








































American Journal of Agricultural Science, Engineering and Technology 

ISSN: 2158-8104 (Online), 2164-0920 (Print), 2017, Volume 1 Issue 1 30

TRAFFIC CONTROL PATCHING AND SECURITY SOLUTION IN IOT 

Afridi Shahid1, Md. Alam Hossain1*, Nazmul Hossain1 

ABSTRACT 

After connecting multiple devices to a network and possessing data analysis and 

excerpting, the IoT is awaited to contribute to the formation of new customer value. 

Critical infrastructure that gets into people’s lives and economic deeds will also become 

an area, in which way the IoT is used, so security measures for IoT systems are very 

important. On the other hand, a dramatic increase in the number of connected devices 

will create technical problems such as attacks with a broader scope of influence and 

attacks that last longer. So, a shortage of security operations administrators will also be 

a problem. The internet of things refers to a way of connecting objects to the Internet for 

the purpose of intelligent control and management. The objects are sensed through RFID 

(Radio-frequency identification) or sensors achieving the integration of human society 

and the information system. RFID is the core technology to implement the internet of 

things. So the security issue of RFID is becoming more and more important, in the past 

decade, a large number of research papers dealing with security issues of RFID 

technology have appeared. This paper deals with the security of data of RFID as IoT 

devices and defence against malware attacks, and DDoS attacks in IoT systems. 

Keywords: Security, Privacy, Cryptographic Hardware, IoT, System on Chip, 

Embedded Systems, RFID 
1 Department of Computer Science and Engineering, Jashore University of Science and 

Technology (JUST), Bangladesh 

* Corresponding Author: E-mail: alam@just.edu.bd

INTRODUCTION 

Internet Technology (IT) is very pervasive today. The number of digital devices connected to 

the Internet, those with a digital identity, is rapidly increasing day by day. With the 

developments in the technology, Internet of Things (IoT) become important part of human life. 

However, it is not well defined and secure. Now, various security issues are considered as 

major problem for a full-fledged IoT environment. There exists a lot of security challenges 

with the proposed architectures and the technologies which make the backbone of the Internet 

of Things. Some efficient and promising security mechanisms have been developed to secure 

the IoT environment, however, there is a lot to do. The challenges are ever rising and the 

solutions have to be ever elevating 

Literature summarized the security issues in the internet of things based on RFID, literature 

paid attention to the privacy models for RFID, literature explained mobile RFID network based 

on EPC and analyzed threats of the mobile RFID system, this is important to create a secure 

IOT architecture, literature analyzed RFID technology and its Applications in Internet of 

Things (IOT) from different layers, In this paper, we will first introduce the IOT based on RFID 

http://journals.e-palli.com/
mailto:alam@just.edu.bd


American Journal of Agricultural Science, Engineering and Technology 

ISSN: 2158-8104 (Online), 2164-0920 (Print), 2017, Volume 1 Issue 1 31

then we analyze the security issues in the IOT based on RFID , and on the basis of these, we 

will give the current countermeasures for the security of RFID data and malware attacks.. 

RFID SYSTEM WORKING PRINCIPLES 

a. System Composition

As per various applications, RFID frameworks maybe vary from one another on creation 

components. However, fundamentally, RFID framework is formed by tag, peruser and 

information trade and the executives framework. Electronic tag is created by coupling part and 

chip containing security rationale. 

b. Working Principle

As a serious programmed recognizable proof innovation, RFID actualizes non-contact full 

duplex information interchanges through RF to get target things distinguished. RFID label 

comprises of chip and radio wire and each label highlights exceptional item code. 

RFID framework can communicate information among transponder and sensor handset. The 

accompanying figure shows working guideline of RFID framework. 

Figure 1: RFID working principle 

When RFID framework is working, RF signals with a specific recurrence are initial 

communicated by peruser through recieving wire. As RFID label enters peruser's working field, 

the recieving wire will communicate actuated current so that RFID label will catch vitality that 

will be enacted to send their own code data to peruser. With regards to inactive frameworks, 

peruser will communicate RF signals at a specific recurrence through coupling segments. When 

RFID enters this field, vitality will be gotten through coupling segments to drive chips and 

peruser for correspondences. After peruser peruses self-coded data, it'll send it to information 

trade and the board framework. With regards to dynamic framework, after label enters peruser 

working region, installed battery will flexibly control so as to finish correspondences with 

peruser. 

http://journals.e-palli.com/


American Journal of Agricultural Science, Engineering and Technology 

ISSN: 2158-8104 (Online), 2164-0920 (Print), 2017, Volume 1 Issue 1 32

THE INTERNET OF THINGS BASED ON RFID 

Figure 2: Structure of IOT 

In the web of things dependent on RFID, RFID peruser is liable for gathering through this EPC 

code the middleware framework can discover relating IP address from the ONS foundation on 

the web, consequently the important data of the article can be gotten from this location. At that 

point the middleware framework (Savant framework) can measure and deal with the data. In 

this cycle there are neighborhood ONS worker, nearby PML worker and far off PML worker 

which are responsible for information stockpiling, as appeared in the Figure 2. 

