Overview of Enterprise IoT Security System based on Edge

Computing

Liyun Lan, Jiujun Bai and Xuebo Chen

School of Electronic and Information Engineering, University of Science and Technology Liaoning,

Qianshan road, Anshan 114051, Liaoning, China

Keywords: Internet of Things, Edge Computing, Enterprise Security System.

Abstract: The topic of security runs through the development of human society, and it exists in all aspects of our lives

and work. In order to better ensure the safety of the employees in enterprises, the enterprise IoT security

system should be established. With the development of technology, the application of IoT in enterprise

security has made some progress. Since more and more devices are connected to the Internet and generate big

data, cloud computing is no longer sufficient to process and analyse IoT devices in real time. Especially the

data is generated by different digital platforms involving enterprise production, management and safety.

Therefore, edge computing can be taken into account. This paper briefly introduces the development status

of Internet of Things technology and edge computing technology comparing with cloud computing. It should

be helpful for us that edge computing is proposed to apply to enterprise IoT security system.

1 INTRODUCTION

The process of production in the enterprise is

complex, the operation line is long and it has strong

continuity. During the production process, it not only

has the characteristics of high temperature, high

pressure and high energy, but also involves the toxic,

harmful, flammable and explosive substances in the

production process. Meanwhile, there is also the

hidden danger of mechanical injuries such as high-

rise buildings, mechanical processing and so on,

which are prone to fall from high places and objects

to strike (Wang Shuming, 2016, Pan Zhixing, 2015).

With the acceleration of China's modernization

process, enterprises have developed at a high speed,

but at the same time, the probability of serious

accidents such as fires, explosions, poisonings, and

leakages has also increased year by year. Starting

from the regularity of accidents, effective early

warning of accident symptoms has become an

important way to reduce accident losses (Xu

Yangguang, Chen Xuebo, Sun Qiubai, 2017).

With the increasing progress of technology, there

have been many cases of Internet of Things (IoT)

applied to enterprise security. However, because

https://orcid.org/0000-0001-6799-7667

more and more devices are connected to the Internet

and generate data, cloud computing is no longer

sufficient to process and analyze data generated or to

be generated by IoT devices and other digital

platforms in real time, especially in the case of safe

production in enterprises. In order to make up for the

shortcomings of both the amount of data and the

transmission rate of cloud computing in the security

system, so that it can process the received data faster

and more efficiently, it is necessary to "sink" some

functions of cloud computing. Edge computing came

into being at the historic moment.

2 IoT TECHNOLOGY RELATED

RESEARCH

This section summarizes the development and

application research of IoT technology.

2.1 Development History of Internet of

Things Technology

The Internet of Things originated in the 1990s. In the

early 1990s, the MIT Auto-ID Laboratory set the

Lan, L., Bai, J. and Chen, X.

Overview of Enterprise IoT Security System based on Edge Computing.

DOI: 10.5220/0009407103210326

In Proceedings of the 5th International Conference on Internet of Things, Big Data and Security (IoTBDS 2020), pages 321-326

ISBN: 978-989-758-426-8

321

Electronic Coding Standard (EPC). The designation

of this standard makes the radio frequency

identification technology (RFID) more widely used in

various fields. Build an EPC real-time tracking

information system based on the EPC standard, which

can virtually connect objects to the Internet (Liu

Qibiao, Chen Zhiming, 2015, Gui Jinsong, 2013). In

1995, Bill Gates first proposed the rudiment of the

Internet of Things concept connected by "thing to

thing", which is the idea of interconnection. And it is

also known as the "Internet of Things" in English

(Bill Gates book, 1996). In 1998, the Massachusetts

Institute of Technology put forward the concept of the

Internet of Things. In the same year, the Automatic

Identification Center put forward the preliminary

concept of the Internet of Things. At the WSIS

Information World Summit in 2005, the International

Telecommunication Union formally proposed the

concept of the "Internet of Things" in its report (ITU

Internet Reports, 2005), stating that the Internet of

Things includes the networking and application of all

items.

Since its inception, the Internet of Things has

sustained innovation and strong impetus, and its

applications involve defense military (Furtak, J.,

Zielinski, Z., Chudzikiewicz, J., 2016,Wang J, Jiang

F, Xie C, 2012), intelligent transportation (Zhang G

W., 2013), smart grid (Zeng Li, Xu Xin, Zeng Dajun,

2017, Yang W, Peng Z, Yu H, et al, 2013, Liu B W,

Zhou H, 2013), smart home, medical and health (Li

Cuijin, 2017, Liu Qibiao, Chen Zhiming, 2015) and

many other fields. It played an active role in them.

2.2 The Application Status of Internet

of Things Technology

Sun Qibo et al. summarized the key technologies

which are involved in the Internet of things and

proposed the technology system model of the Internet

of things (Sun Qibo, Liu Jie, Li Li Li, Fan Chunxiao,

Sun Juanjuan, 2010). The architecture system of the

Internet of things technology is shown in figure 1.

Yan Tao and Lv Limin applied the Internet of things

technology to the enterprise safety production

monitoring system, and elaborated the design process

from the aspects of the Internet of things architecture,

the overall design of the security monitoring system,

and the realization of functions (Yan Tao, Lv Limin,

2012). Literature (Chen Xuebo, sun Qiubai, 2015)

established the framework of the behavioral safety

management system consisting of people, things and

environment, and established an early warning

system for unsafe behaviors to dynamically track and

monitor human behaviors by utilizing the Internet of

things technology, complex system theory and

behavioral safety management method. Liu Zude and

Li Pengfei proposed to apply the Internet of things

technology to the accident early warning system of

metallurgical enterprises, and proposed the basic

framework of the enterprise accident early warning

system based on the Internet of things architecture,

(Liu Zude, Li Pengfei, 2015). Based on the existing

traditional video monitoring, the paper (Su Huo, Liu

Xiaodong, 2016) used OpenCV visual library and

C++ to realize face recognition, and implemented the

judgment of suspicious persons in the prohibited area.

Literature (Zhang Li, 2013) used video analysis

technology and Internet of things technology to

develop an intelligent video monitoring system with

multiple functions including area invasion, object

detection, smoke detection, direction and path

detection of moving objects. In literature (Zhang Yi,

2010, Wang Yucheng, 2016), intelligent video

recognition algorithm was studied in depth to

improve the feature extraction algorithm of moving

target detection. It also defined the abnormal

behavior, recognized the behavior of moving objects,

and rose them to the height of the event. Literature

(Hu Dongtao, 2014, Qin Jianwang, 2012)

respectively established a set of underground mine

behavior safety monitoring and warning system based

on Internet of things technology. The real-time

dynamic detection subsystem was established to

collect personnel positioning information and

underground mine environment information in real

time. Ground monitoring subsystem was built to

analyze online information and warn timely. And it

also designed personnel location, environment

detection terminal software, hardware, and ground

hand-held security information query terminal

equipment. The above researches are the applications

of Internet of things technology in video recognition,

and the algorithm and model are given in detail.

However, they are only one part of the whole

enterprise security system, which needs to consider

other subsystem.

In literature (Sun, E., Zhang, X., & Li, Z.,

2012), the monitoring and early warning system

(TDMPAS) of tailing dam based on Internet of

things and cloud computing was realized, and the

system structure of the early warning system was

given to realize the real-time monitoring of

saturation line, stagnant water level and dam

deformation of tailing dam. In literature (Wu, Y.,

Chen, M., Wang, K., & Fu, G., 2019), the

underground dynamic information platform of coal

mine based on Internet of things

technology was

established. The platform was divided into six

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functional layers: support layer, perception layer,

transmission layer, service layer, data extraction layer

and application layer. This platform can monitor and

record the working condition data of coal mine

production system, as well as the location information

of underground equipment and miners. Based on

cloud computing technology, it can quickly analyze

the big data related to underground coal mines and

accurately extract the key data related to users' needs.

Literature (Chen, L. R. Cao, J. F., 2018) described the

architecture and key technologies of industrial

Internet of things. Literature (2017) introduced

outliers detection and spatiotemporal statistical

analysis based on cluster analysis. It also presented a

real-time monitoring, event reporting and early

warning platform based on RSS distance weighted

centroid localization algorithm. The platform used the

Internet of things, cloud computing, real-time

operation database, application gateway and

application program interface to seamlessly integrate

the monitoring, analysis and localization methods. In

literature (Dong, L.J., Shu, W.W., Sun, D.Y., Li, X.B.,

Zhang, L.Y., 2017), a multiple key information

system of tailing pond was constructed based on the

Internet of things and wireless network, and also

utilizing the sensor data including the stability

indicators such as diving line, reservoir water level,

internal and external deformation of tailing pond. The

basic system was given and the simulation analysis

was carried out. In reference (Bo, C., Xin, C.,

Zhongyi, Z., Chengwen, Z., & Junliang, C, 2014), a

remote monitoring system was proposed based on the

Internet of things, which made full use of wireless

sensor network and combined with CAN bus

communication technology to abstract the data and

capabilities of underground sensors into WoT

resources, and services were provided through

representational state transfer (REST). The above

researches are all based on the applications of Internet

of things technology in enterprises, such as

metallurgical enterprises, underground mines, etc.,

but they are all about the framework research, lacking

in-depth study of specific models and algorithms.

3 RESEARCH ON EDGE

COMPUTING TECHNOLOGY

In 2004, Pang (PANG H H, TAN K L, 2004)

proposed edge computing in the open literature for

the first time in the 20th IEEE International

Conference. It mentioned that "Edge computing is to

implement extensible and highly available web

services, which will promote the logic and data

processing center of the enterprise to the edge side of

proxy services. Its advantage is that the operation of

applications on the edge side reduces network latency

and produces faster web service response". Shi

Weisong and others systematically introduced the

concept and principle of edge computing. It

instantiated the concept of edge computing through

existing cases as well (Shi Weisong, Sun Hui, Cao

Jie, Zhang Quan, Liu Wei, 2017). Edge computing

refers to a distributed open platform that integrates

the core capabilities of network, computing, storage

and applications on the edge of the network close to

the object or data source to provide edge intelligent

services nearby (SHI W S, CAO J, ZHANG Q, et al,

2016, HU Y C, PATEL M, SABELLA D, et al, 2015).

Reference (Li Linzhe, Zhou Peilei, Cheng Peng, Shi

Zhiguo, 2019) introduced the concept and general

architecture of edge computing. Its general

architecture is shown in Figure 2, which introduces

the application of edge computing. The general

architecture of edge computing is divided into three

layers , that is terminal layer, edge computing layer

and cloud computing layer. Each layer can

communicate with each other and across layers. The

composition of each layer determines the computing

and storage capacity of each layer, and thus it

determines the functions of each layer.

(1) Terminal layer

The terminal layer is composed of various Internet of

things devices such as sensors, RFID tags, cameras,

smart phones and the like, which mainly completes

the function of collecting original data and reporting.

In the terminal layer, only the perception ability of

various IOT devices is considered, but not their

computing ability. Billions of Internet of things

devices in the terminal layer continuously collect all

kinds of data, taking the form of event source as the

input of application services.

(2) Edge computing layer

Edge computing layer is composed of network edge

nodes, which are widely distributed between terminal

equipment and computing center. It can be intelligent

terminal equipment itself, such as smart bracelet,

smart camera, etc., or it can be deployed in network

connection, such as gateway, router and so on.

Obviously, the computing and storage resources of

the edge node are quite different, and the resources of

the edge node are dynamic. For example, the

available resources of the intelligent bracelet are

dynamic with the use of people. Therefore, how to

allocate and schedule computing tasks in dynamic

network topology is worth studying. The edge

computing layer realizes the basic service response by

Overview of Enterprise IoT Security System based on Edge Computing

323

reasonably deploying and deploying the computing

and storage capabilities on the edge of the network.

Figure 1: Basic structure of enterprise safety system based

on Internet of Things.

(3) Cloud computing layer

In the joint services of cloud edge computing, cloud

computing is still the most powerful data processing

center. The reported data of the edge computing layer

will be stored permanently in the cloud computing

center. The analysis tasks and comprehensive global

information processing tasks that cannot be processed

by the edge computing layer still need to be

completed in the cloud Computing Center. In

addition, cloud computing center can dynamically

adjust the deployment strategy and algorithm of edge

computing layer according to the distribution of

network resources.

In reference (Qi Bing, Xia Yan, Li Bin, Shi Kun,

Xue Mingfeng, 2018), a family energy system

framework based on edge computing was proposed, a

four-tier architecture based on data fusion and

operation collaboration between heterogeneous

platforms was designed, and detailed design schemes

of several common subsystems were given, which

provides new ideas for the application of edge

computing technology in the field of intelligent

energy use. Reference (An Xingshuo, Cao Guixing,

Miao Li, Ren Shubo, Lin Fuhong, 2018) introduced

the basic concept, system architecture and the

relationship with other computing paradigms of edge

computing, analyzed the security threats existing in

current edge computing, and discussed the

corresponding security technology issues for various

security threats. In reference (Sun Jie, Qian Lei,

2019), it was proposed to add moving object detection

algorithm to the webcam to process the collected

original video data, remove redundant information,

and analyze the behavior in the video, and only

transmit the most valuable data to the cloud

computing center. Yu Tianqi and others proposed the

monitoring system framework of the Internet of

things based on edge computing (Yu Tianqi, Zhu

Yongxu, Wang Xianbin, 2018).

Figure 2: General architecture of edge computing.

Figure 3: Cloud computing paradigm.

4 COMPARISON BETWEEN

CLOUD COMPUTING AND

EDGE COMPUTING

This chapter mainly compares cloud computing

and edge computing from the models based on

existing research.

4.1 Cloud Computing

Figure 3 shows the traditional cloud computing

model. In this model, the source data is sent by the

producers to the cloud computing center and the

end users send the usage request to the cloud

computing center (Shi Weisong, Sun Hui, Cao Jie,

Zhang Quan, Liu Wei, 2017). In figure 3, The solid

blue line represents the data producers sending the

source data to the cloud computing center, the

dashed red line represents the end users sending the

usage requests to the cloud computing center, and

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the dashed brown line represents the cloud

computing center feeding back the data result to the

end users.

4.2 Edge Computing

Edge computing refers to an open platform that

integrates network, computing, storage and

application core capabilities on the side close to the

objects or data source to provide the nearest terminal

services. Its applications are launched on the edge,

generating faster network service responses to meet

the industry's basic needs in real-time business,

application intelligence, security and privacy

protection. Edge computing is located between the

physical entity and the industrial connection, or at the

top of the physical entity.

Figure 4: Edge computing paradigm.

From the above model, we can find that the edge

computing model is to migrate some or all of the

computing tasks from the original cloud computing

center to execute near the source data. Therefore, it

has advantages in some aspects, for instance, data

transmission performance and real-time data

processing. However, it has higher requirements on

data privacy protection and security, service

management, data abstraction and other aspects.

These aspects deserve our in-depth study.

5 SUMMARY

With the rapid development of Internet of things

technology, edge computing has been highly

concerned and recognized by the government,

industry and academia at home and abroad because it

provides new solutions to the complex challenges in

the field of Internet of things, such as massive data

transmission and real-time service response. This

paper introduces the development and applications of

Internet of things technology and edge computing

technology. Edge computing extends the computing

and storage capabilities of cloud computing to the

edge of the network, provides local computing

services with low latency, high availability and

privacy protection, and solves the problems of cloud

computing such as high latency and network

environment constraints. Therefore, we can apply

edge computing to the enterprise IOT security

system, providing a new method for the security of

employees, environment and equipment.

ACKNOWLEDGEMENTS

The research reported herein is supported by the

NSFC of China under Grants Nos. 71571091,

71771112 and 71371092, and by University of

Science and Technology Liaoning Talent Project

Grants No. 601011507-03.

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