R/dynetNLAResistance
R/dynetNLAResistance is an R package of anonymization algorithm to resist neighbor label attack in a dynamic network.
Installation
You can install the stable version of R/dynetNLAResistance from CRAN:
install.packages("dynetNLAResistance")
Example
You can create a dynamic network by function make.virtual.dynamic.network. Then group it by function lw.grouping,and anonymize it by function anonymization.
library(dynetNLAResistance)
dynet <- make.virtual.dynamic.network()
dynet.grouped <- lw.grouping(dynet,l = 2, w = 1)
## candidates number: 21 selected id: V22987
## Grouping t1 50%
## candidates number: 20 selected id: V905
## Grouping t1 100%
## merge.groups
## candidates number: 25 selected id: V22987
## Grouping t2 50%
## candidates number: 25 selected id: V40271
## Grouping t2 100%
## merge.groups
## candidates number: 30 selected id: V64428
## Grouping t3 50%
## candidates number: 29 selected id: V40271
## Grouping t3 100%
## merge.groups
## candidates number: 35 selected id: V64428
## Grouping t4 50%
## candidates number: 35 selected id: V40271
## Grouping t4 100%
## merge.groups
## candidates number: 39 selected id: V64428
## Grouping t5 33.33333%
## candidates number: 38 selected id: V78667
## Grouping t5 66.66667%
## candidates number: 38 selected id: V40271
## Grouping t5 100%
## merge.groups
## candidates number: 40 selected id: V26750
## Grouping t6 20%
## candidates number: 39 selected id: V61271
## Grouping t6 40%
## candidates number: 39 selected id: V64428
## Grouping t6 60%
## candidates number: 38 selected id: V78667
## Grouping t6 80%
## candidates number: 39 selected id: V40271
## Grouping t6 100%
## merge.groups
## candidates number: 43 selected id: V26750
## Grouping t7 16.66667%
## candidates number: 43 selected id: V35010
## Grouping t7 33.33333%
## candidates number: 42 selected id: V22987
## Grouping t7 50%
## candidates number: 39 selected id: V78667
## Grouping t7 66.66667%
## candidates number: 41 selected id: V40271
## Grouping t7 83.33333%
## candidates number: 38 selected id: V8536
## Grouping t7 100%
## merge.groups
## candidates number: 46 selected id: V26750
## Grouping t8 14.28571%
## candidates number: 46 selected id: V35010
## Grouping t8 28.57143%
## candidates number: 44 selected id: V46066
## Grouping t8 42.85714%
## candidates number: 45 selected id: V22987
## Grouping t8 57.14286%
## candidates number: 43 selected id: V78667
## Grouping t8 71.42857%
## candidates number: 45 selected id: V40271
## Grouping t8 85.71429%
## candidates number: 43 selected id: V8536
## Grouping t8 100%
## merge.groups
## candidates number: 49 selected id: V26750
## Grouping t9 12.5%
## candidates number: 49 selected id: V35010
## Grouping t9 25%
## candidates number: 48 selected id: V46066
## Grouping t9 37.5%
## candidates number: 49 selected id: V22987
## Grouping t9 50%
## candidates number: 47 selected id: V78667
## Grouping t9 62.5%
## candidates number: 46 selected id: V905
## Grouping t9 75%
## candidates number: 48 selected id: V40271
## Grouping t9 87.5%
## candidates number: 46 selected id: V8536
## Grouping t9 100%
## merge.groups
## candidates number: 53 selected id: V26750
## Grouping t10 12.5%
## candidates number: 53 selected id: V35010
## Grouping t10 25%
## candidates number: 52 selected id: V46066
## Grouping t10 37.5%
## candidates number: 53 selected id: V22987
## Grouping t10 50%
## candidates number: 51 selected id: V78667
## Grouping t10 62.5%
## candidates number: 51 selected id: V14096
## Grouping t10 75%
## candidates number: 51 selected id: V40271
## Grouping t10 87.5%
## candidates number: 50 selected id: V8536
## Grouping t10 100%
## merge.groups
g5.a <- anonymization(dynet.grouped$t5, alpha = 1, beta = 2, gamma = 3)
## Merged group-set's size: 3
## Vertex number: 43
## iterating...
## Anonymized nodes with sensitive label:
## V97632
##
## Merged group-set's size: 2
## Vertex number: 45
## iterating...
## Anonymized nodes with sensitive label:
## V97632 V20247
##
## Merged group-set's size: 1
## Vertex number: 53
## iterating...
## Anonymized nodes with sensitive label:
## V97632 V20247 V97788
License
MIT