Crowdsourcing privacy policy analysis: Potential, challenges and best practices

2016 ◽  
Vol 58 (5) ◽  
Author(s):  
Florian Schaub ◽  
Travis D. Breaux ◽  
Norman Sadeh
Keyword(s):  
Best Practices ◽  
Policy Analysis ◽  
Personal Information ◽  
Lessons Learned ◽  
Privacy Policy ◽  
Privacy Policies ◽  
Policy Documents ◽  
Specific Data ◽  
Data Practices ◽  
Research Challenges

AbstractPrivacy policies are supposed to provide transparency about a service's data practices and help consumers make informed choices about which services to entrust with their personal information. In practice, those privacy policies are typically long and complex documents that are largely ignored by consumers. Even for regulators and data protection authorities privacy policies are difficult to assess at scale. Crowdsourcing offers the potential to scale the analysis of privacy policies with microtasks, for instance by assessing how specific data practices are addressed in privacy policies or extracting information about data practices of interest, which can then facilitate further analysis or be provided to users in more effective notice formats. Crowdsourcing the analysis of complex privacy policy documents to non-expert crowdworkers poses particular challenges. We discuss best practices, lessons learned and research challenges for crowdsourcing privacy policy analysis.

Automated Extraction and Presentation of Data Practices in Privacy Policies

2021 ◽  
Vol 2021 (2) ◽  
pp. 88-110
Author(s):  
Duc Bui ◽  
Kang G. Shin ◽  
Jong-Min Choi ◽  
Junbum Shin
Keyword(s):  
User Study ◽  
Personal Information ◽  
Personal Data ◽  
Neural Model ◽  
Automated Analysis ◽  
Entity Recognition ◽  
Automated System ◽  
Privacy Policies ◽  
Fine Grained ◽  
Data Practices

Abstract Privacy policies are documents required by law and regulations that notify users of the collection, use, and sharing of their personal information on services or applications. While the extraction of personal data objects and their usage thereon is one of the fundamental steps in their automated analysis, it remains challenging due to the complex policy statements written in legal (vague) language. Prior work is limited by small/generated datasets and manually created rules. We formulate the extraction of fine-grained personal data phrases and the corresponding data collection or sharing practices as a sequence-labeling problem that can be solved by an entity-recognition model. We create a large dataset with 4.1k sentences (97k tokens) and 2.6k annotated fine-grained data practices from 30 real-world privacy policies to train and evaluate neural networks. We present a fully automated system, called PI-Extract, which accurately extracts privacy practices by a neural model and outperforms, by a large margin, strong rule-based baselines. We conduct a user study on the effects of data practice annotation which highlights and describes the data practices extracted by PI-Extract to help users better understand privacy-policy documents. Our experimental evaluation results show that the annotation significantly improves the users’ reading comprehension of policy texts, as indicated by a 26.6% increase in the average total reading score.

An Analysis of Online Privacy Policies of Fortune 100 Companies

2009 ◽  
pp. 269-283
Author(s):  
Suhong Li
Keyword(s):  
Personal Information ◽  
Online Privacy ◽  
Third Party ◽  
Security Requirements ◽  
Current Status ◽  
Safe Harbor ◽  
Privacy Policy ◽  
Privacy Policies ◽  
Fair Information Practices ◽  
Fortune 100

The purpose of this chapter is to investigate the current status of online privacy policies of Fortune 100 Companies. It was found that 94% of the surveyed companies have posted an online privacy policy and 82% of them collect personal information from consumers. The majority of the companies only partially follow the four principles (notice, choice, access, and security) of fair information practices. For example, most of the organizations give consumers some notice and choice in term of the collection and use of their personal information. However, organizations fall short in security requirements. Only 19% of organizations mention that they have taken steps to provide security for information both during transmission and after their sites have received the information. The results also reveal that a few organizations have obtained third-party privacy seals including TRUSTe, BBBOnline Privacy, and Safe Harbor.

