Modeling and Practice for Trustworthy and Secure Systems

Dear Colleagues,

There is always a fundamental question that could be asked of any automated decision system based on algorithms, namely: how much do you trust their output? To address such question, we need to model, develop and practice a trustworthy and secure approach. Such a system should fulfill stakeholders’ needs regarding security, privacy, responsibility/accountability, reliability, and governance bodies’ rules and regulations. There have been many solutions outlined to address these requirements, which are mainly focussed on the use of automated models based on Artificial Intelligence (AI). Though it has been a crucial question, it remains unclear if AI can always make the ‘right’ decision in real-time applications? In order to answer such a question, automated data-driven intelligent systems should be designed and tested in such a way that facilitates their decisions being described or explained for verification and validation by an expert human in the system’s context. By doing so, humans/experts will be able to account for their use by developing trustworthy AI models for real-time decision-making for high-risk AI applications. Additionally, the secure-by-design (SBD) paradigm should be optimised in such a way as to automatically check the processes and data involved in developing trustworthy systems.

Dr. Ali Sadiq
Dr. Houbing Song
Dr. Ahmad Fadhil Yusof
Dr. Sushil Kumar
Dr. Omprakash Kaiwartya
Guest Editors

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