Design and Implementation of Intrusion Detection Systems using RPL and AOVD Protocols-based Wireless Sensor Networks



Wireless Sensor Network (WSN) technology has grown in importance in recent years. All WSN implementations need secure data transmission between sensor nodes and base stations. Sensor node attacks introduce new threats to the WSN. As a result, an appropriate Intrusion Detection System (IDS) is required in WSN for defending against security attacks and detecting attacks on sensor nodes. In this study, we use the Routing Protocol for Low Power and Lossy Networks (RPL) for addressing security services in WSN by identifying IDS with a network size of more or less 20 nodes and introducing 10% malicious nodes. The method described above is used on Cooja in the VMware virtual machine Workstation with the InstantContiki2.7 operating system. To track the movement of nodes, find network attacks, and spot dropped packets during IDS in WSN, an algorithm is implemented in the Network Simulator (NS2) using the Ad-hoc On-Demand Distance Vector (AODV) protocol in the Linux operating system.

Keywords—Intrusion Detection Systems, wireless sensor networks, Cooja simulator, sensor nodes, NS2

Author Biographies

Joseph Kipongo, University of Johannesburg

Department of Electrical and Electronic Engineering Science, PhD candidate

Theo G. Swart, University of Johannesburg

Department of Electrical and Electronic Engineering Science, Associate Professor

Ebenezer Esenogho, University of Johannesburg and University of Botswana

Department of Electrical and Electronic Engineering Science, Associate Professor


I. Butun, S. D. Morgera, and R. Sankar, “A Survey of Intrusion Detection Systems in Wireless Sensor Networks,” IEEE Commun. Surv. TUTORIALS, vol. 16, no. 1, pp. 266–282, 2014, doi: 10.1109/SURV.2013.050113.00191.

J. Kipongo, E. Esenogho, and T. G. Swart, “Efficient topology discovery protocol using IT-SDN for software-defined wireless sensor network,” Bull. Electr. Eng. Informatics, vol. 11, no. 1, pp. 256–269, 2022, doi: 10.11591/eei.v11i1.3240.

K. Nikolina, “Overview of the progress of IPv6 adoption in Croatia,” 2022 45th Jubil. Int. Conv. Information, Commun. Electron. Technol., pp. 405–408, 2022, doi: 10.23919/MIPRO55190.2022.9803479.

N. Chuangchunsong, “Performance Evaluation of IPv4 / IPv6 Transition Mechanisms : IPv4-in-IPv6 Tunneling Techniques,” Int. Conf. Inf. Netw. 2014, pp. 238–243, 2014, doi: 10.1109/ICOIN.2014.6799698.

A. Al-Nasser, R. Almesaeed, and H. Al-Junaid, “A comprehensive survey on routing and security in mobile wireless sensor networks,” Int. J. Electron. Telecommun., vol. 67, no. 3, pp. 483–496, 2021, doi: 10.24425/ijet.2021.137838.

O. A. Osanaiye and A. S. Alfa, “Denial of Service Defence for Resource Availability in Wireless Sensor Networks,” IEEE Access, vol. 6, pp. 6975–7004, 2018, doi: 10.1109/ACCESS.2018.2793841.

G. Divyashree, A. Durgabhavani, A. Gudoor, and M. B. Shetty, “Intrusion Detection System In Wireless Sensor Network,” Int. J. Recent Technol. Eng., vol. 8, no. 1, pp. 2047–2051, 2019.

E. Baraneetharan, “Role of Machine Learning Algorithms Intrusion Detection in WSNs : A Survey,” J. Inf. Technol. Digit. World, vol. 02, no. 03, pp. 161–173, 2020.

S. Godala and R. P. Vaddella, “A Study on Intrusion Detection System in Wireless Sensor Networks,” Int. J. Commun. Networks Inf. Secur., pp. 127–141, 2020, doi: 10.17762/ijcnis.v12i1.4429.

N. Islam, F. Farhin, I. Sultana, and M. S. Kaiser, “Towards Machine Learning Based Intrusion Detection in IoT Networks,” Tech Sci. Press, pp. 1801–1821, 2021, doi: 10.32604/cmc.2021.018466.

V. Gowdhaman and R. Dhanapal, “An intrusion detection system for wireless sensor networks using deep neural network,” Soft Comput., pp. 1–9, 2021, doi: 10.1007/s00500-021-06473-y.

S. Rizwana, K. M. Gayathri, and N. Thangadurai, “Intrusion Detection Algorithm for Packet Loss Minimization in Wireless Sensor Networks,” Int. J. Eng. Adv. Technol., vol. 8958, no. 6, pp. 69–74, 2019, doi: 10.35940/ijeat.E7453.088619.

I. Gupta and K. Gupta, “Evaluation of Intrusion Detection Schemes in Wireless Sensor Network,” Int. Organ. Sci. Res. J. Comput. Eng., vol. 18, no. 2, pp. 60–63, 2016, doi: 10.9790/0661-1802056063.

