A survey on data-driven network intrusion detection

D Chou, M Jiang - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Data-driven network intrusion detection (NID) has a tendency towards minority attack
classes compared to normal traffic. Many datasets are collected in simulated environments …

Explainable intrusion detection systems (x-ids): A survey of current methods, challenges, and opportunities

S Neupane, J Ables, W Anderson, S Mittal… - IEEE …, 2022 - ieeexplore.ieee.org
The application of Artificial Intelligence (AI) and Machine Learning (ML) to cybersecurity
challenges has gained traction in industry and academia, partially as a result of widespread …

From artificial intelligence to explainable artificial intelligence in industry 4.0: a survey on what, how, and where

I Ahmed, G Jeon, F Piccialli - IEEE Transactions on Industrial …, 2022 - ieeexplore.ieee.org
Nowadays, Industry 4.0 can be considered a reality, a paradigm integrating modern
technologies and innovations. Artificial intelligence (AI) can be considered the leading …

A survey on llm-gernerated text detection: Necessity, methods, and future directions

J Wu, S Yang, R Zhan, Y Yuan, DF Wong… - arXiv preprint arXiv …, 2023 - arxiv.org
The powerful ability to understand, follow, and generate complex language emerging from
large language models (LLMs) makes LLM-generated text flood many areas of our daily …

[HTML][HTML] Explainable AI and machine learning: performance evaluation and explainability of classifiers on educational data mining inspired career counseling

P Guleria, M Sood - Education and Information Technologies, 2023 - Springer
Abstract Machine Learning concept learns from experiences, inferences and conceives
complex queries. Machine learning techniques can be used to develop the educational …

[HTML][HTML] Artificial intelligence applications in Latin American higher education: a systematic review

SZ Salas-Pilco, Y Yang - … Journal of Educational Technology in Higher …, 2022 - Springer
Over the last decade, there has been great research interest in the application of artificial
intelligence (AI) in various fields, such as medicine, finance, and law. Recently, there has …

[HTML][HTML] Explainable artificial intelligence in Alzheimer's disease classification: A systematic review

V Viswan, N Shaffi, M Mahmud, K Subramanian… - Cognitive …, 2024 - Springer
The unprecedented growth of computational capabilities in recent years has allowed
Artificial Intelligence (AI) models to be developed for medical applications with remarkable …

On locality of local explanation models

S Ghalebikesabi, L Ter-Minassian… - Advances in neural …, 2021 - proceedings.neurips.cc
Shapley values provide model agnostic feature attributions for model outcome at a particular
instance by simulating feature absence under a global population distribution. The use of a …

FCE: Feedback based counterfactual explanations for explainable AI

M Suffian, P Graziani, JM Alonso, A Bogliolo - IEEE Access, 2022 - ieeexplore.ieee.org
Artificial Intelligence can provide quite accurate predictions for critical applications (eg,
healthcare), but lacks the ability to explain its internal mechanism in most applications which …

Would you trust an AI team member? Team trust in human–AI teams

E Georganta, AS Ulfert - Journal of Occupational and …, 2024 - Wiley Online Library
Given that AI is becoming an increasingly active participant in work teams, this study
explores how team trust emerges in human–AI teams compared to human–human teams …