Explainable and secure artificial intelligence: taxonomy, cases of study, learned lessons, challenges and future directions

Faculty Computer Science Year: 2022
Type of Publication: ZU Hosted Pages:
Authors:
Nabil Moustafa AbdelAziz
Journal: Enterprise Information Systems Taylor & Francis Volume:
Keywords : Explainable , secure artificial intelligence: taxonomy, cases    
Abstract:
Explainable artificial intelligence (XAI) is an evolving discipline that mainly emphasises unboxing in these Black-Boxes. This study provides in-depth review of XAI literature together with a new taxonomy of categorising XAI methods.
    
     
 
       

Author Related Publications

  • Nabil Moustafa AbdelAziz, "A Modified Artificial Bee Colony Algorithm for Solving Least-Cost Path Problem in Raster GIS", Natural Sciences Publishing Corporation., 2015 More
  • Nabil Moustafa AbdelAziz, "Enhancing ArcGIS Decision Making Capabilities Using an Intelligent Multicriteria Decision Analysis Toolbox", International Society for Environmental Information Sciences., 2012 More
  • Nabil Moustafa AbdelAziz, "An Expert System for Choosing the Suitable MCDM Method for solving A Spatial Decision Problem", Alex, Egypt, 2009 More
  • Nabil Moustafa AbdelAziz, "Efficient MCDM Model for Evaluating the Performance of Commercial Banks: A Case Study", Tech Science Press, 2021 More
  • Nabil Moustafa AbdelAziz, "Green Communication for Sixth-Generation Intent-Based Networks: An Architecture Based on Hybrid Computational Intelligence Algorithm", Hindawi, 2021 More

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  • Saber Mohamed, "A surrogate-assisted differential evolution algorithm with dynamic parameters selection for solving expensive optimization problems", IEEE, 2014 More
  • Saber Mohamed, "Differential Evolution Combined with Constraint Consensus for Constrained Optimization", IEEE, 2011 More
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