2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 17 , Issue 2 , PP: 23-35, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Bahaa Kareem Mohammed 1 * , Hayder Najm 2 , Mohammed Salih Mahdi 3 , Riyadh Rahef Nuiaa Alogaili 4 , Waleed Khaled 5
Doi: https://doi.org/10.54216/JISIoT.170203
Establishing basic network connectivity by mobile devices depends on wireless communication during infrastructure downtime. Nodes within these networks use routing protocols to send data packets between one another until the packets reach their endpoint. The protocols have security weaknesses that permit harmful nodes to stage assaults on the network. Network disruption occurs through the Black Hole Attack, which blocks all data packets from getting to their destinations by intercepting them during their transmission. Security systems that detect intruders executing these attacks protect against the security challenge. A simulated wireless ad-hoc network scenario is the basis for assessing how well response systems fight against the Black Hole attack. In this paper, the Anti-Black Hole Ad hoc On-Demand Distance Vector (ABAODV) is the proposed solution to combat the Black Hole attack effects. During the experiments, ABAODV's modified AODV version and standard AODV protocol underwent performance measurements through throughput, Packet Delivery Fraction (PDF), Average End-to-End Delay (AED), and Normalized Routing Load (NRL) while operating in Black Hole attack environments and without such attacks. Through its NS-2 implementation, ABAODV achieved 99% effectiveness in combating the Black Hole attack. The entire simulation was conducted on a Linux platform, including mobility generation, analysis, results presentation, and NS-2 simulation.
Data Security , Wireless Network Security , AODV , ABAODV , Black Hole Attack , MANET
[1] K. A. A. Omer, "The impact of node misbehavior on the performance of routing protocols in MANET," Int. J. Comput. Netw. Commun., vol. 8, no. 2, pp. 103–112, 2016.
[2] O. Ahmed, "Enhancing Intrusion Detection in Wireless Sensor Networks through Machine Learning Techniques and Context Awareness Integration," Int. J. Math. Stat. Comput. Sci., vol. 2, pp. 244–258, 2024. doi: 10.59543/ijmscs.v2i.10377.
[3] A. Mohebi, E. Kamal, and S. Scott, "Simulation and analysis of AODV and DSR routing protocol under black hole attack," Int. J. Modern Educ. Comput. Sci., vol. 5, no. 10, pp. 19–25, 2013.
[4] K. Roshan and V. Bibhu, "Preventive aspect of black hole attack in mobile AD HOC network," Int. J. Comput. Netw. Inf. Secur., vol. 4, no. 6, pp. 49–55, 2012.
[5] D. M. Khan et al., "Black hole attack prevention in mobile ad-hoc network (MANET) using ant colony optimization technique," Inf. Technol. Control, vol. 49, no. 3, pp. 308–319, 2020.
[6] Z. B. Ibrahim and M. F. Ghanim, "A review of AI-based approaches against wormhole and blackhole attacks in AODV protocol," 2024. [Online]. Available: [Publisher Info Needed].
[7] E. E. A. Sallum et al., "Performance analysis and comparison of the DSDV, AODV and OLSR routing protocols under VANETs," in Proc. 16th Int. Conf. Intell. Transp. Syst. Telecommun. (ITST), 2018, pp. 1–7.
[8] M. S. Mahdi, W. R. Abdulhussien, H. Najm, and A. S. M. Aloqali, "Image encryption using modified Serpent algorithm and Harris Hawks optimization," J. Wirel. Mob. Netw. Ubiquitous Comput. Dependable Appl., vol. 16, no. 1, pp. 154–171, Mar. 2025.
[9] S. Naveena, C. Senthilkumar, and T. Manikandan, "Analysis and countermeasures of black-hole attack in MANET by employing trust-based routing," in Proc. 6th Int. Conf. Adv. Comput. Commun. Syst. (ICACCS), 2020, pp. 1222–1227.
[10] Y. Nakano and T. Matsuzawa, "Preventing black hole attacks in AODV using RREQ packets," Netw., vol. 3, no. 4, pp. 469–481, 2023.
[11] T. M. Mahmoud, A. A. Aly, and O. Makram, "A modified AODV routing protocol to avoid black hole attack in MANETs," Int. J. Comput. Appl., vol. 109, no. 6, pp. 27–33, 2015.
[12] B. Reddy and B. Dhananjaya, "The AODV routing protocol with built-in security to counter blackhole attack in MANET," Mater. Today: Proc., vol. 50, pp. 1152–1158, 2022.
[13] G. Rathore, R. Dubey, and V. Richhariya, "Black Hole Attack in AODV routing protocol using security algorithm in MANET," Int. J. Comput. Appl., vol. 975, pp. 8887, 2016.
[14] K. Murty and M. V. D. S. Rajalakshmi, "Secure and light weight AODV (SLW-AODV) routing protocol for resilience against blackhole attack in MANETs," Int. J. Soft Comput. Eng., vol. 13, no. 1, pp. 2231–2307, 2023.
