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Related Experiment Video

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Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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Using a Prediction Model to Manage Cyber Security Threats.

Venkatesh Jaganathan1, Priyesh Cherurveettil1, Premapriya Muthu Sivashanmugam1

  • 1Department of Management Studies, Anna University Regional Centre Coimbatore, Jothipuram Post, Coimbatore, Tamilnadu 641 047, India.

Thescientificworldjournal
|June 12, 2015
PubMed
Summary

Organizations face significant cyber-attack risks. This study introduces a mathematical model to quantitatively predict cyber-attack impact, aiding risk management and cybersecurity strategies.

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Area of Science:

  • Information Security
  • Risk Management
  • Mathematical Modeling

Background:

  • Cyber-attacks pose a critical threat to all organizations, necessitating robust information system security.
  • Understanding the cyber ecosystem and predicting potential attacks are essential for effective risk management.
  • The financial impact of malware, including worms and viruses, is substantial and requires quantitative assessment.

Purpose of the Study:

  • To propose a generalized mathematical model for predicting the impact of cyber-attacks.
  • To incorporate key factors influencing cybersecurity and relevant environmental information into the model.
  • To provide a customizable tool for organizations to assess and manage cyber-attack risks.

Main Methods:

  • Development of a novel mathematical model.
  • Integration of significant cybersecurity influencing factors.
  • Inclusion of environmental information for contextual analysis.

Main Results:

  • A generalized mathematical model capable of predicting cyber-attack impact.
  • The model's flexibility allows customization for specific organizational needs.
  • Quantitative prediction of attack impact supports informed risk management decisions.

Conclusions:

  • The proposed model offers a valuable tool for organizations to quantitatively assess and predict the impact of cyber-attacks.
  • By considering key influencing factors and environmental data, the model enhances cybersecurity risk management.
  • Customization ensures the model's applicability across diverse organizational contexts.