The 3rd International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC 2022)
Conference Date: September 23-25, 2022
  • IIoTBDSC 2022
Keynote & Invited Speakers

Invited Speakers

Dr. Mohamed Abdel-Basset
Zagazig University, Egypt

Mohamed Abdel-Basset received his B.Sc. and M.Sc from Faculty of Computers and Informatics, Zagazig University, Egypt. Received his Ph.D from Faculty of Computers and Informatics, Menoufia University, Egypt. Currently, Mohamed is Associate Professor at Faculty of Computers and Informatics, Zagazig University, Egypt. His current research interests are Optimization, Operations Research, Data Mining, Computational Intelligence, Applied Statistics, Decision support systems, Robust Optimization, Engineering Optimization, Multi-objective Optimization, Swarm Intelligence, Evolutionary Algorithms, and Artificial Neural Networks. He is working on the application of multiobjective and robust meta-heuristic optimization techniques. He is also an/a Editor/reviewer in different international journals and conferences. He is an editor-in-chief of Neutrosophic Sets and Systems: An International Journal in Information Science and Engineering. He holds the program chair in many conferences in the fields of decision making analysis, big data, optimization, complexity and internet of things, as well as editorial collaboration in some journals of high impact.

Title: Explainable Intelligence for Dependable and Trustworthy Industrial Internet of Things
The Industrial Internet of Things (IIoT) denotes the digitization of physical industrial processes utilizing a set of internet sensors and actuators to enable automated control and effective resource exploitation. Being a key enabler for Industry 4.0 revolution, the IIoT is projected to give rise to extraordinary opportunities for improving the business value especially with the integration of advanced cellular technologies, such as 5G, B5G, 6G, and computing paradigms, such as cloud computing, fog computing, mobile edge computing, etc. However, the inclusion of the recent embedded technologies and advanced communications in the management and automation processes multiplies the operational complexities of the industrial control system, while broadening the surface of security and privacy threats and attacks. Therefore, security and privacy turned to be of supreme importance for realizing the dependability and trustworthiness of the IIoT applications. To this end, Artificial Intelligence (AI) has revealed notable achievements over the traditional security solutions in IIoT. However, it also exhibits more complexity and interoperability challenges leading to severe issues concerning verifiability, validity, deployability. Besides, the current AI solutions hard to interpret the way they work completely or the idea behind their behavior and decisions hence named black boxes. This is because AI models are often devised by emphasizing only the performance aspect while ignoring some critical aspects like translucence, interpretability, privacy awareness, trustworthiness, accountability. This behavior is regarded as one of the major challenges in AI-based security solutions in IIoT as the decisions are unintelligible and often inconceivable even for the developers and security experts themselves. As a promising remedy, Explainable AI (XAI) is emerging to enable AI techniques to provide an explanation and justifications for model decisions and outcomes. Thus, XAI can bridge the gap between the complexity of underlying AI solutions and the intellectual abilities of the IIoT stakeholders for which explainability is wanted. Consequently, AI-based models must be designed to create white-box security solutions instead of black-box ones to assure the dependability and trustworthiness of business problems in IIoT networks.

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