基于预约束加密的可追溯加密恶意流量检测

张迪; 王皓; 张颖; 乐俊青; 廖晓峰

doi:10.12263/DZXB.20251051

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基于预约束加密的可追溯加密恶意流量检测

密态网络安全前沿技术 | 更新时间：2026-07-30

- 基于预约束加密的可追溯加密恶意流量检测
- A Traceable and Encrypted Malicious Traffic Detection Scheme Based on Set Pre-Constrained Encryption
- 电子学报 2026年54卷第4期页码：1481-1496
- 作者机构：
  
  重庆大学计算机学院，重庆 400044
- 作者简介：
  
  张迪女，1993年11月出生于贵州省毕节市。现为重庆大学计算机学院副教授、硕士生导师。主要研究方向为隐私保护、区块链、应用密码学。E-mail: dizhang@cqu.edu.cn
  王皓男，2001年8月出生于辽宁省海城市。现为重庆大学计算机学院硕士研究生。主要研究方向为隐私保护、应用密码学。E-mail: wang_hao@cqu.edu.cn
  张颖女，2002年4月出生于重庆市。现为重庆大学计算机学院硕士研究生。主要研究方向为信息安全。E-mail: zhang_ying@stu.cqu.edu.cn
  乐俊青男，1991年4月出生于江西省抚州市。现为重庆大学计算机学院副教授、硕士生导师。主要研究方向为隐私保护、联邦学习、信息安全。E-mail: junqingle@cqu.edu.cn
  廖晓峰男，1964年10月出生于重庆市。现为重庆大学计算机学院教授、博士生导师。主要研究方向为神经网络、隐私保护、密码学。E-mail: xfliao@cqu.edu.cn
- 基金信息：
  
  国家自然科学基金(62302072);重庆市自然科学基金创新发展联合基金(CSTB2023NSCQ-LZX0149)
- DOI：10.12263/DZXB.20251051
  中图分类号： TP309;
- 收稿：2026-01-20，
  
  录用：2026-03-09，
  
  网络首发：2026-06-03，
  
  纸质出版：2026-04-25
- 稿件说明：
移动端阅览
张迪, 王皓, 张颖, 等. 基于预约束加密的可追溯加密恶意流量检测[J]. 电子学报, 2026, 54(04): 1481-1496.

ZHANG Di, WANG Hao, ZHANG Ying, et al. A Traceable and Encrypted Malicious Traffic Detection Scheme Based on Set Pre-Constrained Encryption[J]. Acta Electronica Sinica, 2026, 54(04): 1481-1496.
张迪, 王皓, 张颖, 等. 基于预约束加密的可追溯加密恶意流量检测[J]. 电子学报, 2026, 54(04): 1481-1496. DOI：10.12263/DZXB.20251051

ZHANG Di, WANG Hao, ZHANG Ying, et al. A Traceable and Encrypted Malicious Traffic Detection Scheme Based on Set Pre-Constrained Encryption[J]. Acta Electronica Sinica, 2026, 54(04): 1481-1496. DOI：10.12263/DZXB.20251051