[15] M. A. A. Alsudani, "Self-organizing control for telecommunication networks 5G," in AIP Conf. Proc., vol. 2591, no. 1, 2023.
[16] H. Najm, M. S. Mahdi, and W. R. Abdulhussien, "Lightweight image encryption using Chacha20 and Serpent algorithm," J. Internet Serv. Inf. Secur. (JISIS), vol. 14, no. 4, pp. 436–449, 2024.
[17] H. Weerasinghe and H. Fu, "Preventing cooperative black hole attacks in mobile ad hoc networks: Simulation implementation and evaluation," in Future Gener. Commun. Netw. (FGCN), vol. 2, pp. 362–367, 2007.
[18] M. Khalaf et al., "Schema matching using word-level clustering for integrating universities’ courses," in Proc. 2nd Al-Noor Int. Conf. Sci. Technol. (NICST), 2020, pp. 1–6.
[19] H. Najm, M. S. Mahdi, and S. Mohsin, "Novel key generator-based SqueezeNet model and hyperchaotic map," Data Metadata, vol. 4, p. 743, Mar. 2025.
[20] A. H. Al-Fatlawi et al., "Design of a compact microstrip band pass filter for IoT and S-band radar applications," Data Metadata, vol. 4, p. 714, Feb. 2025. [Online]. Available: https://doi.org/10.56294/dm2025714.
[21] C. Perkins, E. Belding-Royer, and S. Das, "Ad hoc on-demand distance vector (AODV) routing," IETF RFC 3561, 2003.
[22] H. M. Al-Dabbas and M. Salih, "Classification of brain tumor diseases using data augmentation and transfer learning," Iraqi J. Sci., pp. 2275–2286, 2024.
[23] E. H. Hassan et al., "Using K-mean clustering to classify the kidney images," Iraqi J. Sci., pp. 2070–2084, 2023.
[24] E. H. Hassan et al., "Mask laws to study texture features of the kidney infection," Iraqi J. Sci., pp. 2261–2270, 2023.
[25] Y. M. Abid et al., "Development of an intelligent controller for sports training system based on FPGA," J. Intell. Syst., vol. 32, no. 1, p. 20220260, 2023.
[26] I. Alameri, J. Komarkova, T. Al-Hadhrami, and A. Lotfi, "Systematic review on modification to the ad-hoc on-demand distance vector routing discovery mechanics," PeerJ Comput. Sci., vol. 8, p. e1079, 2022.
[27] A. M. Alwan, M. S. Mohammed, and R. M. Shehab, "Modified laser-etched silicon covered with bimetallic Ag–Au alloy nanoparticles for high-performance SERS: Laser wavelength dependence," Indian J. Phys., vol. 95, pp. 1843–1851, 2021.
[28] R. M. Shehab and A. M. Alwan, "Improved the sensitivity and limit of detection of surface alloying SERS sensors by controlling mixing ratio of trimetallic (Ag-Au-Pd) nanoparticles," Int. J. Nanoelectron. Mater., vol. 16, no. 2, pp. 359–370, 2023.
[29] R. A. Azeez, A. S. Jamil, and M. S. Mahdi, "A partial face encryption in real world experiences based on features extraction from edge detection," Int. J. Interact. Mob. Technol., vol. 17, no. 7, pp. 69–81, 2023.
[30] B. I. Bakri et al., "Using deep learning to design an intelligent controller for street lighting and power consumption," East.-Eur. J. Enterp. Technol., vol. 117, no. 8, 2022.
[31] H. Najm, H. Hoomod, and R. Hassan, "A new WoT cryptography algorithm based on GOST and novel 5D chaotic system," 2021, pp. 184–199.
[32] Z. A. Ramadhan, B. K. Mohammed, and A. H. Alwaily, "Design and implement a smart traffic light controlled by internet of things," Period. Eng. Nat. Sci. (PEN), vol. 9, no. 4, pp. 542–548, 2021.
[33] A. M. Ali, M. A. Ngadi, I. I. Al_Barazanchi, and P. S. J. Ng, "Intelligent traffic model for unmanned ground vehicles based on DSDV-AODV protocol," Sensors, vol. 23, no. 14, p. 6426, 2023.
[34] J. Smith and L. Johnson, "Advancements in Cybersecurity Protocols for IoT Devices," Int. J. Cybersecurity, vol. 9, no. 2, pp. 45–60, 2021.
[35] R. Lee and T. Kim, "Machine Learning Applications in Financial Technology: A Review," Fin. Technol. Innov., vol. 3, no. 1, pp. 22–37, 2023.
[36] M. Zhao et al., "Data Analysis Techniques for Smart City Development," Smart Cities, vol. 5, no. 3, pp. 112–125, 2024.
