Data Stream Management System and Capital Market Surveillance

摘要：

Importance of real-time data analysis has been felt since early 90s and thus processing of streaming data (from either sensor networks or telecom switches or web & other disparate systems) is the demand of the industries worldwide. Quicker detection of fraudulent activities in a financial system is the order of the day. Thus capital market surveillance, if can be performed by using the streaming input of various trading transactions, without being stored, that would be beneficial to the regulatory authorities and stock exchanges. In this paper, we describe how stream processing using a data stream management system (DSMS) can be used for the above task and how effective would be that in terms of performance and latency. We present results obtained from using a commercial event stream processing system (IBM InfoSphere Streams platform) for certain typical fraud detection scenarios.

关键词： Stream Processing Data Stream Management Systems Capital Market Surveillance Low Latency High Performance

作者: Aniruddha Mukherjee Prasun Bhattacharjee Debnath Mukherjee Prateep Misra

作者单位: Innovation Labs, Tata Consultancy Services Ltd. Bengal Intelligent Park, Salt Lake Electronic Complex Kolkata, INDIA

会议类型: 国际会议

会议名称: 2011 International Conference on Database and Data Mining(ICDDM 2011)(2011年数据库和数据挖掘国际会议)

会议地点: 三亚

会议语种:英文

页码: 260-264

在线出版日期: 2011-03-25（万方平台首次上网日期，不代表论文的发表时间）