摘要

随着超文本传输安全协议（HyperText Transfer Protocol Secure，HTTPS）、传输层安全协议（Transport Layer Security，TLS）等安全通信协议的广泛部署，网络流量内容在获得有效保护的同时，也使依赖明文分析的恶意流量检测技术难以直接应用，给密态流量检测带来了新挑战。基于可搜索加密等密码技术的现有检测方案，通过半解密等操作能助力实现密态流量检测。然而，这类方案的中间盒可能借助检测过程推断检测规则，关联用户通信行为，挖掘用户隐私信息，容易引发严峻的隐私泄漏风险。此外，随着检测规则规模与流量分段Token数量不断增长，现有方案中大量使用的双线性配对、多轮交互或者复杂预处理等高开销操作导致计算与通信负担显著加重，难以满足实时检测与大规模部署需求。针对上述问题，本文提出一种基于预约束加密的可追溯加密恶意流量检测方案——CipherSight，旨在面向端到端通信场景，构建兼顾隐私保护与高效检测的主动检测机制。该方案首先结合集合预约束加密、轻量级布谷鸟哈希与对称加密技术，对检测规则与传输流量进行保护，在不泄露流量明文与规则语义的前提下实现恶意Token匹配。其次，基于签名机制对双向通信会话密钥进行承诺与绑定，使接收方能够快速验证并筛选其所需密文流量，从而避免对非目标流量进行冗余解密，提升解密阶段效率与可靠性。进一步地，基于Diffie-Hellman问题，在流量Token密文中隐式嵌入发送方身份信息，仅当流量匹配恶意规则时，中间盒才能恢复有效身份标识并实现精确溯源，而对合规流量仍无法获得任何有用信息。CipherSight在保证通信用户匿名性及恶意规则隐私性的前提下，实现了密态恶意流量的精确检测和恶意传播者的溯源。理论分析表明，所提方案基于不可区分性选择明文攻击（INDistinguishable Chosen Plaintext Attack，IND-CPA）安全的对称加密满足流量机密性，基于会话密钥签名的不可伪造性选择消息攻击（Existential UnForgeability under Chosen Message Attack，EUF-CMA）的安全性满足流量不可链接性，检测规则机密性则继承集合预约束加密的Element-hiding与Set-hiding安全性质。实验结果表明，CipherSight在密钥生成、规则生成、流量检测和流量解密等阶段均展现出较优性能：相较于BlindIDS，检测和解密效率分别提升40倍和15倍以上；相较于近期相关方案Pine与PrivBox，检测和解密效率均提升约5倍；在大规模规则与Token场景下，方案检测时间对规则规模变化不敏感，表现出更好的扩展性与实用性。综上，CipherSight为加密网络环境下实现高效、隐私保护的密态恶意流量主动检测和溯源提供了一种可行的新方案。

Abstract

With the widespread deployment of secure communication protocols such as hypertext transfer protocol secure (HTTPS) and transport layer security (TLS)

while network traffic contents have been effectively protected

malicious traffic detection techniques that rely on plaintext analysis have become difficult to apply directly

posing new challenges to encrypted traffic detection. Existing detection schemes based on searchable encryption and related cryptographic techniques have facilitated the detection of malicious traffic over encrypted data through operations such as partial decryption. However

middleboxes in such schemes may infer detection rules during the detection process

correlate users’ communication behaviors

and further mine users’ private information

thereby causing severe privacy leakage risks. In addition

as the scale of detection rules and the number of traffic segmentation tokens continue to grow

the extensive use of high-overhead operations in existing schemes

such as bilinear pairings

multiple rounds of interaction

and complex preprocessing

significantly increases computational and communication burdens

making it difficult to meet the demands of real-time detection and large-scale deployment. To address these issues

this paper proposes CipherSight

a traceable encrypted malicious traffic detection scheme based on set pre-constrained encryption

which aims to construct an active detection mechanism for end-to-end communication scenarios that achieves both privacy preservation and efficient detection. Specifically

the scheme combines set pre-constrained encryption

lightweight cuckoo hashing

and symmetric encryption to protect detection rules and transmitted traffic

enabling malicious token matching without revealing traffic plaintext or rule semantics. It further uses a signing mechanism to commit and bind bidirectional session keys

allowing the receiver to quickly verify and filter ciphertext traffic intended for itself

thereby avoiding redundant decryption of non-target traffic and improving the efficiency and reliability of the decryption phase. Moreover

based on the Diffie-Hellman problem

sender identity information is implicitly embedded into traffic token ciphertexts

so that only when traffic matches malicious rules can the middlebox recover a valid identity tag and achieve precise traceability

while no useful information can be obtained from benign traffic. CipherSight realizes accurate encrypted malicious traffic detection and malicious sender tracing while preserving communication user anonymity and malicious rule privacy. Theoretical analysis shows that the proposed scheme satisfies traffic confidentiality based on a symmetric encryption being indistinguishable chosen plaintext attack (IND-CPA) security

that the scheme satisfies traffic unlinkability based on the existential unforgeability under chosen message attack (EUF-CMA) security of the session key signature

and that the confidentiality of detection rules inherits the element-hiding and set-hiding security properties of set pre-constrained encryption. Experimental results demonstrate that CipherSight achieves strong performance in key generation

rule generation

traffic detection

and traffic decryption: compared with BlindIDS

it improves detection and decryption efficiency by about 40 times and more than 15 times

respectively; compared with recent related schemes such as Pine and PrivBox

it improves both detection and decryption efficiency by about 5 times; and in large-scale rule and token scenarios

its detection time is insensitive to changes in rule size

showing better scalability and practicality. Overall

CipherSight provides a feasible new solution for achieving efficient

privacy-preserving active detection and traceability of malicious traffic in encrypted network environments.

关键词

Keywords

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