Muslum Ozgur Ozmen, Habiba Farrukh, Hyungsub Kim, Antonio Bianchi, Z. Berkay Celik (Purdue University)

Drone swarms are becoming increasingly prevalent in important missions, including military operations, rescue tasks, environmental monitoring, and disaster recovery. Member drones coordinate with each other to efficiently and effectively accomplish a given mission. To automatically coordinate a swarm, member drones exchange critical messages (e.g., their positions, locations of identified obstacles, and detected search targets) about their observed environment and missions over wireless communication channels. Therefore, swarms need a pairing system to establish secure communication channels that protect the confidentiality and integrity of the messages. However, swarm properties and the open physical environment in which they operate bring unique challenges in establishing cryptographic keys between drones.

In this paper, we first outline an adversarial model and the ideal design requirements for secure pairing in drone swarms. We then survey existing human-in-the-loop-based, context-based, and public key cryptography (PKC) based pairing methods to explore their feasibility in drone swarms. Our exploration, unfortunately, shows that existing techniques fail to fully meet the unique requirements of drone swarms. Thus, we propose research directions that can meet these requirements for secure, energy-efficient, and scalable swarm pairing systems.

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] => 13421 ) )

Automata-Based Automated Detection of State Machine Bugs in Protocol...

Paul Fiterau-Brostean (Uppsala University, Sweden), Bengt Jonsson (Uppsala University, Sweden), Konstantinos Sagonas (Uppsala University, Sweden and National Technical University of Athens, Greece), Fredrik Tåquist (Uppsala University, Sweden)

Read More

Assessing the Impact of Interface Vulnerabilities in Compartmentalized Software

Hugo Lefeuvre (The University of Manchester), Vlad-Andrei Bădoiu (University Politehnica of Bucharest), Yi Chen (Rice University), Felipe Huici (Unikraft.io), Nathan Dautenhahn (Rice University), Pierre Olivier (The University of Manchester)

Read More

OBSan: An Out-Of-Bound Sanitizer to Harden DNN Executables

Yanzuo Chen (The Hong Kong University of Science and Technology), Yuanyuan Yuan (The Hong Kong University of Science and Technology), Shuai Wang (The Hong Kong University of Science and Technology)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)