An Analysis of Online Privacy Policies of Fortune 100 Companies

Cyber Crime ◽  
2013 ◽  
pp. 1276-1291
Author(s):  
Suhong Li ◽  
Chen Zhang
Keyword(s):  
Personal Information ◽  
Online Privacy ◽  
Third Party ◽  
Security Requirements ◽  
Current Status ◽  
Safe Harbor ◽  
Privacy Policy ◽  
Privacy Policies ◽  
Fair Information Practices ◽  
Fortune 100

The purpose of this chapter is to investigate the current status of online privacy policies of Fortune 100 Companies. It was found that 94% of the surveyed companies have posted an online privacy policy and 82% of them collect personal information from consumers. The majority of the companies only partially follow the four principles (notice, choice, access, and security) of fair information practices. For example, most of the organizations give consumers some notice and choice in term of the collection and use of their personal information. However, organizations fall short in security requirements. Only 19% of organizations mention that they have taken steps to provide security for information both during transmission and after their sites have received the information. The results also reveal that a few organizations have obtained third-party privacy seals including TRUSTe, BBBOnline Privacy, and Safe Harbor.

scholarly journals From Prescription to Description: Mapping the GDPR to a Privacy Policy Corpus Annotation Scheme

2020 ◽  
Author(s):  
Ellen Poplavska ◽  
Thomas B. Norton ◽  
Shomir Wilson ◽  
Norman Sadeh
Keyword(s):  
Natural Language Processing ◽  
Language Processing ◽  
Specific Information ◽  
Privacy Policy ◽  
Legal Research ◽  
Privacy Policies ◽  
Annotation Scheme ◽  
General Data Protection Regulation ◽  
Data Practices ◽  
General Data

The European Union’s General Data Protection Regulation (GDPR) has compelled businesses and other organizations to update their privacy policies to state specific information about their data practices. Simultaneously, researchers in natural language processing (NLP) have developed corpora and annotation schemes for extracting salient information from privacy policies, often independently of specific laws. To connect existing NLP research on privacy policies with the GDPR, we introduce a mapping from GDPR provisions to the OPP-115 annotation scheme, which serves as the basis for a growing number of projects to automatically classify privacy policy text. We show that assumptions made in the annotation scheme about the essential topics for a privacy policy reflect many of the same topics that the GDPR requires in these documents. This suggests that OPP-115 continues to be representative of the anatomy of a legally compliant privacy policy, and that the legal assumptions behind it represent the elements of data processing that ought to be disclosed within a policy for transparency. The correspondences we show between OPP-115 and the GDPR suggest the feasibility of bridging existing computational and legal research on privacy policies, benefiting both areas.

scholarly journals Assessment of privacy policy compliance for chronic disease management applications in China (Preprint)

2020 ◽  
Author(s):  
Zhenni Ni ◽  
Yiying Wang ◽  
Yuxing Qian
Keyword(s):  
Chronic Disease ◽  
Disease Management ◽  
Information Security ◽  
Chronic Disease Management ◽  
Personal Information ◽  
Average Score ◽  
Privacy Policy ◽  
Privacy Policies ◽  
Security Issues ◽  
Privacy Risks

BACKGROUND With the development of mobile health, chronic disease management applications have brought the possibility of reducing the burden of chronic diseases and also brought huge privacy risks to patients' health data. OBJECTIVE The purpose of the study is to analyze the extent to which chronic disease management apps comply with personal information security regulations. METHODS This article analyzed the privacy policies of 39 popular chronic disease management apps, introduced a scale based on personal information security specifications, and analyzed the compliance of privacy policies from various stages of the information life cycle. RESULTS 26 apps (66.7%) have a privacy policy and the average score of these apps is 39 points. CONCLUSIONS It was found that most chronic disease management apps in China have a privacy policy, but the content expression was ambiguous and unclear, and it did not meet the requirements of regulations. Besides, the security issues at the information destruction stage were ignored by most app vendors.

