SOSO: Symbiotic Organisms Search Optimization based Faster RCNN for Secure Data Storage in Cloud

References

• S. N. Swamy, and S. R. Kota, “An empirical study on system level aspects of internet of things (IoT),” IEEE. Access, Vol. 8, pp. 188082–188134, 2020. doi:10.1109/ACCESS.2020.3029847
   Web of Science ®Google Scholar
• X. Li, Q. Wang, X. Lan, X. Chen, N. Zhang, and D. Chen, “Enhancing cloud-based IoT security through trustworthy cloud service: An integration of security and reputation approach,” IEEE. Access, Vol. 7, pp. 9368–9383, 2019. doi:10.1109/ACCESS.2018.2890432
   Web of Science ®Google Scholar
• S. Meng, Z. Gao, Q. Li, H. Wang, H. N. Dai, and L. Qi, “Security-driven hybrid collaborative recommendation method for cloud-based IoT services,” Comput. Secur., Vol. 97, pp. 101950, 2020. doi:10.1016/j.cose.2020.101950
   Web of Science ®Google Scholar
• S. A. Chaudhry, A. Irshad, K. Yahya, N. Kumar, M. Alazab, and Y. B. Zikria, “Rotating behind privacy: an improved lightweight authentication scheme for cloud-based IoT environment,” ACM Trans. Internet Technol., Vol. 21, no. 3, pp. 1–19, 2021. doi:10.1145/3425707
   Web of Science ®Google Scholar
• A. J. Khan, and S. Mehfuz, “Big-data driven approaches in materials science on cloud storage API through optimal homomorphic encryption,” Mater. Today: Proc. 2021.
   Google Scholar
• S Jothi, and A. Chandrasekar, “An efficient modified dragonfly optimization based MIMO-OFDM for enhancing QoS in wireless multimedia Ccmmunication,” Wireless Personal Communications, Vol. 122, no. 2, pp. 1043–1065, 2022. doi:10.1007/s11277-021-08938-7
   Google Scholar
• A. Sathya, and S. Raja, “Privacy preservation-based access control intelligence for cloud data storage in smart healthcare infrastructure,” Wirel. Pers. Commun., Vol. 118, no. 4, pp. 3595–3614, 2021. doi:10.1007/s11277-021-08278-6
   Web of Science ®Google Scholar
• P. Abirami, and S. V. Bhanu, “Enhancing cloud security using crypto-deep neural network for privacy preservation in trusted environment,” Soft. comput., Vol. 24, no. 24, pp. 18927–18936, 2020. doi:10.1007/s00500-020-05122-0
   Web of Science ®Google Scholar
• F. Thabit, O. Can, S. Alhomdy, G. H. Al-Gaphari, and S. Jagtap, “A novel effective lightweight homomorphic cryptographic algorithm for data security in cloud computing,” Int J Intelligent Networks, Vol. 3, pp. 16–30, 2022.
   Google Scholar
• G. Swetha, and K. Janaki, “Cloud-based secure multimedia medical data using optimized convolutional neural network and cryptography mechanism,” Multimed. Tools. Appl., 1–37, 2022.
   Web of Science ®Google Scholar
• M. Elhoseny, K. Shankar, S. K. Lakshmanaprabu, A. Maseleno, and N. Arunkumar, “Retracted article: hybrid optimization with cryptography encryption for medical image security in internet of things,” Neural Computing and Applications, Vol. 32, no. 15, pp. 10979–10993, 2020. doi:10.1007/s00521-018-3801-x
   Web of Science ®Google Scholar
• M. Govindarajalu and S.R. Suresh, “Intelligent secure phrase search of encrypted data in cloud-based IoT”. Mater. Today: Proc., 2021.
   Google Scholar
• Y. Pu, J. Luo, C. Hu, J. Yu, R. Zhao, H. Huang, and T. Xiang, “Two secure privacy-preserving data aggregation schemes for IoT,” Wirel. Commun. Mob. Comput. 2019.
