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Security and privacy issues for artificial intelligence in edge-cloud computing

Edge computing has emerged as a popular computing paradigm with the aim to minimize the delay between end-users and the cloud. A wide range of artificial intelligence applications benefit from the low latency offered by edge computing, e.g., driverless cars, smart homing, etc. However, edge computing suffers from capacity limitations and is challenged by computationally expensive artificial intelligent applications. To overcome these limitations, the edge-cloud computing paradigm offers a trade-off between artificial intelligence applications, requirements for computing resources and low latency. Unlike the centralized cloud, in the edge-cloud environment, there is a lack of security technologies and privacy protection mechanisms specifically designed for artificial intelligence applications facilitated by the edge-cloud computing paradigm. In the edge-cloud environment, artificial intelligence applications are subject to a variety of security threats, such as data privacy disclosure, adversarial attacks, confidential attacks, etc. This thematic series shares and discusses recent advances and future trends of security and privacy issues for artificial intelligence in edge-cloud computing.

Guest editors:
Lianyong Qi, Qufu Normal University, China
Jianxin Li, Beihang University, China
Nick Antonopoulos, Edinburgh Napier University, UK
Hao Wang, Norwegian University of Science and Technology, Norway

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    Authors: Jindong Zhao, Wenshuo Wang, Dan Wang, Xuan Wang and Chunxiao Mu
    Citation: Journal of Cloud Computing 2022 11:96
  4. K-anonymity has been gaining widespread attention as one of the most widely used technologies to protect location privacy. Nevertheless, there are still some threats such as behavior deception and service swin...

    Authors: Manxiang Yang, Baopeng Ye, Yuling Chen, Tao Li, Yixian Yang, Xiaobin Qian and Xiaomei Yu
    Citation: Journal of Cloud Computing 2022 11:2
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    Authors: Xiaogang Xing, Yuling Chen, Tao Li, Yang Xin and Hongwei Sun
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  6. Due to the high risk factors in the electric power industry, the safety of power system can be improved by using the surveillance system to predict and warn the operators’ nonstandard and unsafe actions in rea...

    Authors: Yanfang Yin, Jinjiao Lin, Nongliang Sun, Qigang Zhu, Shuaishuai Zhang, Yanjie Zhang and Ming Liu
    Citation: Journal of Cloud Computing 2021 10:17
  7. Intelligent transportation brings huge benefits to humans’ life and Industrial production in terms of vehicle control and traffic management. Now, the development of edge-cloud computing has once again promote...

    Authors: Bin Xie, Kun Zhang, Yi Zhao, Yunchun Zhang, Ying Cai and Tian Wang
    Citation: Journal of Cloud Computing 2021 10:10
  8. With the rapid development of hospital informatization and Internet medical service in recent years, most hospitals have launched online hospital appointment registration systems to remove patient queues and i...

    Authors: Junshu Wang, Guoming Zhang, Wei Wang, Ka Zhang and Yehua Sheng
    Citation: Journal of Cloud Computing 2021 10:4
  9. Data redundancy is a significant issue that wastes plenty of storage space in the cloud-fog storage integrated environments. Most of the current techniques, which mainly center around the static scenes, for ex...

    Authors: Shynu P. G., Nadesh R. K., Varun G. Menon, Venu P., Mahdi Abbasi and Mohammad R. Khosravi
    Citation: Journal of Cloud Computing 2020 9:61
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    Authors: Xiaoping Zhao, Kaiyang Lv, Zhongyang Zhang, Yonghong Zhang and Yifei Wang
    Citation: Journal of Cloud Computing 2020 9:58
  11. The video request service of users in 5G network will explode, and adaptive bit rate technology can provide users with reliable video response. Placing video resources on edge servers close to users can overco...

    Authors: Zhi Liu, Bo Qiao and Kui Fang
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  12. This paper proposes a collaborative scheduling strategy for computing resources of the Internet of vehicles considering location privacy protection in the mobile edge computing environment. Firstly, a multi ar...

    Authors: Meiyu Pang, Li Wang and Ningsheng Fang
    Citation: Journal of Cloud Computing 2020 9:52
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    Authors: Chao Liu, Jianbo Gao, Yue Li, Huihui Wang and Zhong Chen
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    Authors: Wei Tian, Lei Yi, Wei Liu, Wei Huang, Guangyi Ma and Yonghong Zhang
    Citation: Journal of Cloud Computing 2020 9:22
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    Authors: Xianrui Yang, Yuming Liu, Jiehong Wang, Zhao Yao, Yanping Zhou and Shucun Fu
    Citation: Journal of Cloud Computing 2020 9:20