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Most privacy-conscious users utilize HTTPS and an anonymity network such as Tor to mask source and destination IP addresses. It has been shown that encrypted and anonymized network traffic traces can still leak information through a type of attack called a website fingerprinting (WF) attack. The adversary records the network traffic and is only able to observe the number of incoming and outgoing messages, the size of each message, and the time difference between messages. In previous work, the effectiveness of website fingerprinting has been shown to have an accuracy of over 90% when using Tor as the anonymity network. Thus, an Internet Service Provider can successfully identify the websites its users are visiting. One main concern about website fingerprinting is its practicality. The common assumption in most previous work is that a victim is visiting one website at a time and has access to the complete network trace of that website. However, this is not realistic. We propose two new algorithms to deal with situations when the victim visits one website after another (continuous visits) and visits another website in the middle of visiting one website (overlapping visits). We show that our algorithm gives an accuracy of 80% (compared to 63% in a previous work [24]) in finding the split point which is the start point for the second website in a trace. Using our proposed “splitting” algorithm, websites can be predicted with an accuracy of 70%. When two website visits are overlapping, the website fingerprinting accuracy falls dramatically. Using our proposed “sectioning” algorithm, the accuracy for predicting the website in overlapping visits improves from 22.80% to 70%. When part of the network trace is missing (either the beginning or the end), the accuracy when using our sectioning algorithm increases from 20% to over 60%.