International Journal of Computer Networks and Applications

Open Access Open Access  Restricted Access Subscription Access

Hybrid Optimization-Based Secure Routing Protocol for Cloud Computing


Affiliations
1 Department of Computer Science, PRIST Deemed University, Thanjaur, Tamil Nadu, India
 

Cloud Computing (CC) combines the computer paradigm and a shared environment allowing multiple users to access services and resources. In addition to being accessible internationally via the Internet, this ecosystem may be shared at all levels. Resources, infrastructure, and platforms at all levels may be traded with a wide range of customers. Through the Internet, CC enables remote server access. To create cloud environments, CCuses a wide range of already existing technologies, including internet servers, web browsers, and virtualization. These system vulnerabilities can have a significant impact on the cloud as well. The majority of data breaches occur on the way to their final destination. Because of this, the route that data takes must be protected. In this paper, Hybrid Optimization-based Secure Routing Protocol (HOSRP) is proposed to find the best route to destination and provide security to data that passes on it. HOSRP initially clusters the network into different numbers via modified particle swarm optimization strategy and selects the cluster head. HOSRP detects the shorted routes among clusters via firefly optimization strategy to minimize the delay and maximize the delivery ratio of packets. HOSRP applies security to data transmission using the message digest and cryptographic strategy. The performance of HOSRP is analyzed using greencloud simulator with standard performance metrics. Results indicate that HOSRP has better performance in minimizing the delay to save energy consumption and protecting security to the data.

Keywords

Hybrid, Optimization, Routing, Cloud, Security, Swarm.
User
Notifications
Font Size

  • R. Yarinezhad et al., “An energy efficient cluster head selection approach for performance improvement in network-coding-based wireless sensor networks with multiple sinks,” Ad Hoc Networks, vol. 64, pp. 514–526, Apr. 2021, doi: https://doi.org/10.1016/j.future.2018.12.024.

  • H. Han, S. Shakkottai, C. V Hollot, R. Srikant, and D. Towsley, “Multi-Path TCP: A Joint Congestion Control and Routing Scheme to Exploit Path Diversity in the Internet,” IEEE/ACM Trans. Netw., vol. 14, no. 6, pp. 1260–1271, 2006, doi: 10.1109/TNET.2006.886738.

  • O. Samuel, N. Javaid, T. A. Alghamdi, and N. Kumar, “Towards sustainable smart cities: A secure and scalable trading system for residential homes using blockchain and artificial intelligence,” Sustain. Cities Soc., vol. 76, p. 103371, 2022, doi: https://doi.org/10.1016/j.scs.2021.103371.

  • M. Ganesan and N. Sivakumar, “IoT based heart disease prediction and diagnosis model for healthcare using machine learning models,” in 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN), 2019, pp. 1–5, doi: 10.1109/ICSCAN.2019.8878850.

  • S. Luo, G. Zhang, C. Wu, S. U. Khan, and K. Li, “Boafft: Distributed Deduplication for Big Data Storage in the Cloud,” IEEE Trans. Cloud Comput., vol. 8, no. 4, pp. 1199–1211, 2020, doi: 10.1109/TCC.2015.2511752.

  • I. Bolodurina and D. Parfenov, “Comprehensive approach for optimization traffic routing and using network resources in a virtual data center,” Procedia Comput. Sci., vol. 136, pp. 62–71, 2018, doi: https://doi.org/10.1016/j.procs.2018.08.238.

  • B. Farahani, F. Firouzi, V. Chang, M. Badaroglu, N. Constant, and K. Mankodiya, “Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare,” Futur. Gener. Comput. Syst., vol. 78, pp. 659–676, 2018, doi: https://doi.org/10.1016/j.future.2017.04.036.

  • A. S. Alqahtani, “Security threats and countermeasures in software defined network using efficient and secure trusted routing mechanism,” Comput. Commun., vol. 153, pp. 336–341, 2020, doi: https://doi.org/10.1016/j.comcom.2020.02.020.

  • J. Ben Othman and L. Mokdad, “Enhancing data security in ad hoc networks based on multipath routing,” J. Parallel Distrib. Comput., vol. 70, no. 3, pp. 309–316, 2010, doi: https://doi.org/10.1016/j.jpdc.2009.02.010.

  • V. Mythili, A. Suresh, M. M. Devasagayam, and R. Dhanasekaran, “SEAT-DSR: Spatial and energy aware trusted dynamic distance source routing algorithm for secure data communications in wireless sensor networks,” Cogn. Syst. Res., vol. 58, pp. 143–155, 2019, doi: https://doi.org/10.1016/j.cogsys.2019.02.005.

