Our research will include studying privacy preservation mechanisms in big data and presenting the challenges for existing mechanisms. Besides, the research endeavors to improve existing data protection methods and develop new scalable data protection techniques for big-data focusing particularly on big-data hosting, analysis, and processing in the cloud. The project will develop novel privacy and secrecy preserving techniques for the analysis of big data in the cloud and novel protection techniques ensuring the confidentiality and integrity of big-data. Moreover, the research will develop novel techniques for secure transformation and processing of big data in the cloud without compromising privacy or confidentiality and securely perform privacy-preserving analysis of significant open data without compromising the secrecy of the analysis.
Particular emphasis will be placed on ensuring compliance with European cyber-security directive and with regulatory requirements and recommendations for privacy data protection as well as ensuring alignment with the European Cloud strategy.
Sharing Cyber Threat Intelligence (CTI) is a key strategy for improving cyber defense, but there are risks of breaching regulations and laws regarding privacy. With regulations such as the General Data Protection Regulation (GDPR) that are designed to protect citizens’ data privacy, the managers of CTI datasets need clear guidance on how and when it is legal to share such information. This paper defines the impact that GDPR legal aspects may have on the sharing of CTI. In addition, we define adequate protection levels for sharing CTI to ensure compliance with the GDPR. We also present a model for evaluating the legal requirements for supporting decision making when sharing CTI, which also includes advice on the required protection level. Finally, we evaluate our model using use cases of sharing CTI datasets between entities.