Recent Research Articles in Internet of Things (IoT)

International Journal of Computer Networks & Communications (IJCNC)

(Scopus, ERA Listed)

ISSN 0974 – 9322 (Online); 0975 – 2293 (Print)

Availability Aspects through Optimization Techniques Based Outlier Detection Mechanism in Wireless and Mobile Networks

Neeraj Chugh, Adarsh Kumar and Alok Aggarwal

University of Petroleum & Energy Studies, Dehradun, India


Radio Frequency IDentification (RFID) and Wireless Sensor Networks (WSN) are the two most prominent wireless technologies for implementing a complete smart environment for the Internet of Things (IoT). Both RFID and WSN are resource constraint devices, which forces us to go for lightweight cryptography for security purposes. Security in terms of confidentiality, integrity, authentication, authorization, and availability. Key management is one of the major constraints for resource constraint mobile sensor devices. This work is an extension of the work done by Kumar et al. using efficient error prediction and limit of agreement for anomaly score. This work ensures cryptographic property, availability, in RFID-WSN integrated network through outlier detection mechanism for 50 to 5000 nodes network. Through detection ratios and anomaly scores system is tested against outliers. The proposed outlier detection mechanism identifies the inliers and outliers through anomaly score for protection against Denial-of-Service (DoS) attack. Intruders can be detected in few milliseconds without giving any conflict to the access rights. In terms of throughput, a minimum improvement of 6.2% and a maximum of 219.9% is observed for the proposed protocol as compared to Kumar et al. Protocol and in terms of percentage of Packet Delivery Ratio (PDR), a minimum improvement of 8.9% and a maximum of 19.5% is observed for the proposed protocol as compared to Kumar et al. protocol.



For More Details:

Volume Link:


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[53] N. Chugh, A. Kumar and A. Aggarwal, “Security aspects of a RFID-sensor integrated low-powered devices for internet-of-things”, 2016 Fourth International Conference on Parallel, Distributed and Grid Computing (PDGC), JUIT, Waknaghat, India, Dec. 2016, pp. 759-763.



Neeraj Chugh is an Assistant Professor in University of Petroleum & Energy Studies, Dehradun, India and enrolled in PhD (CSE) from Uttrakhand Technical University (UTU), Uttrakhand, India. He received his M. Tech. (CSE) from Kurukshetra University Kurukshetra, India in 2001. His research interests includes Database Management system, Data Mining, and Outlier/Anomaly detection and event detection in sensor networks.

author-2Adarsh Kumar received his ME degree in Software Engineering from Thapar University, Patiala, Punjab, India, in 2005 and earned his PhD degree from JIIT university, Noida, India in 2016 followed by Post Doctoral from AIT, Ireleand during 2016-2018. From 2005 to 2016, he has been associated with the Department of Computer Science Engineering & Information Technology, Jaypee Institute of Information Technology, Noida, UttarPardesh, India, where he worked as Assistant Professor. Currently he is working with University of Petroleum & Energy Studies,Dehradun, India as Associate Professor in CSE department. His main research interests are cryptography, network security, and adhoc networks.


Alok Aggarwal received his bachelors’ and masters’ degrees in Computer Science& Engineering in 1995 and 2001 respectively and his PhD degree in Engineering from IITRoorkee, Roorkee, India in 2010. He has academic experience of 18 years, industry experience of 4 years and research experience of 5 years. He has contributed more than 150 research contributions in different journals and conference proceedings. Currently he is working with University of Petroleum & Energy Studies, Dehradun, India as Professor in CSE department. His main research interests are wired/wireless networks, security, and coding theory.

Ensemble of Probabilistic Learning Networks For Iot Edge Intrusion Detection

Tony Jan and A.S.M Sajeev, Melbourne Institute of Technology, Australia


This paper proposes an intelligent and compact machine learning model for IoT intrusion detection using an ensemble of semi-parametric models with Ada boost. The proposed model provides an adequate real time intrusion detection at an affordable computational complexity suitable for the IoT edge networks. The proposed model is evaluated against other comparable models using the benchmark data on IoT-IDS and shows comparable performance with reduced computations as required.


Adaboosted ensemble learning, IoT edge security, machine learning for IoT

For More Details:

Volume Link:


[1] Muhammad Umar Farooq, Muhammad Waseem, Anjum Khairi, and Sadia Mazhar, (2015) “A critical analysis on the security concerns of internet of things (IoT)”, International Journal of Computer Applications, Vol. 111, No. 7.

