Nicolas Quero (Expleo France), Aymen Boudguiga (CEA LIST), Renaud Sirdey (CEA LIST), Nadir Karam (Expleo France)

Platooning is an upcoming technology which aims at improving transportation by allowing a leading human-driven vehicle to automatically guide multiple trucks to their respective destinations, saving driver time, improving road efficiency and reducing gas consumption. However, efficient linkage of trucks to platoons requires the centralization and processing of business-critical data which truck operators are not willing to disclose. In order to address these issues, we investigate how homomorphic encryption can be used at the core of a protocol for privately linking a vehicle to a nearby platoon without disclosing its location and destination. Furthermore, we provide experimental results illustrating that such protocols achieve acceptable performances and latencies at practical platoon database scales (serving around 500 simultaneous clients on a single platooning server processor core with sub second latency over databases of up to ≈60000 platoons scattered among over 250 destinations).

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 66 [1] => 68 ) ) ) [post__not_in] => Array ( [0] => 13426 ) )

Learning Automated Defense Strategies Using Graph-Based Cyber Attack Simulations

Jakob Nyber, Pontus Johnson (KTH Royal Institute of Technology)

Read More

WIP: A First Look At Employing Large Multimodal Models...

Mohammed Aldeen, Pedram MohajerAnsari, Jin Ma, Mashrur Chowdhury, Long Cheng, Mert D. Pesé (Clemson University)

Read More

Your Router is My Prober: Measuring IPv6 Networks via...

Long Pan (Tsinghua University), Jiahai Yang (Tsinghua University), Lin He (Tsinghua University), Zhiliang Wang (Tsinghua University), Leyao Nie (Tsinghua University), Guanglei Song (Tsinghua University), Yaozhong Liu (Tsinghua University)

Read More

FCGAT: Interpretable Malware Classification Method using Function Call Graph...

Minami Someya (Institute of Information Security), Yuhei Otsubo (National Police Academy), Akira Otsuka (Institute of Information Security)

Read More