SECURITY ISSUES 

Correspondence security treats 

a) Wireless correspondence chances In RFID framework remote correspondence is received

between the RFID perusers and RFID labels. Because of the receptiveness of the remote signs,

it is simple for an assailant to look, capture, screen, and jam remote correspondence signals.

So encryption and confirmation are expected to secure the remote transmission between the

RFID perusers and RFID labels.

b) Wired correspondence hazards Between the RFID perusers and the middleware framework,

information transmission is through the web. Much the same as customary organization

association, a sequential of safety efforts will be received for guaranteeing the information

classification and honesty, and the typical organization association.

c) Denial of Service (DOS) In both of remote and wired correspondence, there are Denial of

Service (DOS) . When assailants control countless phony perusers and labels, they can make

the information

d) Network Evasdropping

Organization listening in is an organization layer assault that centers around catching little 

bundles from the organization communicated by different PCs and perusing the information 

content looking for a data. This sort of organization assault is commonly one of the best as an 

absence of encryption administrations are utilized 

http://journals.e-palli.com/


American Journal of Agricultural Science, Engineering and Technology 

ISSN: 2158-8104 (Online), 2164-0920 (Print), 2017, Volume 1 Issue 1 33

Decryption 

Encryption 

Text Read the data Card 

Table 1: Security target and Solution 

Security target Security Solution 

IoT devices Privacy protection Blocking 

Anti-interference Data coding 
Data coding and data integrity 

Communication 

process 

Wireless communication 

risks(search, intercept, monitor, 

and jam wireless communication 

signals) 

the openness of the wireless signals 

wired communication risks The openness of the internet 

Denial of Service (DOS) Malicious attackers 

Network Eavesdropping Encryption 

EXISTING SYSTEM 

System 1: The card was read by the reader. The read information was encrypted by our 

encrypted software and this information will save to the cloud memory. When the raw 

information was needed, then only the administrator, who knew the decrypted private key could 

get the original information. As a result, the information of the card could not be theft through 

an unauthenticated person. Beside no one could duplicate the card and the authenticated card 

holder remains save from social engineering attack. It also helped the administrator that the 

information will save in the cloud memory with instant time. So administrator calculates the 

number of the uses of the card with exact time. DES algorithm is used in this system. The 

procedere of methodology are depicted as follows. 

Figure 3: DES algorithm 

This previous methodology could give the new technology some important security related in 

IOT. But it was unable to give the strong security that today’s life need, because of the 

popularities of IOT. Besides this technology left the discussion of traffic control of data which 

has a major impact in encryption and decryption system. 

In this paper, those problems are tried to solve through acceptable performances. 

System 2: There are some iot data transfer algorithm was introduced in past such as RST-IoT 

HCT-IoT .These algorithms are based on spanning tree theory. 

http://journals.e-palli.com/


American Journal of Agricultural Science, Engineering and Technology 

ISSN: 2158-8104 (Online), 2164-0920 (Print), 2017, Volume 1 Issue 1 34

Number of devices Avrg. Data Size (KB) RST-IoT HCT-IoT DES-IoT 

20 512 5.6 5.53 1.6 

40 1024 8.1 7.9 3.2 

60 2048 10.9 9.9 5.2 

100 3072 13.1 12.8 6.7 

Figure 4: spanning tree theory 

HCT- IoT RST-IoT 

Comparison all IoT DES-IoT 

http://journals.e-palli.com/


American Journal of Agricultural Science, Engineering and Technology 

ISSN: 2158-8104 (Online), 2164-0920 (Print), 2017, Volume 1 Issue 1 35

METHODOLOGY 

When data transfer from RFID tag to destination, at first data will be encrypted for defending 

data cloning and eavesdropping attack. Secondly, different malicious attacks will took place at 

data passing time are generated by intermediate nodes could be blocked by TCP algorithm. It 

also control the data traffic or jam to reach the destination 

TRAFFIC CONTROL PATCH 

Algorithm 

Here Tpr= packet pass runtime, t= present time, AP= Access point, If Tpr>t 

Then select malware, generated by intermediate node in descending order based on its power 

by patched intermediate node (Pin) 

And blocked them in run time 

Else if Tpr<t 

No action is needed 

When Tpr=t 

Always check the AP to control the traffic 

Calculation 1 portrays the nitty gritty strides in fixing stage. With restricted assets and 

endeavors, the administrator could give a fixed measure of patches on the halfway hubs (e.g., 

p rate). To ease the spread from the framework connects, the Pin most significant middle hubs 

will be chosen for fixing. It resembles to securing the most significant hub to keep up network 

power . Subsequently, we present the traffic checking span for assessing the significance 

of fixed halfway hubs. From the observed outcomes, the proposed traffic-control fixing plan 

sorts the malware in plunging request as per the intensity of traffic volumes, and the top 

moderate hubs are fixed. 