  • G. C. Hadjichristofi, L. A. DaSilva, S. F. Midkiff, U. Lee, and W. De Sousa, “Routing, security, resource management, and monitoring in ad hoc networks: Implementation and integration,” Comput. Networks, vol. 55, no. 1, pp. 282–299, 2011, doi: https://doi.org/10.1016/j.comnet.2010.09.001.

  • R. Prasad P and Shivashankar, “ENHANCED ENERGY EFFICIENT SECURE ROUTING PROTOCOL FOR MOBILE AD-HOC NETWORK,” Glob. Transitions Proc., 2021, doi: https://doi.org/10.1016/j.gltp.2021.10.001.

  • K. Haseeb, I. Ud Din, A. Almogren, I. Ahmed, and M. Guizani, “Intelligent and secure edge-enabled computing model for sustainable cities using green internet of things,” Sustain. Cities Soc., vol. 68, p. 102779, 2021, doi: https://doi.org/10.1016/j.scs.2021.102779.

  • G. Thahniyath and M. Jayaprasad, “Secure and load balanced routing model for wireless sensor networks,” J. King Saud Univ. - Comput. Inf. Sci., 2020, doi: https://doi.org/10.1016/j.jksuci.2020.10.012.

  • A. Seyfollahi, M. Moodi, and A. Ghaffari, “MFO-RPL: A secure RPL-based routing protocol utilizing moth-flame optimizer for the IoT applications,” Comput. Stand. Interfaces, vol. 82, p. 103622, 2022, doi: https://doi.org/10.1016/j.csi.2022.103622.

  • C. C. Sobin, C. Labeeba, and K. Deepika Chandran, “An Efficient method for Secure Routing in Delay Tolerant Networks,” Procedia Comput. Sci., vol. 143, pp. 820–826, 2018, doi: https://doi.org/10.1016/j.procs.2018.10.384.

  • A. Vinitha, M. S. S. Rukmini, and Dhirajsunehra, “Secure and energy aware multi-hop routing protocol in WSN using Taylor-based hybrid optimization algorithm,” J. King Saud Univ. - Comput. Inf. Sci., 2019, doi: https://doi.org/10.1016/j.jksuci.2019.11.009.

  • A. Yazdinejad, R. M. Parizi, A. Dehghantanha, G. Srivastava, S. Mohan, and A. M. Rababah, “Cost optimization of secure routing with untrusted devices in software defined networking,” J. Parallel Distrib. Comput., vol. 143, pp. 36–46, 2020, doi: https://doi.org/10.1016/j.jpdc.2020.03.021.

  • R. Prasad and S. shankar, “Secure Intrusion Detection System Routing Protocol for Mobile Ad-Hoc Network,” Glob. Transitions Proc., 2021, doi: https://doi.org/10.1016/j.gltp.2021.10.003.

  • D. Kothandaraman, S. Naik Korra, A. Balasundaram, and S. Magesh Kumar, “Sequence number based secure routing algorithm for IoT networks,” Mater. Today Proc., 2021, doi: https://doi.org/10.1016/j.matpr.2020.11.703.

  • H. Helly, E. Efrat, and J. Yosef, “Spatial routinization and a ‘secure base’ in displacement processes: Understanding place attachment through the security-exploratory cycle and urban ontological security frameworks,” J. Environ. Psychol., vol. 75, p. 101612, 2021, doi: https://doi.org/10.1016/j.jenvp.2021.101612.

  • Z. Liu, L. Wang, X. Wang, X. Shen, and L. Li, “Secure Remote Sensing Image Registration Based on Compressed Sensing in Cloud Setting,” IEEE Access, vol. 7, pp. 36516–36526, 2019, doi: 10.1109/ACCESS.2019.2903826.

  • R. Kumar and R. Goyal, “Modeling continuous security: A conceptual model for automated DevSecOps using open-source software over cloud (ADOC),” Comput. Secur., vol. 97, p. 101967, 2020, doi: https://doi.org/10.1016/j.cose.2020.101967.

  • F. Thabit, P. S. Alhomdy, and P. S. Jagtap, “Security Analysis and Performance Evaluation of a New Lightweight Cryptographic Algorithm for Cloud Computing Environment,” Glob. Transitions Proc., 2021, doi: https://doi.org/10.1016/j.gltp.2021.01.014.

