The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.

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International Journal of Computer
Networks & Communications (IJCNC)
ISSN 0974 - 9322 (Online) ; 0975 - 2293
(Print)
http://airccse.org/journal/ijcnc.html
Contact US: ijcnc@airccse.org

2. AN EFFICIENT DATA COLLECTION PROTOCOL FOR UNDERWATER
WIRELESS SENSOR NETWORKS
Khaled Day1
, Faiza Al-Salti2
, Abderezak Touzene1
and Nasser Alzeidi1
1
Department of Computer Science, Sultan Qaboos University, Muscat, Oman
2
Muscat College, Muscat, Oman
Abstract
This paper presents the design and evaluation of a new data collection protocol for Underwater
Wireless Sensor Networks called the Data Collection Tree Protocol (DCTP). It uses an efficient
distributed algorithm to proactively construct and maintain a data collection tree rooted at the
sink node. The preconstructed and maintained data collection tree allows the efficient selection
of a single forwarding node at each hop when routing a data packet. We prove the correctness of
the constructed data collection tree and we show that under some stability conditions, the
constructed tree converges to an optimal shortestpath tree. Results of extensive simulations show
a big improvement in terms of packet delivery ratio, endto-end delay and energy consumption
compared to the well-known VBF protocol. The simulated cases show increases in the packet
delivery ratio between 20% and 122%, reductions in the average end-to-enddelay between 15%
and 55% and reductions in the energy consumption between 20% and 50%. These results clearly
demonstrate the attractiveness of the proposed DCTP protocol.
Keywords:
Underwater Wireless Sensor Networks, Data Collection, Routing Protocols, Performance
Evaluation
Orginal Source URL: https://aircconline.com/ijcnc/V12N5/12520cnc01.pdf
Volume Link: http://airccse.org/journal/ijc2020.html
References
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1447, 2014.
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and Research Challenges for Underwater Acoustic Sensor Networks. Int. J. Commun. Syst., Vol.
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[4] F. Al Salti, N. Alzeidi, and B. Arafeh, EMGGR: An Energy-Efficient Multipath Grid-Based
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Underwater Acoustic Wireless Sensor Network. Wireless Personal Commun. 2018, 98, 843–856.
[6] S. M. Ghoreyshi, A. Shahrabi, and T. Boutaleb, Void-Handling Techniques for Routing
Protocols in Underwater Sensor Networks: Survey and Challenges. IEEE Communications
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[7] Z. H. Jiang, Underwater Acoustic Networks-Issues and Solutions, International Journal of
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[8] M. Ahmed, Routing Protocols for Underwater Wireless Sensor Network Based on Location:
A Survey, Ad Hoc & Sensor Wireless Networks, 38:67-101, 2018.
[9] T. Islam, andY. K. Lee, A Comprehensive Survey of Recent Routing Protocols for
Underwater Acoustic Sensor Networks. Sensors, 19(19), 4256. doi:10.3390/s19194256.
[10] G. Han, J. Jiang, N. Bao, L. Wan, and M. Guizani, Routing Protocols for Underwater
Wireless Sensor Networks, IEEE Communications Magazine, pp. 72-78, November 2015.
[11] P. Xie, J.-H. Cui, and L. Lao, VBF: Vector-Based Forwarding Protocol for Underwater
Sensor Networks, in Proceedings of IFIP Networking'06, Coimbra, Portugal, 2006, pp. 1216–
1221.
[12] H. Yan, Z. J. Shi, and J.-H. Cui, Depth Based Routing for Underwater Sensor Networks, in
Proc. 7th International IFIP-TC6 Networking Conference on Ad-Hoc and Sensor Networks,
Wireless Networks, Next Generation Internet, Singapore, 2008, pp. 72-86.
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[14] Y.-S. Chen, T.-Y. Juang, Y.-W. Lin, and I.-C. Tsai, A Low Propagation Delay Multi-Path
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2010.

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Proceedings of MTS/IEEE Biloxi - Marine Technology for Our Future: Global and Local
Challenges (OCEANS 2009), 2009, pp. 1–7.
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[17] J.-H. Cui, J. Kong, M. Gerla, and S. Zhou, The challenges of building mobile underwater
wireless networks for aquatic applications, IEEE Networks, vol. 20, no. 3, pp. 12–18, May 2006.
