Dynamic and Secure Public Auditing of User Data in Cloud by Using IRSAC

Background: Cloud storage is generally used to provide on-demand services with sufficient scalability in an efficient network environment, and various encryption algorithms are typically applied to protect the data in the cloud. However, it is non-trivial to obtain the original data after encryption and efficient methods are needed to access the original data. Methods: In this paper, we propose a new user-controlled and efficient encrypted data sharing model in cloud storage. It preprocesses user data to ensure the confidentiality and integrity based on triple encryption scheme of CP-ABE ciphertext access control mechanism and integrity verification. Moreover, it adopts secondary screening program to achieve efficient ciphertext retrieval by using distributed Lucene technology and fine-grained decision tree. In this way, when a trustworthy third party is introduced, the security and reliability of data sharing can be guaranteed. To provide data security and efficient retrieval, we also combine active user with active system. Results: Experimental results show that the proposed model can ensure data security in cloud storage services platform as well as enhance the operational performance of data sharing. Conclusion: The proposed security sharing mechanism works well in an actual cloud storage environment.

Download Full-text

Tracing or Tracking? A Preliminary Analysis of COVID-19 Outbreak Tracker Apps on Android and User Privacy (Preprint)

10.2196/preprints.19662 ◽

2020 ◽

Author(s):

Alex Akinbi ◽

Ehizojie Ojie

Keyword(s):

Preliminary Analysis ◽

Service Providers ◽

User Participation ◽

Memory Storage ◽

Phone Call ◽

Contact Tracing ◽

Privacy Rights ◽

User Privacy ◽

Android Apps ◽

User Data

BACKGROUND Technology using digital contact tracing apps has the potential to slow the spread of COVID-19 outbreaks by recording proximity events between individuals and alerting people who have been exposed. However, there are concerns about the abuse of user privacy rights as such apps can be repurposed to collect private user data by service providers and governments who like to gather their citizens’ private data. OBJECTIVE The objective of our study was to conduct a preliminary analysis of 34 COVID-19 trackers Android apps used in 29 individual countries to track COVID-19 symptoms, cases, and provide public health information. METHODS We identified each app’s AndroidManifest.xml resource file and examined the dangerous permissions requested by each app. RESULTS The results in this study show 70.5% of the apps request access to user location data, 47% request access to phone activities including the phone number, cellular network information, and the status of any ongoing calls. 44% of the apps request access to read from external memory storage and 2.9% request permission to download files without notification. 17.6% of the apps initiate a phone call without giving the user option to confirm the call. CONCLUSIONS The contributions of this study include a description of these dangerous permissions requested by each app and its effects on user privacy. We discuss principles that must be adopted in the development of future tracking and contact tracing apps to preserve the privacy of users and show transparency which in turn will encourage user participation.

Download Full-text

Afterword

The Oxford Handbook of Social Media and Music Learning ◽

10.1093/oxfordhb/9780190660772.013.41 ◽

2020 ◽

pp. 680-683

Author(s):

Janice L. Waldron ◽

Stephanie Horsley ◽

Kari K. Veblen

Keyword(s):

Social Media ◽

Media Use ◽

Careful Selection ◽

Social Media Use ◽

Pedagogical Tools ◽

The Future ◽

User Data ◽

Selection Of ◽

Data Surface

We all feel the implications of the force of social media—for good and for ill—in our lives and in our professional world. At the time of this writing, Facebook continues with its struggle to “clean up its act” as more revelations surrounding breaches of trust and hacked user data surface in the news and various countries attempt to hold Facebook to account. Despite this, social media use continues to grow exponentially, and the potential for responsible, ethical, and transparent social media to transform the ways in which we interact with and learn from each other increase with it. As we wait to see what the future holds for social media in society, we are reminded once again that it is the careful selection of pedagogical tools such as social media, as well the guided awareness of the challenges and benefits of those tools, that remains constant, even as tools may change, disappear, or fall out of fashion.

Download Full-text

Big data for climate action or climate action for big data?

Big Data & Society ◽

10.1177/2053951720982032 ◽

2021 ◽

Vol 8 (1) ◽

pp. 205395172098203

Author(s):

Maria I Espinoza ◽

Melissa Aronczyk

Keyword(s):

Big Data ◽

Environmental Sustainability ◽

Global Climate ◽

Intergovernmental Organizations ◽

Address Climate Change ◽

Data Practices ◽

Climate Action ◽

User Data ◽

Climate Crisis ◽

Depth Interviews

Under the banner of “data for good,” companies in the technology, finance, and retail sectors supply their proprietary datasets to development agencies, NGOs, and intergovernmental organizations to help solve an array of social problems. We focus on the activities and implications of the Data for Climate Action campaign, a set of public–private collaborations that wield user data to design innovative responses to the global climate crisis. Drawing on in-depth interviews, first-hand observations at “data for good” events, intergovernmental and international organizational reports, and media publicity, we evaluate the logic driving Data for Climate Action initiatives, examining the implications of applying commercial datasets and expertise to environmental problems. Despite the increasing adoption of Data for Climate Action paradigms in government and public sector efforts to address climate change, we argue Data for Climate Action is better seen as a strategy to legitimate extractive, profit-oriented data practices by companies than a means to achieve global goals for environmental sustainability.

Download Full-text