Shuwen Liu (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China), George C. Polyzos (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China and ExcID P.C., Athens, Greece)

We design a privacy-preserving data proxy mechanism within the FIWARE Data Space framework, utilizing searchable encryption to ensure metadata confidentiality. The system is engineered to enable secure and efficient data querying, hiding the queries from the proxy and other data in the proxy from the querying agent. Recognizing the necessity of regulatory compliance, this paper integrates GDPR compliance modules into the FIWARE Data Space architecture, addressing data collection, storage, sharing, and erasure processes to enhance global applicability and regulatory adherence. In essence, we preserve metadata privacy. Experimental evaluations demonstrate the feasibility of the proposed query privacy mechanisms, focusing on metadata confidentiality and system scalability in data-intensive environments.

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SketchFeature: High-Quality Per-Flow Feature Extractor Towards Security-Aware Data Plane

Sian Kim (Ewha Womans University), Seyed Mohammad Mehdi Mirnajafizadeh (Wayne State University), Bara Kim (Korea University), Rhongho Jang (Wayne State University), DaeHun Nyang (Ewha Womans University)

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Securing BGP ASAP: ASPA and other Post-ROV Defenses

Justin Furuness (University of Connecticut), Cameron Morris (University of Connecticut), Reynaldo Morillo (University of Connecticut), Arvind Kasiliya (University of Connecticut), Bing Wang (University of Connecticut), Amir Herzberg (University of Connecticut)

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