A Secure and Anonymous Communicate Scheme over the Internet of Things

Sun, Qindong; Lin, Kai; Si, Chengxiang; Xu, Yan; Li, Shancang; Gope, Prosanta

doi:10.1145/3508392

Cited by 47 publications

(30 citation statements)

References 31 publications

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“…On the one hand, foreign companies have a good organizational structure, advanced management system, and extremely advanced information technology through reorganization of business processes, so that they can provide products and services with lower costs and better quality. Logistics enterprises will continue to participate in market competition with better services and lower costs and will change the management model through process transformation to improve the competitiveness of logistics enterprises [14][15][16][17][18]. (3) Chinese logistics companies are facing new challenges and opportunities.…”

Section: Changes In the External Environment Of Logistics Companiesmentioning

confidence: 99%

Intelligent Logistics Enterprise Management Based on the Internet of Things

2022

Mathematical Problems in Engineering

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At this stage, many large domestic logistics companies have problems such as complex processes, low efficiency, and chaotic vehicle management. This usually leads to vehicle failure, material loss, or improper installation of the company’s factory, which affects the company’s interests and damages the company’s reputation. In response to the above problems, this article proposes, designs, and implements an intelligent logistics management system based on the Internet of Things technology through the research of the Internet of Things technology at home and abroad. The specific content is as follows: one is to study the origin and current situation of the Internet of Things technology at home and abroad, to understand related theories and cutting-edge technologies of the Internet of Things; the other is to imitate intelligent logistics companies, study the processes and existing problems of the logistics link, and integrate the management concepts of the Internet of Things. A model of intelligent logistics enterprise management is established with enterprise intelligent technology; the third is to conduct an experiment on the management of an intelligent logistics enterprise and do an experimental data analysis of the management of an intelligent logistics enterprise. Experimental research shows that the data of factors affecting logistics operations in smart logistics companies are low, and smart logistics companies are operating in good condition, and the established data model is suitable for smart logistics enterprise management. The Internet of Things and intelligent logistics management are both emerging concepts, while the intelligent logistics management based on the Internet of Things is still in its infancy, and relevant scholars have little research on the intelligent logistics management based on the Internet of Things. It plays a guiding role for the intelligent logistics management of enterprises and promotes the management of intelligent logistics enterprises.

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Section: Changes In the External Environment Of Logistics Companiesmentioning

confidence: 99%

Intelligent Logistics Enterprise Management Based on the Internet of Things

2022

Mathematical Problems in Engineering

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“…Human resource allocation can help enterprises optimize talent management, improve employee quality, and improve the strength of the enterprise. It can also help employees in the enterprise match the most suitable jobs and ultimately achieve the optimal management of human resources in enterprise operations [11][12][13].…”

Section: Human Resource Allocationmentioning

confidence: 99%

Enterprise Human Resource Allocation under the Background of Wireless Communication and Internet of Things

Cao

2022

Mathematical Problems in Engineering

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With the rapid development of computer software and hardware technology, new progress has been made in wireless communication technology, and the Internet of Things technology has gradually penetrated into the daily work of citizens, which has led to a comprehensive upgrade of the work mode. In the context of increasing technological progress, market competition in various industries has gradually intensified, and enterprises also need to make corresponding adjustments to adapt to the development of the times. Human resource management, as the most important management link of contemporary enterprises, has a non-negligible influence on the development of enterprises, especially large and medium-sized enterprises. In order to adapt to the development of the times, most enterprises will choose to make timely adjustments to human resource allocation strategies. If an enterprise wants to develop in the fiercely competitive market, it needs to excavate talents and configure a reasonable human resource system. Starting from the related concepts of wireless communication, Internet of Things technology, and enterprise human resource allocation, this paper adopts the method of questionnaire survey to analyze the current situation and existing problems of human resource allocation in a large banking enterprise and then proposes targeted solutions for the existing problems. The ultimate goal of the plan is to optimize the allocation of human resources in the enterprise. The contribution of this paper is to select the relatively special field of banking for investigation and analysis, which fills the research gap to a large extent.

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“…However many studies on adversarial examples [ 3 , 4 ] have proclaimed the vulnerability of DNN models, which brings great security risks to the deployment of DNN models in practical applications. Even in a DNN-based system with communication security defenses [ 5 ], attackers can break it by adding adversarial perturbations to the transmitted data in advance [ 6 , 7 ]. For example, when a DNN model is used for traffic sign recognition in an automatic driving system, attackers can maliciously modify the captured road sign image, causing the model to give false inference, which leads to the decision system making wrong judgments.…”

Section: Introductionmentioning

confidence: 99%

ABCAttack: A Gradient-Free Optimization Black-Box Attack for Fooling Deep Image Classifiers

Cao

Sun

et al. 2022

Entropy

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The vulnerability of deep neural network (DNN)-based systems makes them susceptible to adversarial perturbation and may cause classification task failure. In this work, we propose an adversarial attack model using the Artificial Bee Colony (ABC) algorithm to generate adversarial samples without the need for a further gradient evaluation and training of the substitute model, which can further improve the chance of task failure caused by adversarial perturbation. In untargeted attacks, the proposed method obtained 100%, 98.6%, and 90.00% success rates on the MNIST, CIFAR-10 and ImageNet datasets, respectively. The experimental results show that the proposed ABCAttack can not only obtain a high attack success rate with fewer queries in the black-box setting, but also break some existing defenses to a large extent, and is not limited by model structure or size, which provides further research directions for deep learning evasion attacks and defenses.

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A Secure and Anonymous Communicate Scheme over the Internet of Things

Cited by 47 publications

References 31 publications

Intelligent Logistics Enterprise Management Based on the Internet of Things

Intelligent Logistics Enterprise Management Based on the Internet of Things

Enterprise Human Resource Allocation under the Background of Wireless Communication and Internet of Things

ABCAttack: A Gradient-Free Optimization Black-Box Attack for Fooling Deep Image Classifiers

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