Drone Swarm Security

Introduction

Drone swarms coordinate multiple UAVs. Security presents unique challenges.

Architectures

Centralized

Single ground station controls all. Simple, single point of failure.

Distributed

Peer-to-peer, collective decisions. Resilient but complex.

Hierarchical

Leaders coordinate subsets. Balanced approach.

Mesh

Ad-hoc mesh network. Multi-hop, self-healing.

Distributed Security

Consensus

Byzantine fault tolerance handles malicious nodes.

Trust Models

• Centralized: ground vouches
• Web of trust: neighbors vouch
• Reputation: behavior history
• Zero-trust: verify all

Secure Voting

Authenticated votes, correct tallying.

Vulnerabilities

Sybil

Fake identities overwhelm systems. Counter: attestation.

Wormhole

Tunneled messages disrupt topology. Detection via timing.

Sinkhole

Malicious node attracts traffic. Multipath routing.

Desynchronization

Timing attacks disrupt coordination. Authenticated PTP.

Cascade

Compromised drone causes neighbors to fail. Isolation needed.

Attack Scenarios

Coordinated Jamming

Distributed jammers create mobile DoS.

Distributed Spoofing

Multiple spoofers create false environment.

Swarm Hijacking

Compromise leaders to redirect swarm.

Collision Induction

Manipulate positions to cause crashes.

Defense

Secure Routing

• SAODV
• ARAN
• SRP

IDS

Distributed intrusion detection.

Self-Healing

Reconfigure around compromised nodes.

Redundancy

Distribute critical functions.

Heterogeneity

Mixed types reduce attack surface.

Key Management

Group Keys

Single key shared. Efficient but risky.

Pairwise

Unique per pair. Secure but O(n²).

Threshold

k-of-n collaboration required.

Emerging

Blockchain

Distributed ledger for decisions.

Federated Learning

Collaborative ML without raw data.

Conclusion

Swarm security needs distributed trust, secure routing, self-healing. Evolve with threats.