Data Mining- Security Systems

Table of Contents

INTRODUCTION AND BACKGROUND3

AIMS AND OBJECTIVES4

SCIENTIFIC COMPUTING4

CASE STUDY6

Statement of the Problem6

Theoretical Solution7

Practical Implementation7

Quality Assurance8

Conclusion10

CRITICAL REFLECTION11

REFERENCES12

Data Mining- Security Systems

Introduction and Background

The paper explores the concept of data mining in holistic context. Data mining is an emerging technology that extracts useful information, patterns, and trends from various data sources (Carrettoni, 2008). Computerization has resulted in the availability and accumulation of a large amount of data. As the amount of data increases, it becomes more and more difficult to access and understand the meaning of both historical and current data from multiple sources. Data mining fulfills the need to access data efficiently, share data, and extract information from existing data, in order to assist decision-making in organizations. Data mining provides information to improve marketing capabilities, detect abnormal patterns, and predict future developments based on existing trends (Chung, 2010). A supermarket could analyze the purchase record of its customers and, based on patterns the analysis shows, arrange items on shelves to improve sales. A credit bureau could analyze the credit history of its current or potential clients and find out which are at risk. Physicians could analyze patient histories and current medical conditions and predict potential problems that might arise. Data mining is an integration of multiple technologies, including database systems, data warehousing, statistics, machine learning, decision support, visualization, and parallel processing(Bigus, 2009).

When data mining is performed, a large quantity of information is analyzed. Therefore, it is important to utilize various data-management technologies to prepare data for mining in order to obtain meaningful results. Data management systems, which include database systems technology and data warehousing, are designed to organize, structure, and manage data.

This paper further analysis a case based on the working of data mining for the security systems. Digital libraries are an emerging technology in Web mining, providing digitized information distributed across several sites. Efforts are being made to allow users to access this information in a transparent and timely fashion. Issues associated with digital libraries include security and privacy, as well as copyright protection and data ownership. Initiatives have been undertaken to address these issues (Fayyad, 2009).

Despite its many uses, data mining poses a potential threat to the security and privacy of individuals. For example, one controversial issue in data mining is inference, the process by which users pose queries and deduce unauthorized information from the legitimate responses they receive (Snapp, 2010). Users with sophisticated tools can now access data and deduce patterns that could be sensitive. In addition, Web mining could potentially compromise the privacy of individuals, whose personal information can be obtained and analyzed as they browse the Web.

Aims and Objectives

Following are the aims & objectives for the current paper:

Examine the features of data mining with respect to security systems

Explore the scientific computing aspects in relation to its issues and its challenges

Examine a case study in order to explore the working of data mining for the security systems.

Scientific Computing

Many of the most important and challenging problems in science and engineering require significant computing resources to model and ...