COVID-19 Contact Tracing: A Review on mHealth Application and HIPPA (Preprint)

2021 ◽  
Author(s):  
Lorna Migiro ◽  
Hossain Shahriar ◽  
Sweta Sneha
Keyword(s):  
Best Practices ◽  
Contact Tracing ◽  
Privacy Policy ◽  
Privacy Policies ◽  
Privacy Concerns ◽  
Privacy Rule ◽  
User Adoption ◽  
New Applications ◽  
Google Play ◽  
The Way

BACKGROUND Contact tracing has been implemented as a necessary tool to slow the spread outbreaks over the years. During the COVID-19 pandemic, the introduction of digital applications has allowed a lot of flexibility regarding transmission by driving more people to testing and quarantine. OBJECTIVE This study discusses contact tracing application usage in COVID-19, compare and analyze them based on HIPPA privacy rule. We also discuss challenges facing these new applications and recommend best practices. METHODS The research sampled top ten applications currently in use. Using Android devices, we downloaded and interacted with apps that had over 100,000 downloads on google play store the way a normal user would. we reviewed their privacy policies and compared them against HIPPAs’ privacy rule and generated a checklist. RESULTS The study interacted and analyzed 10 contact tracing applications, particular attention was paid to how the apps’ privacy policies and Google Play Store app privacy policy descriptions disclosed information. CONCLUSIONS Contact tracing applications have proved to be a fundamental pillar during this pandemic. Aligning this apps with the HIPPA privacy rule is one of the major challenges they face. Privacy concerns, user adoption and perception obstacles have also been associated with this apps. CLINICALTRIAL Not applicable.

Adapting Tactical Military Structures to the Current and Future Operational Environments

2020 ◽  
Vol 26 (1) ◽  
pp. 157-162
Author(s):  
Paul Tudorache ◽  
Lucian Ispas
Keyword(s):  
Best Practices ◽  
Lessons Learned ◽  
Organizational Adaptation ◽  
Common Denominator ◽  
Military Operations ◽  
The Future ◽  
Military Units

AbstractUsing the lessons learned from recent military operations such as Operation Inherent Resolve (OIR) from Syria and Iraq, we proposed to investigate the need for tactical military units to adapt operationally to grapple with the most common requirements specific to current operational environments, but also for those that can be foreseen in the future. In this regard, by identifying the best practices in the field that can be met at the level of some important armies, such as USA and UK, we will try to determine a common denominator of most important principles whose application may facilitate both operational and organizational adaptation necessary for tactical military units to perform missions and tasks in the most unknown future operational environments.

Lecturers’ Role in Design and Implementation of E-Learning Processes

2020 ◽  
pp. 287-298
Author(s):  
Mārtiņš Spridzāns
Keyword(s):  
Best Practices ◽  
Information And Communication Technologies ◽  
English Language ◽  
Communication Technologies ◽  
The State ◽  
Ict In Education ◽  
Policy Documents ◽  
Strategic Approach ◽  
Information And Communication ◽  
E Learning

The potential of Information and Communication Technologies (ICT) is playing increasing role in various pedagogical contexts. The necessity to integrate technologies in learning enhances educators’ digital competences is constantly highlighted in education policy documents European Union and national strategic documents and recommendations. Following the advance of digital technologies, the State Border Guard College of Latvia is constantly looking after innovations in ICT and education contexts. Since 2011 Specialized English language e-learning course for border guards is being implemented, other professional e-learning courses are being systematically introduced, currently 8 specialised qualification courses are available, on average 300 border guards graduate e-learning courses annually. Having in mind the continuous advancement of ICT in education contexts as well as the strategic approach of the State Border Guard College to continue the development of e-learning systems author of this article intends to describe the system of e-learning used in border guards’ training, explore and summarize the theory and best practices on using ICT in pedagogical context, educators’ roles in development and implementation of e-learning courses.

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