Explainable artificial intelligence (xai) for intrusion detection and mitigation in intelligent connected vehicles: A review

CI Nwakanma, LAC Ahakonye, JN Njoku… - Applied Sciences, 2023 - mdpi.com
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 …

Explainable artificial intelligence for cybersecurity: a literature survey

F Charmet, HC Tanuwidjaja, S Ayoubi… - Annals of …, 2022 - Springer
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 …

[HTML][HTML] Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence

S Ali, T Abuhmed, S El-Sappagh, K Muhammad… - Information fusion, 2023 - Elsevier
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 …

Sok: Explainable machine learning for computer security applications

A Nadeem, D Vos, C Cao, L Pajola… - 2023 IEEE 8th …, 2023 - ieeexplore.ieee.org
Explainable Artificial Intelligence (XAI) aims to improve the transparency of machine
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 …

A brief review of explainable artificial intelligence in healthcare

Z Sadeghi, R Alizadehsani, MA Cifci, S Kausar… - arXiv preprint arXiv …, 2023 - arxiv.org
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 …

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 …

Regulating explainable artificial intelligence (XAI) may harm consumers

B Mohammadi, N Malik, T Derdenger… - Marketing …, 2024 - pubsonline.informs.org
The most recent artificial intelligence (AI) algorithms lack interpretability. Explainable
artificial intelligence (XAI) aims to address this by explaining AI decisions to customers …

Propaganda Detection Robustness Through Adversarial Attacks Driven by eXplainable AI

D Cavaliere, M Gallo, C Stanzione - World Conference on Explainable …, 2023 - Springer
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 …

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 …