AI-Driven Risk Management: Exploring Machine Learning Techniques and Privacy Challenges in Smart Cities

被引：0

作者：

Kokkinidis, Konstantinos-Iraklis ^{[1
]}

Chatzipoulidis, Aristeidis ^{[2
]}

机构：

[1] Univ Macedonia, Dept Appl Informat, Thessaloniki, Greece

[2] LRQA, Thessaloniki, Greece

来源：

2024 13TH INTERNATIONAL CONFERENCE ON MODERN CIRCUITS AND SYSTEMS TECHNOLOGIES, MOCAST 2024 | 2024年

关键词：

Artificial Intelligence; Risk Management; Cybersecurity; Human-Computer Interaction (HCI); Smart City;

D O I：

10.1109/MOCAST61810.2024.10615528

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper is a research review that delves into the realm of machine learning techniques for risk management, focusing on the intricate interplay between wireless networks and the burgeoning paradigm of smart cities. As the digital ecosystem continues to expand, encompassing diverse domains such as mobile networks, vehicular communication, and energy-efficient protocols, the need for robust risk management strategies has become increasingly imperative.

引用

页数：4

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