An Edge Correlation Based Differentially Private Network Data Release Method

Abstract

Differential privacy (DP) provides a rigorous and provable privacy guarantee and assumes adversaries' arbitrary background knowledge, which makes it distinct from prior work in privacy preserving. However, DP cannot achieve claimed privacy guarantees over datasets with correlated tuples. Aiming to protect whether two individuals have a close relationship in a correlated dataset corresponding to a weighted network, we propose a differentially private network data release method, based on edge correlation, to gain the tradeoff between privacy and utility. Specifically, we first extracted the Edge Profile (PF) of an edge from a graph, which is transformed from a raw correlated dataset. Then, edge correlation is defined based on the PFs of both edges via JensonShannon Divergence (JS-Divergence). Secondly, we transform a raw weighted dataset into an indicated dataset by adopting a weight threshold, to satisfy specific real need and decrease query sensitivity. Furthermore, we propose -correlated edge differential privacy (CEDP), by combining the correlation analysis and the correlated parameter with traditional DP. Finally, we propose network data release (NDR) algorithm based on the -CEDP model and discuss its privacy and utility. Extensive experiments over real and synthetic network datasets show the proposed releasing method provides better utilities while maintaining privacy guarantee.

Pluripotency Conversion of Gene Studied from Quantum Folding Theory

“…On the same dataset collected by [7] we obtain the best-fit D value is D f =5.619 [8], close to the theoretical prediction D=5.5 and the best-fit B' value B' f =61.63 [8] which means q=3-10 if B=B pt is assumed. Simultaneously, we obtain the correlation between log W and log k f (logarithm experimental folding rate) R= 0.9729 by using Eq(12.1) which is same as R=0.9752 by using HT's [8]. Therefore, two equations have the same overall accuracy in fitting experimental data.…”

“…The folding rate for a two-state protein having a quite oblong or oblate ellipsoid shape is several tenfold higher than a spheroid shape [2] [6]. This can be seen by the shape parameter f appearing in Eqs (6) and (8). The shape parameter is another important factor to measure the coherence degree and influence the transition rate.…”

Recent measurements of the gravitational constant as a function of time

“…Data dates without years are given in the 1999 publication: seven sets of measurements were taken, the first starting on August 4 and the last ending on October 15. The authors report [18] that the year was 1997.…”

Effects of Tube Processing on the Fatigue Life of Nitinol

“…Their analyses predict that once a cracked particle begins to debond, the local plastic strains are intensified in the matrix by the same order of magnitude as an un-cracked but partially debonded inclusion. In the case of Nitinol, simulations of hot deformation of damaged inclusion stringers have shown inter-particle void closure with continued plastic deformation under compressive stress states [37]. These numerical simulations are supported as applications of hot deformation at high pressures to re-bond damaged inclusions have demonstrated significant HCF improvements in bearing steels [38].…”