[18] Z. S. Peng Xie, Zhong Zhou, Zheng Peng, Jun-hong Cui, Void Avoidance in Mobile
Underwater Sensor Networks, in WUWNet’07, 2007.
[19] X. Hong, M. Gerla, G. Pei, and C.-C. Chiang, A Group Mobility Model for Ad Hoc
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[20] Z. Zhou, Z. Peng, J.-H. Cui, Z. Shi, and A. Bagtzoglou, Scalable Localization with Mobility
Prediction for Underwater Sensor Networks, IEEE Trans. Mob. Comput., vol. 10, no. 3, pp. 335–
348, Mar. 2011.
[21] Faiza Al-Salti, Nasser Alzeidi , Khaled Day , Abderezak Touzene, An Efficient and Reliable
GridBased Routing Protocol for UWSNs by Exploiting Minimum Hop Count, Computer
Networks 162 (2019) 106869.

5. A SECURE DATA COMMUNICATION SYSTEM USING
CRYPTOGRAPHY AND STEGANOGRAPHY
Saleh Saraireh
Department of Communications and Electronic Engineering, Philadelphia University,
Amman,Jordan.
Abstract
The information security has become one of the most significant problems in data
communication. So it becomes an inseparable part of data communication. In order to address
this problem, cryptography and steganography can be combined. This paper proposes a secure
communication system. It employs cryptographic algorithm together with steganography. The
jointing of these techniques provides a robust and strong communication system that able to
withstand against attackers. In this paper, the filter bank cipher is used to encrypt the secret text
message, it provide high level of security, scalability and speed. After that, a discrete wavelet
transforms (DWT) based steganography is employed to hide the encrypted message in the cover
image by modifying the wavelet coefficients. The performance of the proposed system is
evaluated using peak signal to noise ratio (PSNR) and histogram analysis. The simulation results
show that, the proposed system provides high level of security.
Keywords:
Steganography, Cryptography, DWT, Filter bank, PSNR.
Orginal Source URL: http://airccse.org/journal/cnc/5313cnc10.pdf
Volime Link: http://airccse.org/journal/ijc2013.html
References
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and Decrypting Data" International Journal of Computer Networks & Communications (IJCNC)
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and Lifting over Finite Fields” In IEEE International Conference on Communications (ICC),
Dresden, Germany.
[17] El Safy, R.O, Zayed. H. H, El Dessouki. A, (2009), “An adaptive steganography technique
based on integer wavelet transform,” ICNM International Conference on Networking and Media
Convergence, pp 111-117.

8. JAMMING DETECTION BASED ON DOPPLER SHIFT ESTIMATION IN
VEHICULAR COMMUNICATIONS SYSTEMS
Javad Afshar Jahanshahi
Universidad Católica Los Ángeles de Chimbote, Instituto de Investigación, Chimbote, Perú
Abstract
Since Doppler shift is one of the most important parameters in wireless propagation, the
evaluation of the Doppler shift at the base station (BTS) in vehicular communications improves
BTS in many aspects such as channel varying rate, jamming detection, and handover operations.
Therefore, in this study, we propose a novel method at a base station based on the received user
signal to estimate the channel Doppler shift seen by BTS. Utilizing the inherent information
existed in common receivers, a level crossing rate (LCR) based Doppler shift estimation
algorithm is developed without any excessive hardware. Moreover, a jamming detection
algorithm is improved based on the proposed Doppler shift estimation scheme. The performance
of the proposed scheme is evaluated in a Terrestrial Trunked Radio (TETRA) network, and
comprehensive experimental results have shown superior performance in a wide range of
velocities, signal to noise ratios and jammers.
Keywords:
Jamming Detection, Vehicular Communications, Level Crossing Rate, Mobile Communication,
TETRA (Terrestrial Trunked Radio).
Orginal Source URL: https://aircconline.com/ijcnc/V12N5/12520cnc02.pdf
Volime Link: http://airccse.org/journal/ijc2020.html
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13. CORRELATION BASED FEATURE SELECTION (CFS) TECHNIQUE TO
PREDICT STUDENT PERFROMANCE
Mital Doshi 1
, Dr.Setu K Chaturvedi, Ph.D 2
1
Mtech. Research Scholar Technocrats Institute of Technology Bhopal, India
2
Professor & HOD (Dept. of CSE) Technocrats Institute of Technology Bhopal, India
Abstract
Education data mining is an emerging stream which helps in mining academic data for solving
various types of problems. One of the problems is the selection of a proper academic track. The
admission of a student in engineering college depends on many factors. In this paper we have
tried to implement a classification technique to assist students in predicting their success in
admission in an engineering stream.We have analyzed the data set containing information about
student’s academic as well as sociodemographic variables, with attributes such as family
pressure, interest, gender, XII marks and CET rank in entrance examinations and historical data
of previous batch of students. Feature selection is a process for removing irrelevant and
redundant features which will help improve the predictive accuracy of classifiers. In this paper
first we have used feature selection attribute algorithms Chi-square.InfoGain, and GainRatio to
predict the relevant features. Then we have applied fast correlation base filter on given features.
