| Type: | Package |
| Title: | Resisting Neighbor Label Attack in a Dynamic Network |
| Version: | 0.1.0 |
| Author: | Jiaqi Tang |
| Maintainer: | Jiaqi Tang <1107967177@qq.com> |
| Description: | An anonymization algorithm to resist neighbor label attack in a dynamic network. |
| Depends: | R (≥ 2.10) |
| License: | MIT + file LICENSE |
| LazyData: | true |
| Suggests: | testthat |
| Imports: | igraph, doParallel, foreach, grDevices, graphics, utils, parallel |
| RoxygenNote: | 5.0.1 |
| NeedsCompilation: | no |
| Packaged: | 2016-11-25 09:47:25 UTC; TJQ |
| Repository: | CRAN |
| Date/Publication: | 2016-11-25 14:14:30 |
Anonymize a snapshot of a dynamic network.
Description
Anonymize a snapshot of a dynamic network.
Usage
anonymization(g, alpha = 1, beta = 2, gamma = 3)
Arguments
g |
A network grouped by lw-grouping algorithm. |
alpha |
Weight of anonymization cost resulted from label generalization. |
beta |
Weight of anonymization cost resulted from adding edges. |
gamma |
Weight of anonymization cost resulted from adding nodes. |
Anonymize two node.
Description
Anonymize two node.
Usage
anonymize2node(g, uid, vid, noise = g$noise)
Arguments
g |
A graph contains vertexs with different labels and some of which are sensitive. |
uid |
Name of a node with sensitive label. |
vid |
Name of a node with unsensitive label. |
noise |
Current amount of noise nodes. |
Value
A list with information of anonymized network.
Calculate anonymization cost of two nodes.
Description
Calculate anonymization cost of two nodes.
Usage
cost(g, uid, vid, alpha = 1, beta = 2, gamma = 3)
Arguments
g |
A graph contains vertexs with different labels and some of which are sensitive. |
uid |
Name of a node with sensitive label. |
vid |
Name of a node with unsensitive label. |
alpha |
Weight of anonymization cost resulted from label generalization. |
beta |
Weight of anonymization cost resulted from adding edges. |
gamma |
Weight of anonymization cost resulted from adding nodes. |
Value
Anonymization cost of two nodes.
Draw a graph contains vertexs with sensitive or unsensitive label
Description
Draw a graph contains vertexs with sensitive or unsensitive label
Usage
draw.graph(g, main = NULL, label = NA)
Arguments
g |
A graph contains vertexs with different labels and some of which are sensitive. |
main |
The title of graph. |
label |
Label of vertexs. |
Examples
dynet <- make.virtual.dynamic.network()
draw.graph(dynet$t1)
Generate a grouped dynamic network by lw-grouping algorithm.
Description
Generate a grouped dynamic network by lw-grouping algorithm.
Usage
lw.grouping(dynet = NULL, l = 2, w = 3)
Arguments
dynet |
An ungrouped dynamic network. |
l |
Kinds of labels in each unmerged group. |
w |
Width of window of lw-grouping algorithm. |
Value
A list of grouped network with attribute of gs.merged.
Make a vertex-increasing virtual dynamic network.
Description
Make a vertex-increasing virtual dynamic network.
Usage
make.virtual.dynamic.network(network.data = NULL, len = 10, by = 5,
label.types = 100, prop.init = 0.001, prop.sensitive = 0.1)
Arguments
network.data |
A data frame containing a symbolic edge list,which contains the information of whole network data. |
len |
Time of this dynamic network lasts. |
by |
The number of vertex added in network each time. |
label.types |
The number of label types the network possesses. |
prop.init |
The proportion of vertex amounts of initial network in whole network data. |
prop.sensitive |
The proportion of amounts of vertex with sensitive label in whole network data. |
Value
A list of snapshots of a virtual dynamic network.
Examples
dynet <- make.virtual.dynamic.network()
Unirected graph: CA-CondMat
Description
Collaboration network of Arxiv Condensed Matter category (there is an edge if authors coauthored at least one paper) network
Usage
network
Format
An object of class data.frame with 93439 rows and 2 columns.
Details
@format A data frame with 93439 rows and 2 variables: