A Survey on Access Control in the Age of Internet of Things

By Jing Qiu, Zhihong Tian, Chunlai Du, Qi Zuo, Shen Su, Binxing Fang. IEEE Internet of Things Journal, 2020

347 citations recorded by the source corpus.

With the development of Internet-of-Things (IoT) technology, various types of information, such as social resources and physical resources, are deeply integrated for different comprehensive applications. Social networking, car networking, medical services, video surveillance, and other forms of the IoT information service model gradually change people’s daily lives. Facing the vast amounts of IoT information data, the IoT search technology is used to quickly find accurate information to meet the real-time search needs of users. However, IoT search requires using a large amount of user private information, such as personal health information, location information, and social relations information, to provide personalized services. Employing private information from users will encounter security problems if an effective access control mechanism is missing during the IoT search process. An access control mechanism can effectively monitor the access activities of resources and ensure that authorized users access information resources under legitimate conditions. This survey examines the growing literature on access control for an IoT search. Problems and challenges of access control mechanisms are analyzed to facilitate the adoption of access control solutions in real-life settings. This article aims to provide theoretical, methodological, and technical guidance for IoT search access control mechanisms in large-scale dynamic heterogeneous environments. Based on a literature review, we also analyzed the future development direction of access control in the age of IoT.

Subfields: Artificial Intelligence, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/0a3a461adb7cd71fd94f634e87609f6b05df0b8c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jing Zhang
2. Dacheng Tao
3. Xiaojiang Du
4. Mohsen Guizani
5. Jiankun Hu
6. Yanming Zhu
7. Zhihong Tian
8. Xuefei Yin

In Sociology and Political Science

1. Dacheng Tao
2. Jing Zhang
3. Jiankun Hu
4. Yanming Zhu
5. Ali Kashif Bashir
6. Xuefei Yin

Citations in the corpus

• CorrAUC: A Malicious Bot-IoT Traffic Detection Method in IoT Network Using Machine-Learning Techniques (2021, background): “NOWADAYS, the Internet-of-Things (IoT) technology is growing up more day by day [1], and in every minute, numerous devices are getting connected with this technology.”
• Empowering Things With Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things (2020, background): “Recently, access control [58] and trust management [59] approaches have been reviewed to protect the security and privacy of IoT.”
• A Comprehensive Survey of Privacy-preserving Federated Learning (2021, background): “Cao et al. [16] developed an FL framework based on the local differential privacy to achieve the privacy-preserving in the Internet-of-Things [141].”