IoT networks require a variety of safety systems, because of evolving new technologies. They are subject to assaults and require a variety of security solutions. Because of the sensor nodes' limited energy, compute capabilities and storage resources, identifying appropriate cryptography is critical in wireless sensor networks (WSN).
So, we need a new energy-aware routing method with an excellent cryptography-based security framework that fulfills critical IoT needs such as dependability, energy efficiency, attacker detection and data aggregation.
Intelligent dynamic trust secure attacker detection routing (IDTSADR) is a novel energy-aware routing method suggested for WSN-IoT networks. IDTSADR fulfills critical IoT needs such as dependability, energy efficiency, attacker detection and data aggregation. IDTSADR is an energy-efficient routing technique that discovers routes that use the least amount of energy for end-to-end packet traversal and improves malicious node detection. Our suggested algorithms take connection dependability into account to discover more reliable routes, as well as a goal of finding more energy-efficient routes and extending network lifespan by finding routes with nodes with greater battery charge levels. We presented a cryptography-based security framework for implementing the advanced encryption approach in IoT.
Improving the algorithm's encryption and decryption elements, which currently exist and provide outstanding security. From the below results, we can conclude that the proposed method surpasses the existing methods, this difference obviously prolonged the lifetime of the network.
Citation: B. Kiruthika, Shyamala Bharathi P. Intelligent dynamic trust secure attacker detection routing for WSN-IoT networks[J]. Mathematical Biosciences and Engineering, 2023, 20(2): 4243-4257. doi: 10.3934/mbe.2023198
IoT networks require a variety of safety systems, because of evolving new technologies. They are subject to assaults and require a variety of security solutions. Because of the sensor nodes' limited energy, compute capabilities and storage resources, identifying appropriate cryptography is critical in wireless sensor networks (WSN).
So, we need a new energy-aware routing method with an excellent cryptography-based security framework that fulfills critical IoT needs such as dependability, energy efficiency, attacker detection and data aggregation.
Intelligent dynamic trust secure attacker detection routing (IDTSADR) is a novel energy-aware routing method suggested for WSN-IoT networks. IDTSADR fulfills critical IoT needs such as dependability, energy efficiency, attacker detection and data aggregation. IDTSADR is an energy-efficient routing technique that discovers routes that use the least amount of energy for end-to-end packet traversal and improves malicious node detection. Our suggested algorithms take connection dependability into account to discover more reliable routes, as well as a goal of finding more energy-efficient routes and extending network lifespan by finding routes with nodes with greater battery charge levels. We presented a cryptography-based security framework for implementing the advanced encryption approach in IoT.
Improving the algorithm's encryption and decryption elements, which currently exist and provide outstanding security. From the below results, we can conclude that the proposed method surpasses the existing methods, this difference obviously prolonged the lifetime of the network.
| [1] |
G. Kaur, P. Chanak, M. Bhattacharya, Energy-efficient intelligent routing scheme for IoT-enabled WSNs, IEEE Internet Things J., 8 (2021), 11440–11449. https://doi.org/10.1109/JIOT.2021.3051768 doi: 10.1109/JIOT.2021.3051768
|
| [2] | X. Zhang, H. M. Heys, C. Li, Energy efficiency of symmetric key cryptographic algorithms in wireless sensor networks, in 2010 25th Biennial Symposium on Communications, (2010), 168–172. https://doi.org/10.1109/BSC.2010.5472979 |
| [3] | G. H. Kumar, G. P. Ramesh, C. R. Murthy, Energy efficient multi-hop routing techniques for cluster head selection in wireless sensor networks, in Further Advances in Internet of Things in Biomedical and Cyber Physical Systems, 193 (2021), 3–9. https://doi.org/10.1007/978-3-030-57835-0_1 |
| [4] | M. Esmaeeli, S. A. H. Ghahroudi, Improving energy efficiency using a new game theory algorithm for wireless sensor networks, Int. J. Comput. Appl. Technol., 136 (2016), 1–4. |
| [5] | A. Shrestha, L. Xing, H. Liu, Modeling and evaluating the reliability of wireless sensor networks, in 2007 Annual Reliability and Maintainability Symposium, (2007) 186–191. https://doi.org/10.1109/RAMS.2007.328105 |
| [6] |
Y. Duan, W. Li, X. Fu, Y. Luo, L. Yang, A methodology for reliability of WSN based on software defined network in adaptive industrial environment, IEEE/CAA J. Autom. Sin., 5 (2018), 74–82. https://doi.org/10.1109/JAS.2017.7510751 doi: 10.1109/JAS.2017.7510751
|
| [7] | K. Hemanth, G. P. Ramesh, Energy efficiency and Data packet security for wireless sensor networks using African Buffalo Optimization, Int. J. Control Automation, 13 (2020), 944–954. |
| [8] |
L. Zhou, C. Ge, S. Hu, C. Su, Energy-efficient and privacy-preserving data aggregation algorithm for wireless sensor networks, IEEE Internet Things J., 7 (2020) 3948–3957. https://doi.org/10.1109/JIOT.2019.2959094 doi: 10.1109/JIOT.2019.2959094
|
| [9] | R. Misra, C. Mandal, Ant-aggregation: ant colony algorithm for optimal data aggregation in wireless sensor networks, in 2006 IFIP International Conference on Wireless and Optical Communications Networks, (2006), 1–5. https://doi.org/10.1109/WOCN.2006.1666600 |
| [10] | M. Ebrahim, C. W. Chong, Secure force: a low-complexity cryptographic algorithm for wireless sensor network (WSN), in 2013 IEEE International Conference on Control System, Computing and Engineering, (2013), 557–562. https://doi.org/10.1109/ICCSCE.2013.6720027 |
| [11] |
M. Rostami, K. Berahmand, E. Nasiri, S. Forouzandeh, Review of swarm intelligence-based feature selection methods, Eng. Appl. Artif. Intell., 100 (2021), 104210. https://doi.org/10.1016/j.engappai.2021.104210 doi: 10.1016/j.engappai.2021.104210
|
| [12] |
E. Nasiri, K. Berahmand, Y. Li, Robust graph regularization nonnegative matrix factorization for link prediction in attributed networks, Multimedia Tools Appl., (2022), 1–24. https://doi.org/10.1007/s11042-022-12943-8 doi: 10.1007/s11042-022-12943-8
|
| [13] |
J. von Mulert, I. Welch, W. K. G. Seah, Security threats and solutions in MANETs: A case study using AODV and SAODV, J. network comput. Appl., 35 (2012), 1249-1259. https://doi.org/10.1016/j.jnca.2012.01.019 doi: 10.1016/j.jnca.2012.01.019
|
Figures(7) / Tables(7)
B. Kiruthika, Shyamala Bharathi P. Intelligent dynamic trust secure attacker detection routing for WSN-IoT networks[J]. Mathematical Biosciences and Engineering, 2023, 20(2): 4243-4257. doi: 10.3934/mbe.2023198
DownLoad: