements respectively). Each Statement can be classified into five different categories, according to its purpose (Caramujo and Silva, 2015): Collection (which data is collected); Disclosure (which data is disclosed and to what parties); Retention (how long data will be stored); Usage (what is the purpose of having the data); and Informative (with just generic information). This approach has been supported by an Eclipse plugin, called "RSLingo4Privacy Studio" and available from its GitHub repository (https://github.com/ RSLingo/RSLingo4Privacy).…”

Section: Rslingo and Rsl-il4privacymentioning

confidence: 99%

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An Evaluation of the Challenges of Multilingualism in Data Warehouse Development

Dediź

Stanier

2016

Proceedings of the 18th International Conference on Enterprise Information Systems

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ICEIS 2016 received 257 paper submissions from 42 countries in all continents, which makes it one of the largest conferences in the World in the area of Information Systems, thus demonstrating the success and global dimension of this conference. From these, 42 papers were selected for publication and presentation at the Conference as full papers. These numbers, leading to a full-paper acceptance ratio of 16%, show the intention of preserving a high quality forum for this conference, a quality that we intend to maintain in the future, for the next editions of this conference.The high number and high quality of the received papers imposed difficult choices in the selection process. To evaluate each submission, a double blind paper review was performed by the Program Committee, whose members are highly qualified researchers in ICEIS topic areas.All presented papers will be available at the SCITEPRESS Digital Library and will be submitted for indexation by Thomson Reuters Conference Proceedings Citation Index (ISI), INSPEC, DBLP, EI (Elsevier Index) and Scopus.Additionally, a short list of presented papers will be selected to be expanded into a forthcoming book of ICEIS 2016 Selected Papers to be published by Springer in the LNBIP Series.The technical program of the conference included a panel and 4 invited talks delivered by internationally distinguished speakers, namely: Claudia Loebbecke (University of Cologne, Germany), Sergio Gusmeroli (TXT e-solutions SPA, Italy), Wil Van Der Aalst (Technische Universiteit Eindhoven, Netherlands) and Jan Vom Brocke (University of Liechtenstein, Liechtenstein). Their participation positively contributes to reinforce the overall quality of the Conference and to provide a deeper understanding of the fields addressed by the conference.Moreover, ICEIS 2016 had a Doctoral Consortium on Enterprise Information Systems and 1 tutorial. We are thankful to the Conference Co-chairs (Olivier Camp and José Cordeiro) and Program Co-chairs (Slimane Hammoudi, Leszek Maciaszek and Michele M. Missikoff) for their dedication and hard work in organizing these events.We sincerely thank all the authors for their submissions and participation in ICEIS 2016. Furthermore, we would like to thank all the members of the program committee and reviewers, who helped us with their expertise, dedication and time. We would also like to thank the invited speakers for their excellent contribution in sharing their knowledge and vision and the workshop/special session chairs whose collaboration with ICEIS 2015 was much appreciated. Finally, we gratefully acknowledge the professional support of the ICEIS 2016 team for all organizational processes. XIIIWe hope that all colleagues find this a fruitful and inspiring conference. We hope to contribute to the development of the Enterprise Information Systems community and look forward to having additional research results presented at the next edition of ICEIS, details of which are available at http://www.iceis.org. Slimane Hammoudi University of Cologne, GermanyAbstract:...

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Analyzing Privacy Policies Based on a Privacy-Aware Profile: The Facebook and LinkedIn Case Studies

Cited by 15 publications

References 7 publications

A Systematic Mapping Study on Software Quality Control Techniques for Assessing Privacy in Information Systems

A Systematic Mapping Study on Software Quality Control Techniques for Assessing Privacy in Information Systems

Reliable Decision Making of Accepting Friend Request on Online Social Networks

An Evaluation of the Challenges of Multilingualism in Data Warehouse Development

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