###### Abstract  
The rapid development of IoT technology has promoted the integration of physical space and cyberspace. At the same time, it has also increased the risk of privacy leakage of Internet users. A large number of research works have shown that attackers can infer Internet surfing privacy through traffic patterns without decryption. Most of the existing research work on anti-traffic analysis is based on a weakened experimental assumption, which is difficult to apply in the actual IoT network environment and seriously affects the user experience. This article proposes a novel lightweight and reliable defense--SMART, which can ensure the anonymity and security of network communication without sacrificing network transmission performance. SMART introduces a multi-path transmission model in the Tor network, and divides traffic at multiple Tor entry onion relays, preventing attackers from obtaining network traffic statistical characteristics. We theoretically proved that SMART can improve the uncertainty of website fingerprint analysis results. The experimental result shows that SMART is able to resist encrypted traffic analysis tools, reducing the accuracy of four state-of-the-art classifiers from 98% to less than 12%, without inducing any additional artificial delay or dummy traffic. In order to avoid the performance degradation caused by data reassembly, SMART proposes a redundant slice mechanism to ensure reliability. Even in the case of human interference, the communication success rate is still as high as 97%. privacy issue in cyborgs; communication privacy; traffic analysis; website fingerprinting +
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with (i.e., visited websites) by passively observing traffic patterns. According to numerous studies over the years, WFP attacks have been able to achieve more than 90% of their effectiveness and are becoming more applicable in real-world environments thanks to the advancement of machine learning (ML) [3; 4; 5; 6; 7; 8; 9; 10]. Research on defenses against WFP attacks has received increasing attention. However, most current defenses struggle with balancing security and network overhead due to their significant bandwidth and latency overhead, including artificial delays or dummy packet padding to hide traffic patterns. In the current advanced padding defenses, trade-offs are unacceptable. They increase latency, slow page loads by an average of two to four times, and impose a bandwidth overhead of 40% to 350% [11]. Some defenses need to know the prior knowledge of the page in advance, so the database is required to store the resources generated by the dynamic changes of the page, such as SuperSequence [12] and Glove [13]. These additional requirements increase the difficulty of deployment. Developing effective defensive countermeasures that are both easy to use and deploy is critical given the growing number of powerful WFP attacks. We propose SMART: a novel lightweight and reliable WFP multi-path transmission defense. It successfully combats several state-of-the-art WFP classifiers with reasonable overhead. This research is based on user control and splits traffic across multiple entry ORs, limiting the traffic information that can be observed at a single entry OR and destroying otherwise consistent pipeline model features without injecting any extra delays or packets. In this paper, our main contributions are as follows:  
* We present the existing WFP attack model, background research on related attacks and defenses, and analyze the applicability of deploying defenses in the anonymous communication system, taking Tor as an example;
* We design a novel WFP defense for the lightweight reliable multi-path transmission, SMART, which allows decentralized data transmission based on user-selected multi-paths without padding any spurious packets and artificial delays during the period.