   Google Scholar
• S. Kavitha, A. Bora, M. Naved, K. B. Raj, and B. R. N. Singh, “An internet of things for data security in the cloud using artificial intelligence,” Int J Grid Distributed Comput, Vol. 14, no. 1, pp. 1257–1275, 2021.
   Google Scholar
• C. Guo, and D. Li, “Iot security privacy protection mechanism and mechanical structure design simulation optimization,” EURASIP. J. Adv. Signal. Process., Vol. 1, pp. 1–14, 2021.
   Google Scholar
• V. Jaikumar, and K. Venkatachalapathy, “Retracted article: integrative optimization with Qos using multi-level security in medical cloud,” J. Ambient. Intell. Humaniz. Comput., Vol. 12, no. 7, pp. 6923–6931, 2021. doi:10.1007/s12652-020-02337-9
   Web of Science ®Google Scholar
• J. S. Raj, “September 2020,” IRO J Sustainable Wireless Syst, Vol. 2, no. 3, pp. 118–122, 2020. doi:10.36548/jsws.2020.3.002
   Google Scholar
• J. V. Ananthi, and S. Shobana, “C-FPA: A cloud-based FPA novel approach to defend hotspot issues and attacks in WSN,” J. Inf. Technol., Vol. 4, no. 2, pp. 95–104, 2022.
   Google Scholar
• D. Avola, et al., “MS-Faster R-CNN: multi-stream backbone for improved faster R-CNN object detection and aerial tracking from UAV images,” Remote. Sens. (Basel), Vol. 13, no. 9, pp. 1670, 2021. doi:10.3390/rs13091670
   Web of Science ®Google Scholar
• M. J. Goldanloo, and F. S. Gharehchopogh, “A hybrid OBL-based firefly algorithm with symbiotic organisms search algorithm for solving continuous optimization problems,” J. Supercomput., Vol. 78, no. 3, pp. 3998–4031, 2022. doi:10.1007/s11227-021-04015-9
   Web of Science ®Google Scholar
• S. Duan, H. Luo, and H. Liu, “An elastic collision seeker optimization algorithm for optimization constrained engineering problems,” Math. Probl. Eng. 2022.
   Web of Science ®Google Scholar
• J. Piri, and P. Mohapatra, “An analytical study of modified multi-objective harris hawk optimizer towards medical data feature selection,” Comput. Biol. Med., Vol. 135, pp. 104558, 2021. doi:10.1016/j.compbiomed.2021.104558
   PubMed Web of Science ®Google Scholar
• A. J. Khan, and S. Mehfuz, “Big-data driven approaches in materials science on cloud storage API through optimal homomorphic encryption,” Mater. Today: Proc. 2021.
   Google Scholar
• R. Shrestha, and S. Kim, “Integration of IoT with blockchain and homomorphic encryption: challenging issues and opportunities,” in Advances in computers, 115, Elsevier, 2019, pp. 293–331.
   Web of Science ®Google Scholar
• V. Kumar, M. Ahmad, and A. Kumari, “A secure elliptic curve cryptography based mutual authentication protocol for cloud-assisted TMIS,” Telemat. Inform., Vol. 38, pp. 100–117, 2019. doi:10.1016/j.tele.2018.09.001
   Web of Science ®Google Scholar
• J. Su, S. He, and Y. Wu, “Features selection and prediction for IoT attacks,” High-Confidence Comput, Vol. 2, no. 2, pp. 100047, 2022. doi:10.1016/j.hcc.2021.100047
   Google Scholar
• Y. N. Kunang, S. Nurmaini, D. Stiawan, and B. Y. Suprapto, “Attack classification of an intrusion detection system using deep learning and hyperparameter optimization,” J Information Security Appl, Vol. 58, pp. 102804, 2021. doi:10.1016/j.jisa.2021.102804
   Google Scholar