TY - GEN
T1 - ProtoEval
T2 - 38th International Conference on Software Engineering and Knowledge Engineering, SEKE 2026
AU - Tang, Zihan
AU - Chen, Sini
AU - Xiao, Lili
AU - Xu, Lang
AU - Zhu, Huibiao
N1 - Publisher Copyright:
© 2026 Knowledge Systems Institute Graduate School. All rights reserved.
PY - 2026
Y1 - 2026
N2 - Internet of Things (IOT) authentication protocols continuously evolve through structural revisions, including message consolidation and gateway rerouting, to satisfy shifting deployment constraints. Consequently, the engineering challenge transitions from establishing baseline correctness to managing trade-offs among reliability, attack exposure, and communication overhead. However, existing formal methods typically evaluate single protocol versions, treating verification as isolated proofs rather than continuous regression assessments. To bridge this gap, we propose ProtoEval, a family-based dual-verification framework to systematically quantify evolutionary regressions. By introducing a shared milestone semantics, ProtoEval seamlessly integrates qualitative state-space exploration with quantitative probabilistic boundary analysis. We formalize eight reusable evolution operators and evaluate a controlled protocol family comprising twelve base-variant pairs across diverse industry-standard architectures. The evaluation reveals highly protocol-dependent regression behaviors. For example, message consolidation significantly improves success rates in multi-round handshakes but yields marginal benefits in compact protocols, while cryptographic agility consistently acts as a Pareto improver. Validation against complex, real-world protocol evolution chains confirms the framework's directional fidelity and compositional accuracy. Ultimately, this approach reframes formal verification, transforming protocol models from disposable proofs into reusable engineering assets to guide comparative design decisions in evolving IoT ecosystems.
AB - Internet of Things (IOT) authentication protocols continuously evolve through structural revisions, including message consolidation and gateway rerouting, to satisfy shifting deployment constraints. Consequently, the engineering challenge transitions from establishing baseline correctness to managing trade-offs among reliability, attack exposure, and communication overhead. However, existing formal methods typically evaluate single protocol versions, treating verification as isolated proofs rather than continuous regression assessments. To bridge this gap, we propose ProtoEval, a family-based dual-verification framework to systematically quantify evolutionary regressions. By introducing a shared milestone semantics, ProtoEval seamlessly integrates qualitative state-space exploration with quantitative probabilistic boundary analysis. We formalize eight reusable evolution operators and evaluate a controlled protocol family comprising twelve base-variant pairs across diverse industry-standard architectures. The evaluation reveals highly protocol-dependent regression behaviors. For example, message consolidation significantly improves success rates in multi-round handshakes but yields marginal benefits in compact protocols, while cryptographic agility consistently acts as a Pareto improver. Validation against complex, real-world protocol evolution chains confirms the framework's directional fidelity and compositional accuracy. Ultimately, this approach reframes formal verification, transforming protocol models from disposable proofs into reusable engineering assets to guide comparative design decisions in evolving IoT ecosystems.
KW - Formal Verification
KW - IoT Security
KW - Probabilistic Model Checking
KW - Protocol Evolution
KW - Trade-off Analysis
UR - https://www.scopus.com/pages/publications/105050574369
U2 - 10.18293/SEKE2026-061
DO - 10.18293/SEKE2026-061
M3 - 会议稿件
AN - SCOPUS:105050574369
T3 - Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
SP - 140
EP - 145
BT - Proceedings - SEKE 2026
PB - Knowledge Systems Institute Graduate School
Y2 - 1 October 2026 through 7 October 2026
ER -