A New Method for Image Steganography Using Discrete Wavelet Transforms

Document Type : Original Article

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Abstract

In Cyber Security Analysis, in addition to data and information obtained from machine-based sensors like intrusion detection systems, firewalls and vulnerability scanners (hard data), human observations and conclusions from world's state including problems reported by users and network administrators, and assessments made by security analysts about network security status (soft data), can be used to obtain more accurate and more reliable estimation and decision. Hard and soft data fusion in cyber security analysis has many challenges such as designing a proper framework for problem modeling and representation of different types of uncertainty. This paper presents a new model based on ontology to fusion of hard and soft data in cyber security analysis.  First, the concepts and problem variables are modeled and then the inference about security status of assets is made by using set of rules. Also, to fusion of data and unified modeling of different uncertainties, transferable belief model (TBM) and Dempster-Shafer combination rule were used. Results of applying proposed model in a sample scenario of cyber security analysis show applicability of model for hard and soft data fusion.

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References

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History

  • Receive Date: 14 August 2018
  • Accept Date: 05 March 2019
  • Publish Date: 20 February 2020

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