S. Smys and H. Wang, “Hybrid Intrusion Detection System for Internet of Things ( IoT ),” J. IoT Soc. Mobile, Anal. Cloud, vol. 02, no. 04, pp. 190–199, 2020.

M. Latah and L. Toker, “An Efficient Flow-based Multi-level Hybrid Intrusion Detection System for Software-Defined Networks,” CCF Trans. Netw. (2020, pp. 261–271, 2020, doi:

T. Xiaopeng, S. Shaojing, H. Zhiping, G. Xiaojun, and Z. Zhen, “Wireless Sensor Networks Intrusion Detection Based on SMOTE and the Random Forest Algorithm,” MDPI Sensors, 2019, doi: 10.3390/s19010203.

J. Govindasamy and S. Punniakodi, “Energy efficient intrusion detection system for ZigBee based wireless sensor networks,” Int. J. Intell. Eng. Syst., vol. 10, no. 3, pp. 155–165, 2017, doi: 10.22266/ijies2017.0630.17.

Z. Tun and A. H. Maw, “Wormhole Attack Detection in Wireless Sensor Networks,” World Acad. Sci. Eng. Technol. 46 2008, pp. 545–550, 2008.

M. A. Patel and M. M. Patel, “Wormhole Attack Detection in Wireless Sensor Network,” Proc. Int. Conf. Inven. Res. Comput. Appl. ICIRCA 2018, no. Icirca, pp. 269–274, 2018, doi: 10.1109/ICIRCA.2018.8597366.

R. Singh, J. Singh, and R. Singh, “Fuzzy Based Advanced Hybrid Intrusion Detection System to Detect Malicious Nodes in Wireless Sensor Networks,” Hindawi Wirel. Commun. Mob. Comput., pp. 1–14, 2017, doi:

M. C. Belavagi and B. Muniyal, “Multiple intrusion detection in RPL based networks,” Int. J. Electr. Comput. Eng., vol. 10, no. 1, pp. 467–476, 2020, doi: 10.11591/ijece.v10i1.pp467-476.

A. A. Titorenko and A. A. Frolov, “Analysis of modern intrusion detection system,” 2018 IEEE Conf. Russ. Young Res. Electr. Electron. Eng., pp. 142–143, 2018, doi: 10.1109/EIConRus.2018.8317049.

V. B. Joshi and R. H. Goudar, “Intrusion detection and defense mechanism for packet replication attack over MANET using swarm intelligence,” 2013 Int. Conf. Pattern Recognition, Informatics Mob. Eng., pp. 152–156, 2013, doi: 10.1109/ICPRIME.2013.6496464.

S. P. Botkar and S. R. Chaudhary, “An Enhanced Intrusion detection System using Adaptive Acknowledgment based Algorithm,” 2018 IEEE Conf. Russ. Young Res. Electr. Electron. Eng., pp. 606–611, 2018.

J. V. A. Sukumar, I. Pranav, M. M. Neetish, and J. Narayanan, “Network Intrusion Detection Using Improved Genetic k-means Algorithm,” 2018 Int. Conf. Adv. Comput. Commun. Informatics, pp. 2441–2446, 2018, doi: 10.1109/ICACCI.2018.8554710.

W. Jian, F. Zhi-feng, and C. Yong, “Design and Implementation of Lightweight Wireless Lan Intrusion Detection System,” IEEE Trans. Comput., 2012, doi: 10.1109/MINES.2012.96.

A. Cherepanov, I. Tyshchenko, M. Popova, and D. Vakhnin, “Building Energy Efficient Wireless Sensor Networks,” Int. J. Electron. Telecommun., vol. 63, no. 1, pp. 45–49, 2017, doi: 10.1515/eletel-2017-0007.

L. Chhaya, P. Sharma, G. Bhagwatikar, and A. Kumar, “Wireless Sensor Network Based Smart Grid Communications : Cyber Attacks, Intrusion Detection System and Topology Control,” MDPI Electron., pp. 1–22, 2017, doi: 10.3390/electronics6010005.

R. Punithavathi, R. T. Selvi, R. Latha, G. Kadiravan, and V. Srikanth, “Robust Node Localization with Intrusion Detection for Wireless Sensor Networks,” Intell. Autom. Soft Comput., pp. 143–156, 2022, doi: 10.32604/iasc.2022.023344.

A. Kathirvel and M. Subramaniam, “Improved Intrusion Detection and Response System for Wireless Sensor Network,” Int. J. Forensic Sci., pp. 1–22, 2020, doi: 10.23880/ijfsc-16000203.

M. R. Rahman, M. M. Islam, E. A. Shahaz, and Y. Alsaawy, “Application Specific Energy Aware and Reliable Routing Protocol for Wireless Sensor Network,” 2019 7th Int. Conf. Smart Comput. Commun. ICSCC 2019, pp. 1–5, 2019, doi: 10.1109/ICSCC.2019.8843687.

Intrusion Detection Systems in Wireless Sensor Networks






Sensors, Microsystems, MEMS, MOEMS