ENhancing seCurity and privAcy in the Social wEb

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Michael Sirivianos

01 January 2016

31 December 2019

EC funded project

ENCASE (ENhancing seCurity and privAcy in the Social wEb) aims at leveraging the latest advances in usable security and privacy to design and implement a browser-based architecture for the protection of minors from malicious actors in online social networks (OSNs). The ENCASE user-centric architecture consists of three distinct services, which can be combined to form an effective protective net against cyberbullying, sexually abusive acts and fake activity: a) a browser add-on with its corresponding intelligent web-proxy and scalable back-end software stack that collects the users” online actions to unveil incidents of aggressive or distressed behavior; b) a browser add-on with its associated web-proxy and back-end software stack that analyses social web data to detect fraudulent and fake activity and alert the user; and c) a browser add-on that detects, together with the intelligent web-proxy, when a user is about to share sensitive content with inappropriate audiences and protects it. The third add-on has usable controls that enable users to protect their content by suggesting suitable access lists, by watermarking, and by securing the content via cryptography or steganography.

The foundation of the research and innovation activities is a diligently planned inter-sectorial and interdisciplinary secondment program for Experienced Researchers (ER) and Early Stage Researchers (ESR) that fosters knowledge exchange. Our main focus is the empowerment of minors or their adult supervisors with parental control tools that unveil malicious social web information or online actors, and enable users to easily protect their sensitive content from unwarranted access by unscrupulous OSN users.

The main knowledge transfer & training objectives of the ENCASE project are: a) to foster industry-academia cooperation, aiming at creating a long-term inter-sectorial cooperation program in the area of security and privacy in OSNs with an emphasis on the protection of minors; b) to implement a dense program of exchanges of ERs and ESRs for the purpose of knowledge exchange and strengthening of collaboration among academia; and c) to conduct world-class interdisciplinary research in the intersection of user experience design, data mining and, and security and privacy.

The main research and innovation objectives of the ENCASE project are: a) to understand the security and privacy concerns of OSN; b) to research methods for performing user profiling, as well as sentiment and affective analysis in OSNs; c) to design algorithms and machine learning (ML) techniques that detect malicious behavior and fake activity in OSNs and warn the users or their custodians of when they are being or are about to be subjected to such online abuses; and d) to design effective content protection mechanisms by employing watermarking, steganography, and advanced encryption techniques.

The academic partners contribute know-how on user experience assessment, large scale data processing, machine learning and data-mining algorithm design, and content confidentiality techniques. The industrial partners primarily offer expertise in production-grade software development, access to real-world online social network data and access to numerous end-users through widely deployed products.

ENCASE is funded by the European Commission’s Horizon 2020 Research and Innovation Framework program under the Marie Skłodowska-Curie Research and Innovation Staff Exchanges Action, Grant Agreement No. 691025.


Vertical Category:


Deliverable D8.2 “Dissemination, Commercialization and IP Protection Activities (a)”
Deliverable D6.3: “Implementation of browser add-on for content detection and protection”
Deliverable D6.2: “Development of content protection techniques that use steganography, encryption and watermarking”
Deliverable D6.1: “Design and implementation of in-browser content analysis filter”
Deliverable D5.2 “Implementation of browser add-on that detects false information and fake identities in OSN”
Deliverable D5.1 “Software libraries built on Graphos.ml for detection of fake activity in large scale OSNs”
Deliverable D4.3 “Implementation of browser add-on that detects distressed or aggressively behaving users”
Deliverable D4.2 “Software libraries built on Graphos.ml using data mining for the detection of aggressive or distressed behaviors in OSN”
Deliverable D4.1 “Development of Automated Techniques to Detect Early Indications of Malicious Behavior of Social Network Users”
Deliverable D3.2 “Development of accurate and sophisticated sentiment analysis approaches”
Deliverable D3.1 “Report on user and societal aspects, and on usability of security and privacy OSN systems”
Deliverable D2.2 “System Requirements and Software Architecture”
Deliverable D2.1 “System Requirements and Software Architecture”