## Data preprocessing is an important and critical step in the data mining process and it has a huge impact on the SUCCESS of a data mining project. In this paper, we present an algorithm DB-HFkduction, which discretiaes or eliminates numeric attributes and generalizes or eliminates symbolic attr
Data mining techniques for information security applications
โ Scribed by Amany Al-Shawi
- Publisher
- Wiley (John Wiley & Sons)
- Year
- 2011
- Tongue
- English
- Weight
- 339 KB
- Volume
- 3
- Category
- Article
- ISSN
- 0163-1829
- DOI
- 10.1002/wics.161
No coin nor oath required. For personal study only.
โฆ Synopsis
Abstract
Information security technology is an essential component for protecting public and private computing infrastructures. With the widespread utilization of information technology applications, organizations are becoming more aware of the security threats to their resources. No matter how strict the security policies and mechanisms are, more organizations are becoming susceptible to a wide range of security breaches against their electronic resources. Networkโintrusion detection is an essential defense mechanism against security threats, which have been increasing in rate lately. It is defined as a special form of cyber threat analysis to identify malicious actions that could affect the integrity, confidentiality, and availability of information resources. Data miningโbased intrusionโdetection mechanisms are extremely useful in discovering security breaches. This article will provide an overview of the applications of data mining techniques in the information security domain. The focus will be on applying data mining to intrusion detection and intrusion prevention. This article will present a critical overview of the research directions in these fields, which will help researchers identify the key practical and research issues essential for building a successful networkโprotection system. WIREs Comp Stat 2011 3 221โ229 DOI: 10.1002/wics.161
This article is categorized under:
Statistical and Graphical Methods of Data Analysis > Data Reduction, Smoothing, and Filtering
Algorithms and Computational Methods > Networks and Security
Statistical Learning and Exploratory Methods of the Data Sciences > Text Mining
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