A Fuzzy Multi-Objective Covering-based Security Quantification Model for Mitigating Risk of Web based Medical Image Processing System

Medical image processing is one of the most active research areas and has big impact on the health sector. With the arrival of intelligent processes, web based medical image processing has become simple and errorless. Web based application is now used extensively for medical image processing. Large amount of medical data is generated daily with more and more data being shared over public and private networks for the diagnosis of diseases through the web based image processing systems. Medical images like that of the CT (Computed Tomography) scan, MRI (Magnetic Resonance Imaging), X-Ray and Ultrasound images, etc., contain highly personal data of the patients. This data needs to be secured from intruders. Medical images are more sensitive to external interruption and manipulation in data may cause changes in the result. Data breaches in medical cases can lead to wrong diagnosis or even more fatal possibilities with life threatening results. So, security in web based medical image processing is a major issue. However, ensuring security for the medical images while preserving the characteristics of confidentiality, integrity, availability, etc., of medical images poses a major challenge. Working towards a feasible solution, in this study, authors are using a list of criteria for checking security level of the web based image processing system. We propose Fuzzy Analytic Hierarchy Process (FAHP) combined with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in the list of criteria that affect the security assessment in medical image processing. At the results we see that FAHP-TOPSIS produce good results in security checking in web based medical image processing system. At the data analysis section all the steps showed which is involved in our model.

@article{Algarni2020,
  title     = {A Fuzzy Multi-Objective Covering-based Security Quantification Model for Mitigating Risk of Web based Medical Image Processing System},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {1},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Abdullah Algarni and Masood Ahmad and Abdulaziz Attaallah and Alka Agrawal and Rajeev Kumar and Raees Ahmad Khan},
  doi       = {10.14569/IJACSA.2020.0110159},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110159}
}