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[3] Antonio Brogi and Stefano Forti, (2017) “QoS-aware deployment of IoT applications through the fog”, IEEE Internet of Things Journal, Vol. 4, No. 5, pp. 1185–1192.

[4]  Farhoud Hosseinpour, Payam Vahdani Amoli, Juha Plosila, Timo Ham ¨ al¨ ainen, and Hannu ¨ Tenhunen, (2016) “An Intrusion Detection System for Fog Computing and IoT based Logistic Systems using a Smart Data Approach”, International Journal of Digital Content Technology and its Applications, Vol. 10.

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A Future Mobile Packet Core Network Based on Ip-In-Ip Protocol

Mohammad Al Shinwan1 and Kim Chul-Soo2

1Amman Arab University, Amman, Jordan. 2Inje University, Gimhae, Republic of Korea.


The current Evolved Packet Core (EPC) 4th generation (4G) mobile network architecture features complicated control plane protocols and requires expensive equipment. Data delivery in the mobile packet core is performed based on a centralized mobility anchor between eNode B (eNB) elements and the network gateways. The mobility anchor is performed based on General Packet Radio Service tunnelling protocol (GTP), which has numerous drawbacks, including high tunnelling overhead and suboptimal routing between mobile devices on the same network. To address these challenges, here we describe new mobile core architecture for future mobile networks. The proposed scheme is based on IP encapsulated within IP (IP-in-IP) for mobility management and data delivery. In this scheme, the core network functions via layer 3 switching (L3S), and data delivery is implemented based on IP-in-IP routing, thus eliminating the GTP tunnelling protocol. For handover between eNB elements located near to one another, we propose the creation of a tunnel that maintains data delivery to mobile devices until the new eNB element updates the route with the gateway, which prevents data packet loss during handover. For this, we propose Generic Routing Encapsulation (GRE) tunnelling protocol. We describe the results of numerical analyses and simulation results showing that the proposed network core architecture provides superior performance compared with the current 4G architecture in terms of handover delay, tunnelling overhead and total transmission delay.


5G network, mobile core network, IP-in-IP, GRE

For More Details:

Volume Link:


[1]   Cisco, (2016) “Visual Networking Index: Global Mobile Data Traffic Forecast Update”, 2015 – 2020,White paper.

[2] Ericsson, Huawei and Qualcomm, (2015) “The Road to 5G: Drivers, Applications, Requirements and Technical Development”, Technical Report.

[3]   Shinwan, M.A. and Chul-Soo, K. (2017) “Enhanced Mobile Packet Core Network Scheme for Next-Generation Mobile Communication Systems”. International Journal of Electronics Communication and Computer Engineering (IJECCE), 8, 56-61.

[4]   3GPP TS 23.002, (2016) “Technical Specification Group Services and System Aspects; Network architecture”, Technical Report, Rel-13 Ver. 13.5.0.

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[18]   M. A. Shinwan, T.-D. Huy, and K. Chul-Soo, (2017) “A Flat Mobile Core Network for Evolved Packet Core Based SAE Mobile Networks,” Journal of Computer and Communications, vol. 05, no.05, pp. 62-73.

[19] B. Davaasambuu, F. Semaganga, and T. Sato, (2015) “Adaptive Handover Hysteresis and Call Admission Control for Mobile Relay Nodes,” International journal of Computer Networks & Communications, vol. 7, no. 6, pp. 87–98.



Mohammad Al Shinwan, received his B.S degree in Computer Science from Al al-Bayt university, Jordan, in 2009 and the master degree in 2013 from the institute of Mathematical and Computer Science, University of Sindh in Pakistan. He received a Ph.D. in Computer Networks from Inje University, Korea. He is currently an assistant professor in the Faculty of Computer Science and Informatics, Amman Arab University, Jordan. His current research interests include mobility management, network management and OAM (Operation, Administration and Maintenance) for future mobile network.


Chul-Soo Kim is a professor in the School of Computer Engineering of Inje University in Gimhae, Korea. He received Ph.D. from the Pusan National University (Pusan, Korea) and worked for ETRI (Electronics and Telecommunication research Institute) from 1985 – 2000 as senior researcher for developing TDX exchange. Aside from the involvement in various national and international projects, his primary research interests include network protocols, traffic management, OAM issue, and NGN charging. He is a member of ITU-T SG3, SG11, SG13 and a Rapporteur of ATM Lite from 1998 – 2002, and CEO in WIZNET from 2000 – 2001. He is currently the chairperson of BcN Reference Model in Korea, and a Rapporteur of ITU-T SG3 NGN Charging.

