… Narayanan and Shmatikov [22] demonstrated that user identification can be accomplished
by relying on network topology information; however, the user identification performance …

… usually create lots of spam information that is harmful to other … Entropy method to measure
the complexity of each user's … In Section 2 we introduce the Multi-scale Entropy method for …

… We also analyze the effectiveness of k-anonymization in resisting user identification attacks
… which the available information about a user’s data is in the form of histograms of the user’s …

… identify user groups; Secondly, we propose a noise filter based on information entropy to
reduce … in this paper has a higher performance for user group identification, and provide a good …

… aimed to identify a set of influential nodes via information entropy. Firstly, the information
entropy of … Then, select the node with the largest information entropy and renovate its l-length …

… In Section 4.2, we apply the Δ-entropy criterion in system identification with quantized I/O data.
… We can use Theorem 2 and the bound of the discrete entropy to obtain a bound on the Δ-…

… The entropy represents the uncertainty of the information … the entropy is how much information
we need to identify data… researches use the entropy to determine re-identification risk […

… to incorporate the entropy evaluation and introduce user coherence by … information entropy
of the relative rating differences between two users captures additional coherent information …

… a user attributes’ susceptibility and entropy based … unique identifications of multiple users
(ie, users’ community) caused by the highly susceptible QIs. We adapt the information entropy …

… An entropy based measure was already proposed for computing information loss [11], and,
… Although the use of this quantity as an utility measure is strongly debated [17], [11], it still …