Self-evident, the proposed volume-based fixing is powerful to the assault which produces 

countless traffic , e.g., DDoS assaults. The fixed middle of the road hubs could forestall the 

redirection of malignant traffic presented by the DdoS assault dispatched by the IoT botnets. 

Finally the passage are likewise consistently checked all through the run time for making sure 

about information passing. 

Table 2: Performance Evaluation 

Number of devices Data size(KB) Execution Time (Per Device) 

20 512 1.6 sec 

40 1024 3.2 sec 

60 2048 5.2 sec 

100 3072 6.7 sec 

ACHITECTURE 

An architecture was created in a simulation software (securicad) to implement the proposed 

network.system.Here, I use a router as an IOT device. The simulation design is given below 

http://journals.e-palli.com/


American Journal of Agricultural Science, Engineering and Technology 

ISSN: 2158-8104 (Online), 2164-0920 (Print), 2017, Volume 1 Issue 1 36

Figure 5: Simulation designed in securicad 

RESULT ANALYSIS 

Here necessary security steps are taken against the attack such as- DDoS, Eavesdropping, IoT 

device blocking, Bypass antimalware, ARP Cache Poisoning, DNS Spoof, Find Exploit etc. 

The output result is given below- 

Table 3: Security steps against attacks 

Name Attack step Risk probability Risk 

Network ARP cash poisioning 0% No 

Network DNS spoof 0% No 

Network DoS 75% Medium 

Router DoS 0% No 

Host Bypass Antimalware 1% No 

Host DoS 0% No 

Host Find Exploit 0% No 

Dataflow Eavesdrop 0% No 

Comparison with existing system 

Conparison can be divided into two parts. i) Malware attack ii) Execution time 

Malware Attack 

Previous system prevented only data cloning attack but this methodology prevent other major 

attacks such as DDoS, Eavesdropping, IoT device blocking, Bypass antimalware, ARP Cache 

Poisoning, DNS Spoof, Find Exploit etc. 

Table 4: Comparison by attack 

Existing System Proposed system 

Data Cloning DDoS, 

Card cloning Eavesdropping 

Social engineering attacks IoT device blocking 

Bypass antimalware 

DNS Spoof 

Find Exploit 

http://journals.e-palli.com/


American Journal of Agricultural Science, Engineering and Technology 

ISSN: 2158-8104 (Online), 2164-0920 (Print), 2017, Volume 1 Issue 1 37

Execution time: 256 KB, 512 KB, 1 MB, 2 MB,3 MB sizes are taken of data with different 

number of devices at a single time and find the comparison given below 

Table 5: Comparison by execution time 

Data 

size(KB) 

Execution Time DES- 

IoT (Per Device) 

Data size(KB) Poroposed system’s 

Execution Time (Per Device) 

512 2.05 512 1.6 sec 

1024 4.05 1024 3.2 sec 

2048 6.25 2048 5.2 sec 

3072 7.5 3072 6.7 sec 

Figure 6: Comparison with existing method 

Above comparison, with security attack and execution time the proposed system shows better 

feedback than existing. Besides it helps to minimize the data traffic by given algorithm. This 

proposed system creates a new era to IOT, giving combination among encryption, defend 

malware attacks and traffic control. 

CONCLUSION 

The IOT utilizes an assortment of data detecting ID gadget and data preparing hardware, for 

example, RFID, WSN, GPRS, and so on consolidating with the Internet to shape a broad 

organization so as to informationize and intelligentize the substances or articles. This paper 

dissects the applications and difficulties of RFID innovation, which is the significant and 

primary part of IOT. 

REFERENCES 

An ontology-based context model for wireless sensor network (WSN) management in the 

Internet of Things. Journal of Sensor and Actuator Networks, 2(4), pp.653-674. 40. Al- 

Turjman, F. and Malekloo, A., 2019. 

An overview of Internet of Things (IoT) and data analytics in agriculture: Benefits and 

challenges. IEEE  Internet of  Things  Journal, 5(5), pp.3758-3773. 

