YAYING WU

Dr. YAYING WU


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 October 2026 in Sensors
Verified
Journal Article
Open access
PDF file
WLWeifeng Long
Weifeng Long
YQYunyun Qu
Yunyun Qu
YWYAYING WU
YAYING WU
ZYZi ran Yan
Zi ran Yan
NWNa Wang
Na Wang
Identity-based multi-proxy signatures (IBMPS) enable an original signer to delegate signing authority to multiple proxy signers, who jointly sign a common message on the original signer’s behalf using their identity-associated private keys. This supports authenticated collaborative reporting in unmanned aerial vehicle (UAV)-assisted rescue. We propose an IBMPS scheme for this application and a security model that captures adaptive queries and signer collusion. Under the computational Diffie–Hellman (CDH) assumption and the collision resistance of H^2 and H^3, we prove unforgeability for the three forgery scenarios of Game 1 in the standard model (SM), with explicit reduction bounds and no public-key replacement. We also analyze long-term private-key recovery under proxy signing-key exposure, assuming an honestly generated target public key that remains unchanged. The scheme verifies individual partial signatures before aggregation, while final verification requires a constant number of pairings and scalar multiplications; signer-list processing still depends on group size. Under historical benchmark timings and the adopted operation counts, with ten proxy signers, the estimated total computational cost is 19.34–44.00% lower than that of five of the six baseline schemes, and the estimated final verification cost is 50.26–74.06% lower than that of all six. Under the adopted encoding assumptions, the 20-byte long-term private-key representation is the smallest among the compared schemes, the 276-byte per-proxy delegation ties for the smallest, and the 532-byte final signature matches that of Shin et al.’s scheme. The cost figures are model-based estimates, and the byte counts are per-object representation sizes rather than complete end-to-end communication costs.