Dai H, Sun X, Mao Y N, et al. A Research on Black-box Evaluation Methods for Quantum Key Distribution Networks[J]. Study on Optical Communications, 2025(3): 240165.
Dai H, Sun X, Mao Y N, et al. A Research on Black-box Evaluation Methods for Quantum Key Distribution Networks[J]. Study on Optical Communications, 2025(3): 240165. DOI: 10.13756/j.gtxyj.2025.240165.
A Research on Black-box Evaluation Methods for Quantum Key Distribution Networks
The Quantum Key Distribution Network (QKDN) is the large-scale implementation of Quantum Key Distribution (QKD)
which is typically deployed within optic fiber communication infrastructure networks. Based on the principles of quantum physics
the key distribution process in QKDN is considered to be theoretically absolutely secure. Any unauthorized interference or measurement will destroy the quantum state and be immediately detected
ensuring the security and integrity of communication. However
since quantum state storage technology is not yet mature
the expansion from point-to-point QKD to multi-point-to-multi-point QKDN needs to be realized with the help of classical technologies
which also brings new security threats. Denial-of-Service (DoS) attacks are a common form of attack in classical networks
widely exploited by attackers
and the application layer of QKDN also faces security challenges.
【Methods】
2
The paper proposes an Adaptive Range Threshold (ART) detection method to detect DoS attacks. It automatically adjusts the threshold based on abnormal fluctuations in network traffic patterns
thereby flexibly identifying and responding to DoS attacks.
【Results】
2
Simulation results show that the Detection Success Rate (DSR) of QKDN is effectively improved by the ART-based DoS attack detection method
and the DSR can reach 80% by setting reasonable parameters. Additionally
the network security of the QKDN is measured from two perspectives: delay time and request success rate.
【Conclusion】
2
The paper identifies potential network security threats by setting dynamic thresholds and evaluates network security from multiple dimensions. This provides an effective security assessment method for the actual operation of QKDN and lays the foundation for future development of security defense strategies for quantum information networks.
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references
Sharma A , Kumar A . A Survey on Quantum Key Distribution [C ] // 2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT) . Ghaziabad, India : IEEE , 2019 : 8977649 .
Kuppa A , Grzonkowski S , Asghar M R , et al . Black Box Attacks on Deep Anomaly Detectors [C ] // Proceedings of the 14th International Conference on Availability, Reliability and Security . Canterbury, CA, UK : ACM , 2019 : 1 - 10 .
Ali Alatwi H , Aldweesh A . Adversarial Black-box Attacks Against Network Intrusion Detection Systems: a Survey [C ] // 2021 IEEE World AI IoT Congress (AI-IoT) . Seattle, WA, USA : IEEE , 2021 : 0034 - 0040 .
Lee S , Wi S , Son S . Link: Black-box Detection of Cross-site Scripting Vulnerabilities Using Reinforcement Learning [C ] // Proceedings of the ACM Web Conference 2022 . Lyon, France : ACM , 2022 : 743 - 754 .
Cao Y , Zhao Y , Wang Q , et al . The Evolution of Quantum Key Distribution Networks: On the Road to the Qinternet [J ] . IEEE Communications Surveys & Tutorials , 2022 , 24 ( 2 ): 839 - 894 .
Wu Z , Li W , Liu L , et al . Low-rate DoS Attacks, Detection, Defense, and Challenges: a Survey [J ] . IEEE Access , 2020 , 8 : 43920 - 43943 .
Yue M , Wang H , Liu L , et al . Detecting DoS Attacks based on Multi-features in SDN [J ] . IEEE Access , 2020 , 8 : 104688 - 104700 .
Latah M , Toker L . Minimizing False Positive Rate for DoS Attack Detection: a Hybrid SDN-based Approach [J ] . ICT Express , 2020 , 6 ( 2 ): 125 - 127 .
Ali T E , Chong Y W , Manickam S . Machine Learning Techniques to Detect a DDoS Attack in SDN: a Systematic Review [J ] . Applied Sciences , 2023 , 13 ( 5 ): 3183 .