A Survey on Intelligent Internet of Things: Applications, Security, Privacy, and Future Directions

• URL: http://arxiv.org/abs/2406.03820v2
• Date: Fri, 21 Jun 2024 14:43:41 GMT
• Title: A Survey on Intelligent Internet of Things: Applications, Security, Privacy, and Future Directions
• Authors: Ons Aouedi, Thai-Hoc Vu, Alessio Sacco, Dinh C. Nguyen, Kandaraj Piamrat, Guido Marchetto, Quoc-Viet Pham,
• Abstract summary: The rapid advances in the Internet of Things (IoT) have promoted a revolution in communication technology and offered various customer services. Artificial intelligence (AI) techniques have been exploited to facilitate IoT operations and maximize their potential in modern application scenarios. The convergence of IoT and AI has led to a new networking paradigm called Intelligent IoT (IIoT), which has the potential to significantly transform businesses and industrial domains.
• Score: 8.657062539499476
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The rapid advances in the Internet of Things (IoT) have promoted a revolution in communication technology and offered various customer services. Artificial intelligence (AI) techniques have been exploited to facilitate IoT operations and maximize their potential in modern application scenarios. In particular, the convergence of IoT and AI has led to a new networking paradigm called Intelligent IoT (IIoT), which has the potential to significantly transform businesses and industrial domains. This paper presents a comprehensive survey of IIoT by investigating its significant applications in mobile networks, as well as its associated security and privacy issues. Specifically, we explore and discuss the roles of IIoT in a wide range of key application domains, from smart healthcare and smart cities to smart transportation and smart industries. Through such extensive discussions, we investigate important security issues in IIoT networks, where network attacks, confidentiality, integrity, and intrusion are analyzed, along with a discussion of potential countermeasures. Privacy issues in IIoT networks were also surveyed and discussed, including data, location, and model privacy leakage. Finally, we outline several key challenges and highlight potential research directions in this important area.

Related papers

• Networking Systems for Video Anomaly Detection: A Tutorial and Survey [55.28514053969056]
  Video Anomaly Detection (VAD) is a fundamental research task within the Artificial Intelligence (AI) community. In this article, we delineate the foundational assumptions, learning frameworks, and applicable scenarios of various deep learning-driven VAD routes. We showcase our latest NSVAD research in industrial IoT and smart cities, along with an end-cloud collaborative architecture for deployable NSVAD.
  arXiv  Detail & Related papers  (2024-05-16T02:00:44Z)
• A Review on Internet of Things for Defense and Public Safety [0.9320657506524147]
  The Internet of Things (IoT) is undeniably transforming the way that organizations communicate and organize everyday businesses and industrial procedures. This survey analyzes the great potential for applying IoT technologies to revolutionize modern warfare and provide benefits similar to those in industry. It identifies scenarios where Defense and Public Safety could leverage better commercial IoT capabilities to deliver greater survivability to the warfighter or first responders.
  arXiv  Detail & Related papers  (2024-02-06T00:16:01Z)
• Introduction to IoT [0.0]
  The Internet of Things has rapidly transformed the 21st century. The integration of smart devices and automation technologies has revolutionized every aspect of our lives. It is also essential to recognize the significant safety, security, and trust concerns in this technological landscape.
  arXiv  Detail & Related papers  (2023-12-09T10:29:16Z)
• Trust-based Approaches Towards Enhancing IoT Security: A Systematic Literature Review [3.0969632359049473]
  This research paper presents a systematic literature review on the Trust-based cybersecurity security approaches for IoT. We highlighted the common trust-based mitigation techniques in existence for dealing with these threats. Several open issues were highlighted, and future research directions presented.
  arXiv  Detail & Related papers  (2023-11-20T12:21:35Z)
• From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks [82.964958051535]
  Generative Artificial Intelligence (GAI) possesses the capabilities of generating realistic data and facilitating advanced decision-making. By integrating GAI into modern Internet of Things (IoT), Generative Internet of Things (GIoT) is emerging and holds immense potential to revolutionize various aspects of society.
  arXiv  Detail & Related papers  (2023-10-27T02:58:11Z)
• Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges [55.82853124625841]
  Artificial General Intelligence (AGI) possesses the capacity to comprehend, learn, and execute tasks with human cognitive abilities. This research embarks on an exploration of the opportunities and challenges towards achieving AGI in the context of the Internet of Things. The application spectrum for AGI-infused IoT is broad, encompassing domains ranging from smart grids, residential environments, manufacturing, and transportation to environmental monitoring, agriculture, healthcare, and education.
  arXiv  Detail & Related papers  (2023-09-14T05:43:36Z)
• Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future [6.422895251217666]
  This paper reviews forensic and security issues associated with IoT in different fields. Most IoT devices are vulnerable to attacks due to a lack of standardized security measures. To fulfil the security-conscious needs of consumers, IoT can be used to develop a smart home system.
  arXiv  Detail & Related papers  (2023-09-06T04:41:48Z)
• AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges [60.56413461109281]
  Artificial Intelligence for IT operations (AIOps) aims to combine the power of AI with the big data generated by IT Operations processes. We discuss in depth the key types of data emitted by IT Operations activities, the scale and challenges in analyzing them, and where they can be helpful. We categorize the key AIOps tasks as - incident detection, failure prediction, root cause analysis and automated actions.
  arXiv  Detail & Related papers  (2023-04-10T15:38:12Z)
• Federated Learning for Industrial Internet of Things in Future Industries [106.13524161081355]
  The Industrial Internet of Things (IIoT) offers promising opportunities to transform the operation of industrial systems. Recently, artificial intelligence (AI) has been widely utilized for realizing intelligent IIoT applications. Federated Learning (FL) is particularly attractive for intelligent IIoT networks by coordinating multiple IIoT devices and machines to perform AI training at the network edge.
  arXiv  Detail & Related papers  (2021-05-31T01:02:59Z)
• Artificial Intelligence for Satellite Communication: A Review [91.3755431537592]
  This work provides a general overview of AI, its diverse sub-fields, and its state-of-the-art algorithms. The application of AI to a wide variety of satellite communication aspects have demonstrated excellent potential, including beam-hopping, anti-jamming, network traffic forecasting, channel modeling, telemetry mining, ionospheric scintillation detecting, interference managing, remote sensing, behavior modeling, space-air-ground integrating, and energy managing.
  arXiv  Detail & Related papers  (2021-01-25T13:01:16Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.