Later classification is done using NBTree, MultilayerPerceptron, NaiveBayes and Instance based
–K- nearest neighbor. Results showed reduction in computational cost and time and increase in
predictive accuracy for the student model
Keywords:
Chi-square, Correlation feature selection, IBK, Infogain, Gainratio, Multilayer perceptron,
NaiveBayes, NBTree
Orginal Source URL: http://airccse.org/journal/cnc/6314cnc15.pdf
Volime Link: http://airccse.org/journal/ijc2014.html
References
[1] Ladha L. and Deepa T., "Feature Selection Methods and Algorithms", International Journal
on Computer Science and Engineering (IJCSE), 2011.
[2] R. Kohavi. “Scaling Up the Accuracy of Naive-Bayes Classifiers: a Decision-Tree Hybrid”
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining,
1996

14. [3] Baker, R.S.J.D. (2010). Data Mining for Education. In B. McGaw, P. Peterson, E. Baker
(eds.), International Encyclopaedia of Education (3rd edition), (pp. 112-118). Oxford, UK:
Elsevier
[4] Pathom Pumpuang, Anongnart Srivihok , Prasong Praneetpolgrang, “Comparisons of
Classifier Algorithms: Bayesian Network, C4.5, Decision Forest and NBTree for Course
Registration Planning Model of Undergraduate Students”, 1-4244-2384-2/08/ 2008 IEEE
[5] Miren Tanna, “Decision Support System for Admission in Engineering Colleges based on
Entrance Exam Marks”, IJCA(0975 – 8887) Volume 52– No.11, August 2012
[6] Malaya Dutta Borah, Rajni Jindal, Daya Gupta Ganesh Chandra Deka, “Application of
knowledge based decision technique to predict student enrollment decision”, 978-1-4577-0792-
6/11 2011 IEEE
[7] Qasem A. Al-Radaideh, Ahmad Al Ananbeh, and Emad M. Al-Shawakfa, “A classification
model for predicting the suitable study track for school students”, Vol8
Issue2/IJRRAS_8_2_15.pdf, August 2011
[8] Hany M. Harb1, Malaka A. Moustafa, “Selecting optimal subset of features for student
performance model”, IJCSI Vol. 9, Issue 5, No 1, September 2012, 1694-0814
[9] Lei Yu leiyu,Huan Liu, “Feature Selection for High-Dimensional Data: A Fast Correlation-
Based Filter Solution”, (ICML-2003), Washington DC, 2003.
[10] B. K. Bharadwaj and S. Pal. "Mining Educational Data to Analyze Students' Performance",
International Journal of Advance Computer Science and Applications (IJACSA), Vol. 2, No. 6,
pp.63-69, 2011.
[11] S. T. Hijazi, and R. S. M. M. Naqvi, "Factors affecting student's performance: A Case of
Private Colleges", Bangladesh e-Journal of Sociology, Vol. 3, No. 1, 2006.
[12] Z. N. Khan, "Scholastic achievement of higher secondary students in science stream",
Journalof Social Sciences, Vol. 1, No. 2, pp. 84-87, 2005.
[13] Z. J. Kovacic, “Early prediction of student success: Mining student enrollment
data”,Proceedings of Informing Science & IT Education Conference 2010
[14] Blum & Langley, 1997; Kohavi &John, 1997
[15] Hall, M. (1999). Correlation based feature selection for machine learning. Doctoral
dissertation, Universityof Waikato, Dept. of Computer Science.
[16] WEKA,http://www.cs.waikato.ac.nz/ml/weka, Last access, 8 April 2008.

