Privacy-preservation techniques in data mining

In today’s information age, data collection is ubiquitous, and every transaction is recorded somewhere. The resulting data sets can consist of terabytes or even petabytes of data, so efficiency and scalability is the primary consideration of most data-mining algorithms. Data mining is becoming increasingly common in both the private and public sectors. Industries, such as banking, insurance, medicine, and retailing, commonly use data mining to reduce costs, enhance research, and increase sales. In the public sector, data-mining applications initially were used as a means to detect fraud and waste, but have grown to also be used for purposes, such as measuring and improving program performance.