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Implementations of various data stream anonymisation methods giving k-anonymity and l-diversity.

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Levelent/JIDSAM

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CS347 Fault Tolerant Systems

JIDSAM: Java Implementations of Data Stream Anonymisation Methods

Uses gradle version 7.3.3 and java openjdk 11.0.14

Execution

In the project's root run the command: gradle run

Version Execution command
Castle gradle castle or gradle run
Castle-L gradle castlel
B-Castle gradle bcastle
FADS gradle fads
FADS-L gradle fadsl
XBAND gradle xband

Command Line Arguments are also supported if the source code is compiled

option Description
-c Castle Variant:
1: Castle l
2: B-Castle
3: FADS
4: FADSL
5: XBAND
6: CASTLE
-k k-anonymity value
-d delta tuple expiration value
-b beta cluster persistance value
-o XBAND Omega
-g XBAND Gamma

Output

Development/Internal output occurs to the terminal where you can see the cluster generalisations and the tuples included.

External output can be seen in output.txt.

Compare Algorithms

To generate graphs comparing the algorithms run gradle compare

Automated Tests

Each of the defined classes have automated testing which can be executed using: gradle test

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Implementations of various data stream anonymisation methods giving k-anonymity and l-diversity.

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