  Common privacy enhancing technologies fail to effectively hide certain
statistical aspects of encrypted traffic, namely individual packets length,
packets direction and, packets timing. Recent researches have shown that using
such attributes, an adversary is able to extract various information from the
encrypted traffic such as the visited website and used protocol. Such attacks
are called traffic analysis. Proposed countermeasures attempt to change the
distribution of such features. however, either they fail to effectively reduce
attacker's accuracy or do so while enforcing high bandwidth overhead and timing
delay. In this paper, through the use of a predefined set of clustered traces
of websites and a greedy packet morphing algorithm, we introduce a website
fingerprinting countermeasure called TG-PSM. Firstly, this method clusters
websites based on their behavior in different phases of loading. Secondly, it
finds a suitable target site for any visiting website based on user indicated
importance degree; thus providing dynamic tunability. Thirdly, this method
morphs the given website to the target website using a greedy algorithm
considering the distance and the resulted overhead. Our evaluations show that
TG-PSM outperforms previous countermeasures regarding attacker accuracy
reduction and enforced bandwidth, e.g., reducing bandwidth overhead over 40%
while maintaining attacker's accuracy.