15. WEB OBJECT SIZE SATISFYING MEAN WAITING TIME IN
MULTIPLE ACCESS ENVIRONMENT
Y. –J. Lee
Department of Technology Education, Korea National University of Education, Cheongju, South
Korea
Abstract
This paper addresses web object size which is one of important performance measures and
affects to service time in multiple access environment. Since packets arrive according to Poission
distribution and web service time has arbitrary distribution, M/G/1 model can be used to describe
the behavior of the web server system. In the time division multiplexing (TDM), we can use
M/D/1 with vacations model, because service time is constant and server may have a vacation.
We derive the mean web object size satisfying the constraint such that mean waiting time by
round-robin scheduling in multiple access environment is equal to the mean queueing delay of
M/D/1 with vacations model in TDM and M/H2/1 model, respectively. Performance evaluation
shows that the mean web object size increases as the link utilization increases at the given
maximum segment size (MSS), but converges on the lower bound when the number of
embedded objects included in a web page is beyond the threshold. Our results can be applied to
the economic design and maintenance of web service.
Keywords:
M/D/1 with vacations, M/H2/1, mean waiting time, multiple web access
Orginal Source URL: http://airccse.org/journal/cnc/6414cnc01.pdf
Volime Link: http://airccse.org/journal/ijc2014.html
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17. ZIGBEE TECHNOLOGY AND ITS APPLICATION IN WIRELESS HOME
AUTOMATION SYSTEMS: A SURVEY
Thoraya Obaid, HaleemahRashed, Ali Abou-Elnour, Muhammad Rehan, Mussab Muhammad
Saleh, and Mohammed Tarique
Department of Electrical Engineering, Ajman University of Science and Technology P.O. Box 2202,
Fujairah, United Arab Emirates (UAE)
Abstract
Wireless home automation systems have drawn considerable attentions of the researchers for
more than a decade. The major technologies used to implement these systems include Z-Wave,
Insteon, Wavenis, Bluetooth, WiFi, and ZigBee. Among these technologies the ZigBee based
systems have become very popular because of its low cost and low power consumption. In this
paper ZigBee based wireless home automation systems have been addressed. There are two main
parts of this paper. In the first part a brief introduction of the ZigBee technology has been
presented and in the second part a survey work on the ZigBee based wireless home automation
system has been presented. The performances of the ZigBee based systems have also been
compared with those of other competing technologies based systems. In addition some future
opportunities and challenges of the ZigBee based systems have been listed in this paper.
Keywords:
Home automation, ZigBee, Z-Wave, Insteon, Waveins,PAN, voice control, energy management,
assistive homes, industrial automation
Orginal Source URL: http://airccse.org/journal/cnc/6414cnc11.pdf
Volime Link: http://airccse.org/journal/ijc2014.html
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23. A DEEP LEARNING TECHNIQUE FOR WEB PHISHING DETECTION
COMBINED URL FEATURES AND VISUAL SIMILARITY
Saad Al-Ahmadi1
and Yasser Alharbi 2
1
College of Computer and Information Science, Computer Science Department, King Saud
University, Riyadh, Saudi Arabia
2
College of Computer and Information Science, Computer Engineering Department, King Saud
University, Riyadh, Saudi Arabia
Abstract
The most popular way to deceive online users nowadays is phishing. Consequently, to increase
cybersecurity, more efficient web page phishing detection mechanisms are needed. In this paper,
we propose an approach that rely on websites image and URL to deals with the issue of phishing
website recognition as a classification challenge. Our model uses webpage URLs and images to
detect a phishing attack using convolution neural networks (CNNs) to extract the most important
features of website images and URLs and then classifies them into benign and phishing pages.
The accuracy rate of the results of the experiment was 99.67%, proving the effectiveness of the
proposed model in detecting a web phishing attack.
Keywords:
Phishing detection, URL, visual similarity, deep learning, convolution neural network.
Orginal Source URL: https://aircconline.com/ijcnc/V12N5/12520cnc03.pdf
Volime Link: http://airccse.org/journal/ijc2020.html
References
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phishing detection,” Comput. Secur., 2015, doi: 10.1016/j.cose.2015.07.006.
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Detect Phishing Websites,” Secur. Commun. Networks, 2018, doi: 10.1155/2018/7251750.
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Recurrent Convolutional Neural Networks,” Secur. Commun. Networks, 2019, doi:
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10.1109/SKIMA47702.2019.8982427.
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Applying Deep Learning Techniques on HTML Analysis,” no. October 2018, 2019, [Online].
Available: http://arxiv.org/abs/1909.01135.