Benaissa, S., Plets, D., Tanghe, E., Trogh, J., Martens, L., Vandaele, L., Verloock, L., 

Tuyttens, F.A.M., Sonck,  B.  and  Joseph,  W., 2017. 

Brown, Eric (13 September 2016). "Who Needs the Internet of Things?". Linux.com. Retrieved 

23 October 2016. 

http://journals.e-palli.com/


American Journal of Agricultural Science, Engineering and Technology 

ISSN: 2158-8104 (Online), 2164-0920 (Print), 2017, Volume 1 Issue 1 38

Dr. S. S. Manikandasaran, 2016,"Security Attacks and Cryptography Solutions for Data Stored 

in Public Cloud Storage" (IJCSITS), 

E. Ronen and A. Shamir, "Extended Functionality Attacks on IoT Devices: The Case Of Smart

Lights", Proc. IEEE S&P Europe 2016, Mar. 2016. 

Floerkemeier, C., Roduner, C. and Lampe, M., 2007. RFID application development with the 

Accada middleware platform. IEEE Systems Journal, 1(2), pp.82-94. Liu, Y., Seet, 

B.C. and Al-Anbuky, A., 2013.

"Internet of Things: Science Fiction or Business Fact?" (PDF). Harvard Business Review. 

November 2014. Retrieved 23 October 2016. 

Internet of animals: characterisation of LoRa sub-GHz off-body wireless channel in dairy 

barns. Electronics Letters, 53(18), pp.1281-1283. 43. García-Lesta, D., Cabello, D., 

Ferro, E., López, P. and Brea, V.M., 2017. 

IOT for smart farm: A case study of the Lingzhi mushroom farm at Maejo University. 

In 2017 14th International Joint Conference on Computer Science and Software 

Engineering (JCSSE) (pp. 1-6). IEEE. 45. Viani, F., Bertolli, M., Salucci, M. and 

Polo, A., 2017. 

J. Granjal, E. Monteiro and J. Silva, "Security for the Internet of Things: A Survey of Existing

Protocols and Open Research Issues", IEEE Commun. Surveys & Tutorials, vol. 17, pp. 

1294-1312, July 2015. 

Low-cost wireless monitoring and decision support for water saving in agriculture. IEEE 

Sensors Journal, 17(13), pp.4299-4309. 

M. Miettinen et al., IoT Sentinel: Automated Device-Type Identification for Security

Enforcement in IoT, CoRR, 2016. 

P.-Y. Chen et al., "Decapitation via Digital Epidemics: A Bio-Inspired Transmissive Attack", 

IEEE Commun. Mag., vol. 54, no. 6, pp. 75-81, June 2016. 

P.-Y. Chen, S.-M. Cheng and K.-C. Chen, "Optimal Control of Epidemic Information 

Dissemination over Networks", IEEE Trans. Cybernetics, vol. 44, no. 12, pp. 2316-28, 

Dec. 2014. 

P. Wang et al., "Understanding the Spreading Patterns of Mobile Phone Viruses", Science, vol.

324, no. 5930, pp. 1071-75, May 2009. 

P.-Y. Chen et al., "Decapitation via Digital Epidemics: A Bio-Inspired Transmissive Attack", 

IEEE Commun. Mag., vol. 54, no. 6, pp. 75-81, June 2016. 

P.-Y. Chen et al., "Decapitation via Digital Epidemics: A Bio-Inspired Transmissive Attack", 

IEEE Commun. Mag., vol. 54, no. 6, pp. 75-81, June 2016. 

R Khan,2012,Future Internet: The Internet of Things Architecture,Possible Applications and 

Key Challenges, 

S. Babar,2011,Proposed Embedded Security Framework for Internet of Things (IoT), 978-1-

4577-0787-2/11/$26.00 2011 IEEE 

S. Tanachaiwiwat and A. Helmy, "Encounter-Based Worms: Analysis and Defense", Ad Hoc

Net., vol. 7, no. 7, pp. 1414-30, Sept. 2009. 

Smart parking in IoT-enabled cities: A survey. Sustainable Cities and Society, p.101608. 41. 

Elijah, O., Rahman, T.A., Orikumhi, I., Leow, C.Y. and Hindia, M.N., 2018. 

Springer International Publishing AG 2017G. Wang et al. (Eds.): SpaCCS 2017 Workshops, 

LNCS 10658, pp. 607–616, 2017. 

Wireless sensor network with perpetual motes for terrestrial snail activity monitoring. 

IEEE Sensors Journal, 17(15), pp.5008-5015. 44. Chieochan, O., Saokaew, A. and 

Boonchieng, E.,  2017, July. 

http://journals.e-palli.com/



