This special issue includes selected papers (with no less than 60% new content of the journal version) from the 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), October 30, 2021, online conference as well as an open call. The submitted manuscripts were reviewed by experts from both academia and industry. After two rounds of reviewing, the highest quality manuscripts were accepted for this special issue. This special issue will be published by Neural Computing and Applications as special issues. The papers are summarized as follows.

Qu et al. [1] presents a model-based single-phase fault-tolerant control as a safety measure that is able to estimate speed and signal delay for Hall-effect sensors of BLDC motors used in the active waist exoskeleton. Huo et al. [2] designed the backbone noise reduction network as a GAN framework that can be internally optimized. Wang et al. [3] puts forward the optimized BP neural system as the financial early warning model and ensures its high prediction accuracy. Aiming at these two difficulties, an intelligent traceability algorithm based on dynamic multi-mode optimization was designed and proposed in the work [4]. Key technologies for a digital twin-based shop floor management and control system are investigated, and the concept is designed and implemented by Peng and Zheng [5]. Huang and Guo [6] aims to make acupuncture give full play to its own advantages in the treatment of non-motor symptoms of Parkinson's disease by studying the meta-analysis of the efficacy of acupuncture and moxibustion in the treatment of non-motor symptoms of Parkinson's disease. Jiang et al. [7] examines the relationship between cloud-native architecture flexibility and cloud provider value and the processes and the boundary condition by which cloud-native architecture flexibility affects cloud provider value based on innovation theory and dynamic capability theory. Through the research on the application of convolutional neural network in the field of image segmentation, the problems of low segmentation accuracy, long time and high cost in the task of aerial image building image segmentation are solved to a certain extent [8]. Pang et al. [9] propose the network sorting rules and searching rules, and construct the network sorting search algorithm to track loan lost-linking customers in different address types. In the preprocessing of gesture images, an improved Otsu method is proposed to improve the real-time performance to realize the threshold segmentation of the human hand; then the morphological processing is carried out, and the median filter method is used to achieve image denoising to improve image quality [10].

Wang and Zhao [11] uses a combination method of qualitative and quantitative to identify the influencing factors of risk estimation to obtain relevant influencing factors, and verify the model proposed in this paper in combination with experimental research. Wu [12] completed the traditional image noise detection and segmentation experiment based on convolutional neural network. Based on the mixed Gaussian background model, the detection target is segmented by the different methods, and the most matching target track is found by using the location information and color information of the detection target, so as to realize the vehicle tracking [13]. Zhang et al. [14] uses it to understand the distribution law of traffic data and the internal connections between data, excavate traffic characteristics in smart cities, and accurately predict the future traffic situation, so as to solve the problems of traffic congestion and route planning in smart cities. A multi-scale memory-enhanced prediction method is proposed to describe fully characteristics of the data [15]. Li [16] presents an in-depth study and analysis of the AC drive control simulation of a supercapacitor tram using a high-order neural network pattern discrimination algorithm. Wu et al. [17] study the rough concept lattice and use the information flow to construct a second-order cone programming model for big data. The relay protection characteristics of DN under DG access are analyzed by Cui et al. [18]. Zhou et al. [19] examined the impacts of market conditions on the choice of contract and timing for information system outsourcing. Real options approach is applied to develop several analytical models to investigate the decision making for outsourcing information system.