27. A MAC PROTOCOL WITH DYNAMIC ALLOCATION OF TIME SLOTS
BASED ON TRAFFIC PRIORITY IN WIRELESS BODY AREA
NETWORKS
Sabin Bhandari and Sangman Moh
Department of Computer Engineering, Chosun University, Gwangju, South Korea
Abstract
In a wireless body area network (WBAN), wireless biomedical sensors are placed around, on, or
inside the human body. Given specific requirements, WBANs can significantly improve
healthcare, diagnostic monitoring, and other medical services. However, the existing standards
such as IEEE 802.11 and IEEE 802.15.4 have some limitations to meet all the requirements of
WBANs. Many medium access control (MAC) protocols have been studied so far, most of which
are derived from the IEEE 802.15.4 superframe structure with some improvements and
adjustments. However, the MAC protocols do not provide the required quality of service (QoS)
for various types of traffic in a WBAN. In this paper, a traffic-aware MAC (TA-MAC) protocol
for WBANs is proposed, in which time slots are dynamically allocated on the basis of traffic
priority, providing the required QoS. According to the performance evaluation results, the
proposed TA-MAC is better than IEEE 802.15.4 MAC and the conventional priority-based MAC
in terms of transmission time, system throughput, energy efficiency, and collision ratio.
Keywords:
Wireless body area network; Medium access control, Energy efficiency; Quality of service;
Traffic priority; IEEE 802.15.4
Orginal Source URL: https://aircconline.com/ijcnc/V11N4/11419cnc02.pdf
Volime Link: http://airccse.org/journal/ijc2019.html
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31. INTRUSION PREVENTION/INTRUSION DETECTION SYSTEM
(IPS/IDS) FOR WIFI NETWORKS
Michal Korčák1
and Jaroslav Lámer2
and František Jakab3
1,2,3
Department of Computer and Informatics, Technical University of Košice, TUKE Košice,
Slovakia
Abstract
The nature of wireless networks itself created new vulnerabilities that in the classical wired
networks do not exist. This results in an evolutional requirement to implement new sophisticated
security mechanism in form of Intrusion Detection and Prevention Systems. This paper deals
with security issues of small office and home office wireless networks. The goal of our work is
to design and evaluate wireless IDPS with use of packet injection method. Decrease of attacker’s
traffic by 95% was observed when compared to attacker’s traffic without deployment of
proposed IDPS system.
Keywords:
Deauthentification, Intrusion detection, Intrusion prevention, Packet injection, WiFi
Orginal Source URL: http://airccse.org/journal/cnc/6414cnc07.pdf
Volime Link: http://airccse.org/journal/ijc2014.html
References
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40.12: 66- 72.
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Proceedings of the second ACM conference on Wireless network security. ACM, p. 79-86.
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cracking demonstration”.
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Washington, D.C.: National Institute of Standards and Technology, National Computer Security
Center, pp. 362-371
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33. ENERGY CONSUMPTION IMPROVEMENT OF TRADITIONAL
CLUSTERING METHOD IN WIRELESS SENSOR NETWORK
Tran Cong Hung1
and Ly Quoc Hung2
1
Posts and Telecommunications Institute of Technology
2
Ho Chi Minh Technical and Economic College
Abstract
In the traditional clustering routing protocol of wireless sensor network, LEACH protocol (Low
Energy Adaptive Clustering Hierarchy) is considered to have many outstanding advantages in
the implementation of the hierarchy according to low energy adaptive cluster to collect and
distribute the data to the base station. The main objective of LEACH is: To prolong life time of
the network, reduce the energy consumption by each node, using the data concentration to reduce
bulletins in the network. However, in the case of large network, the distance from the nodes to
the base station is very different. Therefore, the energy consumption when becoming the host
node is very different but LEACH is not based on the remaining energy to choose the host node,
which is based on the number of times to become the host node in the previous rounds. This
makes the nodes far away from the base station lose power sooner. In this paper, we give a new
routing protocol based on the LEACH protocol in order to improve operating time of sensor
network by considering energy issues and distance in selecting the cluster-head (CH), at that
time the nodes with high energy and near the base station (BS) will have a greater probability of
becoming the cluster-head than the those in far and with lower energy.
Keywords:
LEACH, Life-time, Energy efficient, WSN, Matlab.
Orginal Source URL: https://aircconline.com/ijcnc/V8N5/8516cnc04.pdf
Volime Link: http://airccse.org/journal/ijc2016.html
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