Explainable artificial intelligence (xai) for intrusion detection and mitigation in intelligent connected vehicles: A review
The potential for an intelligent transportation system (ITS) has been made possible by the
growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration …
growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration …
Explainable artificial intelligence for cybersecurity: a literature survey
With the extensive application of deep learning (DL) algorithms in recent years, eg, for
detecting Android malware or vulnerable source code, artificial intelligence (AI) and …
detecting Android malware or vulnerable source code, artificial intelligence (AI) and …
[HTML][HTML] Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …
applications, but the outcomes of many AI models are challenging to comprehend and trust …
Sok: Explainable machine learning for computer security applications
Explainable Artificial Intelligence (XAI) aims to improve the transparency of machine
learning (ML) pipelines. We systematize the increasingly growing (but fragmented) …
learning (ML) pipelines. We systematize the increasingly growing (but fragmented) …
A Survey on XAI for 5G and Beyond Security: Technical Aspects, Challenges and Research Directions
T Senevirathna, VH La, S Marchal… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
With the advent of 5G commercialization, the need for more reliable, faster, and intelligent
telecommunication systems is envisaged for the next generation beyond 5G (B5G) radio …
telecommunication systems is envisaged for the next generation beyond 5G (B5G) radio …
A brief review of explainable artificial intelligence in healthcare
XAI refers to the techniques and methods for building AI applications which assist end users
to interpret output and predictions of AI models. Black box AI applications in high-stakes …
to interpret output and predictions of AI models. Black box AI applications in high-stakes …
Review of white box methods for explanations of convolutional neural networks in image classification tasks
MP Ayyar, J Benois-Pineau… - Journal of Electronic …, 2021 - spiedigitallibrary.org
In recent years, deep learning has become prevalent to solve applications from multiple
domains. Convolutional neural networks (CNNs) particularly have demonstrated state-of-the …
domains. Convolutional neural networks (CNNs) particularly have demonstrated state-of-the …
Regulating explainable artificial intelligence (XAI) may harm consumers
The most recent artificial intelligence (AI) algorithms lack interpretability. Explainable
artificial intelligence (XAI) aims to address this by explaining AI decisions to customers …
artificial intelligence (XAI) aims to address this by explaining AI decisions to customers …
Propaganda Detection Robustness Through Adversarial Attacks Driven by eXplainable AI
Pre-trained language models like BERT have shown remarkable success in many areas,
including the detection of propaganda in text messages. However, recent studies have …
including the detection of propaganda in text messages. However, recent studies have …
Role of Explainable AI in 6G Security
P Porambage, M Liyanage… - Security and Privacy …, 2023 - Wiley Online Library
Accountability and resilience of AI/ML based 6G services is paramount now more than ever.
In this chapter we are going to discuss the potential of Explainable AI (XAI) to address the …
In this chapter we are going to discuss the potential of Explainable AI (XAI) to address the …