Side-Channel Information Leakage of Traffic Data in Instant Messaging

Instant Messaging has been widely applied for both corporate use and personal use in recent years. Major Instant Messaging service providers adopt the Push Technology to ensure the immediacy of message forwarding, which efficiently provides a great convenience for user. However, the immediacy feature causes side-channel information leakage even if some protection measures has been implemented, such as information encryption strategy. In particular, we observe that senders’ traffic flows have a strong temporal correlation with those of corresponding recipients, since the messages are forwarded to recipients as soon as they are received by servers. Based on the observation, attackers can infer real-time communications between pairwise users and even the social connections of users. In this paper, we present a methodology framework to validate this side-channel information leakage, which identifies users of real-time communications by matching the pairwise time sequences of traffic flows. We evaluate the method on the collected real-world data. The experimental results show that users’ communications can be identified with a high accuracy, and 6 groups of users are inferred to have strong connections based on the data collected from a local area networks.