Computer Science – Artificial Intelligence
Scientific paper
Jun 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011ijcci...2s.146s&link_type=abstract
International Journal of Computer Communication and Information System(IJCCIS) Vol2. No.1 - Special Issue, p. 146-149
Computer Science
Artificial Intelligence
Additive, Data Mining, Perturbation, Data Analysis
Scientific paper
Privacy is becoming an increasingly important issue in many data mining applications that deal with health care, security, finance, behavior and other types of sensitive data. Is particularly becoming important in counterterrorism and homeland security-related applications. We touch upon several techniques of masking the data, namely random distortion, including the uniform and Gaussian noise, applied to the data in order to protect it. These perturbation schemes are equivalent to additive perturbation after the logarithmic Transformation. Due to the large volume of research in deriving private information from the additive noise perturbed data, the security of these perturbation schemes is questionable Many artificial intelligence and statistical methods exist for data analysis interpretation, Identifying and measuring the interestingness of patterns and rules discovered, or to be discovered is essential for the evaluation of the mined knowledge and the KDD process as a whole. While some concrete measurements exist, assessing the interestingness of discovered knowledge is still an important research issue. As the tool for the algorithm implementations we chose the language of choice in industrial world MATLAB.
Singh Niranjan Er.
Singhai Niky
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