Challenges in deploying machine learning: a survey of case studies
In recent years, machine learning has transitioned from a field of academic research interest
to a field capable of solving real-world business problems. However, the deployment of …
to a field capable of solving real-world business problems. However, the deployment of …
Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research
Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …
machinery. The majority of these machines comprise rotating components and are called …
The roadmap to 6G security and privacy
Although the fifth generation (5G) wireless networks are yet to be fully investigated, the
visionaries of the 6th generation (6G) echo systems have already come into the discussion …
visionaries of the 6th generation (6G) echo systems have already come into the discussion …
The duo of artificial intelligence and big data for industry 4.0: Applications, techniques, challenges, and future research directions
SK Jagatheesaperumal, M Rahouti… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The increasing need for economic, safe, and sustainable smart manufacturing combined
with novel technological enablers has paved the way for artificial intelligence (AI) and big …
with novel technological enablers has paved the way for artificial intelligence (AI) and big …
Adversarial machine learning-industry perspectives
RSS Kumar, M Nyström, J Lambert… - 2020 IEEE security …, 2020 - ieeexplore.ieee.org
Based on interviews with 28 organizations, we found that industry practitioners are not
equipped with tactical and strategic tools to protect, detect and respond to attacks on their …
equipped with tactical and strategic tools to protect, detect and respond to attacks on their …
Technology readiness levels for machine learning systems
A Lavin, CM Gilligan-Lee, A Visnjic, S Ganju… - Nature …, 2022 - nature.com
The development and deployment of machine learning systems can be executed easily with
modern tools, but the process is typically rushed and means-to-an-end. Lack of diligence …
modern tools, but the process is typically rushed and means-to-an-end. Lack of diligence …
Modeling threats to AI-ML systems using STRIDE
The application of emerging technologies, such as Artificial Intelligence (AI), entails risks that
need to be addressed to ensure secure and trustworthy socio-technical infrastructures …
need to be addressed to ensure secure and trustworthy socio-technical infrastructures …
Towards a research agenda for understanding and managing uncertainty in self-adaptive systems
Despite considerable research efforts on handling uncertainty in self-adaptive systems, a
comprehensive understanding of the precise nature of uncertainty is still lacking. This paper …
comprehensive understanding of the precise nature of uncertainty is still lacking. This paper …
Evasion Attack and Defense On Machine Learning Models in Cyber-Physical Systems: A Survey
Cyber-physical systems (CPS) are increasingly relying on machine learning (ML)
techniques to reduce labor costs and improve efficiency. However, the adoption of ML also …
techniques to reduce labor costs and improve efficiency. However, the adoption of ML also …
Malicious design in aivr, falsehood and cybersecurity-oriented immersive defenses
Advancements in the AI field unfold tremendous opportunities for society. Simultaneously, it
becomes increasingly important to address emerging ramifications. Thereby, the focus is …
becomes increasingly important to address emerging ramifications. Thereby, the focus is …