将问责制引入匿名网络
Introducing Accountability to Anonymity Networks
摘要：
许多匿名通信（AC）网络依赖于通过代理节点路由流量来混淆流量的发起者。在没有问责机制的情况下，如果用户通过AC网络进行非法行为，则退出代理节点将面临执法制裁的风险。我们提出了BackRef，AC网络的通用机制，提供了实际的否认代理节点通过追溯选定的出站流量的前身节点（但不是在前进的方向），通过加密可验证的链。当所有中间结点都在协作时，它还提供了一个选项，可以完全（或部分）追溯到入口节点，甚至追溯到相应的用户。此外，为了在匿名性和问责制之间保持良好的平衡，该协议在出口代理节点处加入了白名单目录。BackRef在相关工作中提供了改进的可部署性，并引入了一个新的匿名签名概念，可能会引起独立的兴趣。我们通过将BackRef集成到洋葱路由（OR）协议中来验证它的实用性，并通过考虑几个系统级方面来检查其可部署性。我们还提出了BackRef系统的安全性定义（即，匿名性，向后可追溯性，没有向前可追溯性，没有虚假指控），并进行正式的安全性分析的OR协议与BackRef使用ProVerif，一个自动化的密码协议验证器，建立上述安全属性对一个强大的对抗模型。
英文摘要：
Many anonymous communication (AC) networks rely on routing traffic through proxy nodes to obfuscate the originator of the traffic. Without an accountability mechanism, exit proxy nodes risk sanctions by law enforcement if users commit illegal actions through the AC network. We present BackRef, a generic mechanism for AC networks that provides practical repudiation for the proxy nodes by tracing back the selected outbound traffic to the predecessor node (but not in the forward direction) through a cryptographically verifiable chain. It also provides an option for full (or partial) traceability back to the entry node or even to the corresponding user when all intermediate nodes are cooperating. Moreover, to maintain a good balance between anonymity and accountability, the protocol incorporates whitelist directories at exit proxy nodes. BackRef offers improved deployability over the related work, and introduces a novel concept of pseudonymous signatures that may be of independent interest. We exemplify the utility of BackRef by integrating it into the onion routing (OR) protocol, and examine its deployability by considering several system-level aspects. We also present the security definitions for the BackRef system (namely, anonymity, backward traceability, no forward traceability, and no false accusation) and conduct a formal security analysis of the OR protocol with BackRef using ProVerif, an automated cryptographic protocol verifier, establishing the aforementioned security properties against a strong adversarial model.
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