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Using Genetic Algorithm to Minimize False Alarms in Insider Threats Detection of Information Misuse in Windows Environment

机译：Windows环境中使用遗传算法将内部威胁检测中的误用最小化

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摘要

Insider threats detection problem has always been one of the most difficult challenges for organizations and research community. Effective behavioral categorization of users plays a vital role for the success of any detection mechanisms. It also helps to reduce false alarms in case of insider threats. In order to achieve this, a fuzzy classifier has been implemented along with genetic algorithm (GA) to enhance the efficiency of a fuzzy classifier. It also enhances the functionality of all other modules to achieve better results in terms of false alarms. A scenario driven approach along with mathematical evaluation verifies the effectiveness of the modified framework. It has been tested for the enterprises having critical nature of business. Other organizations can adopt it in accordance with their specific nature of business, need, and operational processes. The results prove that accurate classification and detection of users were achieved by adopting the modified framework which in turn minimizes false alarms.
机译：内部威胁检测问题一直是组织和研究社区最困难的挑战之一。用户的有效行为分类对于任何检测机制的成功都至关重要。它还有助于减少内部威胁时的误报。为了实现此目的，模糊分类器已经与遗传算法（GA）一起实现，以提高模糊分类器的效率。它还增强了所有其他模块的功能，以实现错误警报方面的更好结果。场景驱动方法与数学评估一起验证了修改后框架的有效性。已针对具有关键业务性质的企业进行了测试。其他组织可以根据其业务，需求和运营流程的特定性质采用它。结果证明，采用改进的框架可以实现准确的用户分类和检测，从而减少了误报。

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  • 来源
    《Mathematical Problems in Engineering》 |2014年第21期|179109.1-179109.12|共12页
  • 作者

    Bin Ahmad Maaz; Akram Adeel; Asif M.; Ur-Rehman Saeed;

  • 作者单位

    Ctr Adv Studies Engn, Dept Elect & Comp Engn, Islamabad, Pakistan.;

    Univ Engn & Technol, Fac Software & Comp Engn, Taxila, Pakistan.;

    Muhammad Ali Jinnah Univ, Dept Elect Engn, Islamabad, Pakistan.;

    Ctr Adv Studies Engn, Dept Elect & Comp Engn, Islamabad, Pakistan.;

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