Privacy policies can be an effective communicative tool, building up consumer trust in an organisation by communicating that organisation’s privacy practices. However, many privacy policies are long and complex, obfuscated by legal jargon and vague clauses. How can we ensure that privacy policies retain their communicative power and harness it for good? By developing a framework for analysing organisations’ privacy policies through Deep Learning techniques, the TRUST aWARE project aims to enhance consumer trust when faced with confusing privacy policies, allowing consumers to better distinguish the trustworthy from the untrustworthy.
The ability to identify the author responsible for a piece of software is critical for many research studies and for enhancing software transparency and accountability. However, as opposed to other application markets like iOS, attribution in the Android ecosystem is known to be hard. Android app authors can, either intentionally or by mistake, hide their true identity. A recent study based on the analysis of 2.5 million market entries from 5 Android markets explores the availability, volatility, and overall aptness of publicly available metadata for author attribution in Android app markets.
As 2023 begins, can we predict what new and emerging cybersecurity threats individuals, businesses, and governments are going to face? How can we prepare for such threats and what tools can be used to combat them?
Can dynamic and static analysis techniques be used to audit and certify the privacy behaviors of IoT products and their regulatory compliance? What are the technical and methodological barriers that must be overcome in order to do this?
Cybersecurity and its interaction with the users are yet to be widely explored. Despite existing reports and researches about cyberthreats in the field, there is still much work to be done to secure one’s activity online. The below information frames the definition of cybersecurity tools and its impact on general population.
As already established, a GDPR Certification is the optimal solution to ensure compliance with legal requirements and inspire confidence in data processing activities. Nonetheless, choosing a suitable certification scheme that will ensure the goals are sufficiently met is not always an easy process. In this context, Europrivacy is the certification scheme that offers precisely those benefits necessary leading to an effective GDPR certification.
Following the adoption of the General Data Protection Regulation (GDPR), the importance of data protection and privacy is constantly increasing both for EU citizens and entreprises operating in the Union. In this privacy-centric environment, we present how and why a GDPR certification is an optimal solution to demonstrate compliance and increase trust in a business’ operations.
Natural language texts are still a relatively unexplored data source in the quest for digital privacy. Leveraging this, we present an automatic labelling of texts related to Android apps. This framework relies on state-of-the-art Natural Language Processing (NLP) and deep learning techniques and will be accessible from a user-friendly dashboard.
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