Security Data Mining: A Survey Introducing Tamper-Resistance

  • Clifton Phua
  • Mafruz Ashrafi

Security data mining, a form of countermeasure, is the use of large-scale data analytics to dynamically detect a small number of adversaries who are constantly changing. It encompasses data-and results-related safeguards; and is relevant across multiple domains such as financial, insurance, and health. With reference to security data mining, there are specific and general problems, but the key solution and contribution of this chapter is still tamper-resistance. Tamper-resistance addresses most kinds of adversaries and makes it more difficult for an adversary to manipulate or circumvent security data mining; and consists of reliable data, anomaly detection algorithms, and privacy and confidentiality preserving results. In this way, organisations applying security data mining can better achieve accuracy for organisations, privacy for individuals in the data, and confidentiality between organisations which share the results.


Data Mining Association Rule Frequent Itemsets Association Rule Mining Fraud Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.A*STAR, Institute of Infocomm Research, Room 04-21 21Singapore

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