Multi-Constraints Adaptive Link Quality Index Based Mobile-Rpl Routing Protocol for Low Power Lossy Networks

Sneha K1 . and B G Prasad2

1BNM Institute of Technology, Bengaluru, Karnataka, India

 2BMS College of Engineering, Bengaluru, Karnataka, India


The importance of IPv6 Routing Protocol for Low power and Lossy Networks (LLNs), also called RPL, has motivated in the development of a robust and quality of service (QoS) oriented Multi-Constraints Adaptive Link Quality Index (MALQI) based routing protocol. Unlike classical RPL protocols, MALQI enables mobile-RPL while ensuring fault-resilient, reliable and QoS communication over LLNs. MALQI protocol exploits key novelties such as signal strength based mobile node positioning, average received signal strength indicator (ARSSI) and ETX based objective function for fault tolerant best forwarding path selection. The functional architecture of MALQI enables it to be used as the parallel to the link layer RPL that even in the case of link failure can assist efficient data delivery over LLNs. Once detecting link outage, MALQI can execute node discover and best forwarding path selection to assist QoS delivery. Contiki-Cooja based simulation reveals that MALQI based mobile-RPL outperforms other state-of-art routing protocols.


Mobile-RPL; Adaptive Link Quality; Low Power Lossy Network; Routing Protocol; MALQI.

For More Details:

Volume Link:


[1] Heinzelman W., Kulik, J., Balakrishnan, H.: Adaptive Protocols for Information Dissemination in Wireless Sensor Networks. In proc. of the 5th ACM/IEEE Mobicom Conference (MobiCom ’99), Seattle, WA, August, pp. 174-85 (1999)

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[3] Yao, Y., Gehrke, J.: The cougar approach to in-network query processing in sensor networks. In ACM SIGMOD Record, vol. 31, no. 3. (2002)

[4] Heinzelman, W., Chandrakasan A., Balakrishnan, H.: Energy-Efficient Communication Protocol for Wireless Microsensor Networks. In proc. of the 33rd Hawaii International Conference on System Sciences (HICSS ’00) (2000)

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A Security Analysis of IoT Encryption: Side Channel Cube Attack on SIMECK32/64

Alya Geogiana Buja1,2, Shekh Faisal Abdul-Latip1 and Rabiah Ahmad1

1Universiti Teknikal Malaysia Melaka, Malaysia and 2Universiti Teknologi MARA, Malaysia


Simeck, a lightweight block cipher has been proposed to be one of the encryption that can be employed in the Internet of Things (IoT) applications. Therefore, this paper presents the security of the Simeck32/64 block cipher against side-channel cube attack. We exhibit our attack against Simeck32/64 using the Hamming weight leakage assumption to extract linearly independent equations in key bits. We have been able to find 32 linearly independent equations in 32 key variables by only considering the second bit from the LSB of the Hamming weight leakage of the internal state on the fourth round of the cipher. This enables our attack to improve previous attacks on Simeck32/64 within side-channel attack model with better time and data complexity of 235 and 211.29 respectively.


Block Cipher, IoT, Lightweight Encryption, Security Analysis, Simeck

For More Details:

Volume Link:


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Alya Geogiana Buja is a Ph.D. student at the Faculty of Information Technology and Communication, Universiti Teknikal Malaysia Melaka, Malaysia. Her research interests include information and network security. She involves actively in giving seminar and talk about information and security.


Shekh Faisal Abdul-Latip is a Senior Lecturer at the Faculty of Information Technology and Communication, Universiti Teknikal Malaysia Melaka, Malaysia. He received PhD degree in 2012 from the University of Wollongong, Australia, in the field of Symmetric-key Cryptography. Currently he is an executive committee member of Malaysian Society for Cryptology Research (MSCR) – a non-profit organization that promotes new ideas and activities in cryptology related areas in Malaysia. His research focuses on Cryptology (i.e. designing and breaking secret codes) and Information Security.


Rabiah Ahmad is a Professor at the Faculty of Information Technology and Communication, Universiti Teknikal Malaysia Melaka, Malaysia. She received her PhD in Information Studies (health informatics) from the University of Sheffield, UK, and M.Sc. (information security) from the Royal Holloway University of London, UK. Her research interests include healthcare system security and information security architecture. She has delivered papers at various health informatics and information security conferences at national as well as international levels. She has also published papers in accredited national/international journals. Besides that, she also serves as a reviewer for various conferences and journals.


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