Hide information
Hide information
measures how easily other nodes can reach a given node [2]. The hide information of node \(i\) is defined as
\begin{equation*}
c_{\mathcal{H}}(i) = \frac{1}{N} \sum_{j=1}^{N} S(j,i),
\end{equation*}
where
\[
S(j,i) = - \log_2 \sum_{\{p(j,i)\}} P[p(j,i)], \quad
P[p(j,i)] = \frac{1}{k_j} \prod_{l \neq j \neq i \in p(j,i)} \frac{1}{k_l - 1}.
\]
Here, \(S(j,i)\) represents the amount of information required to locate node \(i\) starting from node \(j\), and \(P[p(j,i)]\) is the probability of following path \(p(j,i)\) when choosing neighbors uniformly at each step. A node with high hide information is easier to locate from other nodes. For example, in a star graph, the central hub has high hide information as it is easily reached from peripheral nodes [2].