  • J. Ramkumar and R. Vadivel, “Meticulous elephant herding optimization based protocol for detecting intrusions in cognitive radio ad hoc networks,” Int. J. Emerg. Trends Eng. Res., vol. 8, no. 8, pp. 4549–4554, 2020, doi: 10.30534/ijeter/2020/82882020. How to cite this article:

  • J. Ramkumar and R. Vadivel, “Bee inspired secured protocol for routing in cognitive radio ad hoc networks,” INDIAN J. Sci. Technol., vol. 13, no. 30, pp. 3059–3069, 2020, doi: 10.17485/IJST/v13i30.1152.

  • R. Vadivel and J. Ramkumar, “QoS-Enabled Improved Cuckoo Search-Inspired Protocol (ICSIP) for IoT-Based Healthcare Applications,” pp. 109–121, 2019, doi: 10.4018/978-1-7998-1090-2.ch006.

  • J. Ramkumar and R. Vadivel, “Intelligent Fish Swarm Inspired Protocol (IFSIP) For Dynamic Ideal Routing in Cognitive Radio Ad-Hoc Networks,” Int. J. Comput. Digit. Syst., vol. 10, no. 1, pp. 1063–1074, 2020, doi: http://dx.doi.org/10.12785/ijcds/100196.

  • J. Ramkumar, R. Vadivel, and B. Narasimhan, “Constrained Cuckoo Search Optimization Based Protocol for Routing in Cloud Network,” Int. J. Comput. Networks Appl., doi: 10.22247/ijcna/2021/210727.

  • J. Ramkumar and R. Vadivel, “Performance Modeling of Bio-Inspired Routing Protocols in Cognitive Radio Ad Hoc Network to Reduce End-to-End Delay,” Int. J. Intell. Eng. Syst., vol. 12, no. 1, pp. 221–231, 2019, doi: 10.22266/ijies2019.0228.22.

  • J. Ramkumar and R. Vadivel, “Whale Optimization Routing Protocol for Minimizing Energy Consumption in Cognitive Radio Wireless Sensor Network,” Int. J. Comput. Networks Appl., vol. 8, no. 4, doi: 10.22247/ijcna/2021/209711.

  • J. Ramkumar and R. Vadivel, “Multi-Adaptive Routing Protocol for Internet of Things based Ad-hoc Networks,” Wirel. Pers. Commun., pp. 1–23, Apr. 2021, doi: 10.1007/s11277-021-08495-z.

  • S. Namasudra, D. Devi, S. Kadry, R. Sundarasekar, and A. Shanthini, “Towards DNA based data security in the cloud computing environment,” Comput. Commun., vol. 151, pp. 539–547, 2020, doi: https://doi.org/10.1016/j.comcom.2019.12.041.

  • S. R. Jena, R. Shanmugam, K. Saini, and S. Kumar, “Cloud Computing Tools: Inside Views and Analysis,” Procedia Comput. Sci., vol. 173, pp. 382–391, 2020, doi: https://doi.org/10.1016/j.procs.2020.06.045.


Abstract Views: 238

PDF Views: 2




  • Hybrid Optimization-Based Secure Routing Protocol for Cloud Computing

Abstract Views: 238  |  PDF Views: 2

Authors

B. Vatchala
Department of Computer Science, PRIST Deemed University, Thanjaur, Tamil Nadu, India
G. Preethi
Department of Computer Science, PRIST Deemed University, Thanjaur, Tamil Nadu, India

Abstract


Cloud Computing (CC) combines the computer paradigm and a shared environment allowing multiple users to access services and resources. In addition to being accessible internationally via the Internet, this ecosystem may be shared at all levels. Resources, infrastructure, and platforms at all levels may be traded with a wide range of customers. Through the Internet, CC enables remote server access. To create cloud environments, CCuses a wide range of already existing technologies, including internet servers, web browsers, and virtualization. These system vulnerabilities can have a significant impact on the cloud as well. The majority of data breaches occur on the way to their final destination. Because of this, the route that data takes must be protected. In this paper, Hybrid Optimization-based Secure Routing Protocol (HOSRP) is proposed to find the best route to destination and provide security to data that passes on it. HOSRP initially clusters the network into different numbers via modified particle swarm optimization strategy and selects the cluster head. HOSRP detects the shorted routes among clusters via firefly optimization strategy to minimize the delay and maximize the delivery ratio of packets. HOSRP applies security to data transmission using the message digest and cryptographic strategy. The performance of HOSRP is analyzed using greencloud simulator with standard performance metrics. Results indicate that HOSRP has better performance in minimizing the delay to save energy consumption and protecting security to the data.

Keywords


Hybrid, Optimization, Routing, Cloud, Security, Swarm.

References





DOI: https://doi.org/10.22247/ijcna%2F2022%2F212338