洋蔥路由器(Tor）是以匿名通訊的方式在網路上進行，使用者利用Tor在網路上進行匿名交流，且不受地域限制。除此之外，利用Tor到達的網路空間是自然搜索所無法到達。但是為了保護使用者隱私而犧牲的傳輸時間，由多層資料加密解密和節點路徑選擇所佔據，使用者無法適當地選擇的當下對應的加密強度，使得機密隱私和無關重要的行為都是同樣的加密強度。本研究探討了洋蔥路由的加解密傳輸流程，提出一種不同加密強度的洋蔥路由，再利用機器學習對網址分類進行預測，提前分類別給予合適的傳輸加密強度。並且藉由自己提供節點來解決出口節點竊聽的問題，同時更彈性取有效的運用時間。

Wireless communication technology is fully developed, due to the rapid spread of tablet computers, smartphones, and other mobile information devices, together with the promotion and construction of telecommunication. Mobile Internet access has been a daily life for the general public. The Onion Router, better known as Tor, is a technique for anonymous communication over internet without regional restrictions. Apart from this, Tor can reach sites that normal search engine can’t search. Basically, the name of Tor is derived from its operation principle. Before original data reaching server, it has been encrypted layer by layer, just like onion. Our research proposed a system by using machine learning technique on URL in order to predict its category before visiting. According to the prediction, we serve three kinds of RSA key lengths on onion routing to represent different privacy level. Depending on various situations, it obtains the balance in security and in time cost. Giving flexibility to onion routing and make more good use of time.

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