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Integrating Innovations: A Comprehensive Review of Emerging Technologies in AI, Cybersecurity, Blockchain, Mobile Systems, and Industrial Automation

Naveen Madipelli Sriram Kuriseti Sarath Babu Rakki Amrutham Naresh Kumar Rathla Roop Singh

Subject area: Science,Engineering and Technology  ·  Area of research: Computer Science and Engineering

Abstract

This paper provides a comprehensive review of emerging technologies, including artificial intelligence (AI), cybersecurity, blockchain, mobile systems, and industrial automation, highlighting their revolutionary impact across various industries. These technologies are interconnected, with advancements in one often influencing others, leading to a need for a holistic understanding of their relationships. Their convergence offers solutions to current system limitations and fosters unprecedented growth in diverse sectors. However, these integrated technologies are still in their early stages due to the lack of mature reference models and best practices. The review focuses on how these convergent technologies address contemporary security concerns, emphasizing robust governance and protocols for cybersecurity measures at both the ongoing and micro levels within our interconnected world. In today's information environment, the highly inflated and merged of numerous (information) areas, where among many other things, artificial intelligence, cybersecurity, blockchain, mobile systems, and industrial automation constitute a groundbreaking revolution that recasts industrial branches and creates new operational dynamics, these technologies are not operating alone, but are intensively linked and interlinked interdependences and synergies, and are ways in which progress in one technology sends signals across a broad band of different technologies, requiring an appreciation of the systems of inter-relationship. The convergence of these technologies may solve today?s system limits and unlock revolutionary growth in various industry areas. Still, today, these integrated technologies are in their infancy because there are immature reference models and best practices. This paper will look into an overview and review of the emerging technologies under these new technologies from point of convergence to challenge one through advancements slated from your demands generated by convergence view that converges unclaimed by the central concept that yields the notion of the hub for the security concerns, focus on robust governance and/or protocol conducting security measures of the Cybersecurity at underway/micro level that address the issues of today in our inter connected generation.

Keywords

Artificial Intelligence (AI), Cybersecurity, Blockchain, Mobile Systems.

References

[1] Agudelo Aguirre A. A., Duque Méndez N. D., & Rojas Medina R. A. (2021). Artificial intelligence applied to investment in variable income through the MACD (moving average convergence/divergence) indicator. Journal of Economics, Finance and Administrative Science, 26(52), 268–281.

[2] Konda, B. (2024). Explore Data Mining (DM) Techniques That Data Scientists Adopt in IT.

[3] R. Wang, M. Luo, Y. Wen, L. Wang, K. R. Choo, and D. He, “The Applications of Blockchain in Artificial Intelligence,” Security and Communication Networks, vol. 2021, p. 1, Sep. 2021,

[4] V. K. Kasula et al., "Hybrid Short Comparable Encryption with Sliding Window Techniques for Enhanced Efficiency and Security," International Journal of Science and Research Archive, 2022, 5(01), 151-161.

[5] D. Bhumichai, C. Smiliotopoulos, R. Benton, G. Kambourakis, and D. Damopoulos, “The Convergence of Artificial Intelligence and Blockchain: The State of Play and the Road Ahead,” Information, vol. 15, no. 5, p. 268, May 2024,

[6] Yenugula, M. (2024). Challenges With Accountability, Trust & System Security in Google Cloud Platform (GCP).

[7] P. Pawar et al., “Securing Digital Governance: A Deep Learning and Blockchain Framework for Malware Detection in IoT Networks,” p. 1, Nov. 2024, 10.1109/iciics63763.2024.10860155.

[8] Yadulla, A. R. (2024). A qualitative approach to data breaches in mobile devices.

[9] H. Taherdoost, “Blockchain Technology and Artificial Intelligence Together: A Critical Review on Applications,” Applied Sciences, vol. 12, no. 24. Multidisciplinary Digital Publishing Institute, p. 12948, Dec. 16, 2022.

[10] I. Jada and T. O. Mayayise, “The impact of artificial intelligence on organisational cyber security: An outcome of a systematic literature review,” Data and Information Management, vol. 8, no. 2, p. 100063, Dec. 2023, 10.1016/j.dim.2023.100063.

[11] M. Yenugula et al., "Dynamic Data Breach Prevention in Mobile Storage Media Using DQN-Enhanced Context-Aware Access Control and Lattice Structures," International Journal Of Research In Electronics And Computer Engineering, 2022, 10(4), 127-136.

[12] S. Menon et al., “Streamlining task planning systems for improved enactment in contemporary computing surroundings,” SN Computer Science, vol. 5, no. 8, Oct. 2024.

[13] M. D. Schultz and P. Seele, “Towards AI ethics’ institutionalization: knowledge bridges from business ethics to advanced organizational AI ethics,” AI and Ethics, vol. 3, no. 1, p. 99, Mar. 2022,

[14] Kasula, V. (2024). Leveraging Deep Learning Techniques for Enhancing Financial Security Systems: A Comprehensive Review of Methods, Applications, and Challenges. International Journal of Communication Networks and Information Security (IJCNIS), 16(5), 969–978.

[15] H. Gonaygunta et al., “The detection and prevention of cloud computing attacks using artificial intelligence technologies,” Int. J. Multidiscip. Res. Publ. (IJMRAP), vol. 6, no. 8, pp. 191–193, 2024.

[16] N. Mohamed, “Artificial Intelligence in Cybersecurity: A Review of Solutions for APT- Exploited Vulnerabilities,” 2022 13th International Conference on Computing, Communication and Networking Technologies (ICCCNT). p. 1, Jun. 24, 2024. 10.1109/icccnt61001.2024.10724084.

[17] B. Konda et al., "Homomorphic encryption and federated attribute-based multi-factor access control for secure cloud services in integrated space-ground information networks," International Journal of Communication and Information Technology, 2022, 3(2): 33-40.

[18] M. Roshanaei, M. R. Khan, and N. N. Sylvester, “Navigating AI Cybersecurity: Evolving Landscape and Challenges,” Journal of Intelligent Learning Systems and Applications, vol. 16, no. 3, p. 155, Jan. 2024, 10.4236/jilsa.2024.163010.

[19] C. Williams, R. Chaturvedi, R. D. Urman, R. S. Waterman, and R. A. Gabriel, “Artificial Intelligence and a Pandemic: an Analysis of the Potential Uses and Drawbacks,” Journal of Medical Systems, vol. 45, no. 3, Jan. 2021, 10.1007/s10916-021-01705-y.

[20] A. R. Yadulla et al., "A time-aware LSTM model for detecting criminal activities in blockchain transactions," International Journal of Communication and Information Technology, 2023, 4(2): 33-39.

[21] S. R. Addula and G. S. Sajja, "Automated Machine Learning to Streamline Data-Driven Industrial Application Development," 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES), Lucknow, India, 2024, pp. 1 -4, 10.1109/IC3TES62412.2024.10877481.

[22] V. K. Kasula et al., "Enhancing financial cybersecurity: An AI-driven framework for safeguarding digital assets," World Journal of Advanced Research and Reviews, 2022.

[23] K. Yue and Y. Shen, “An overview of disruptive technologies for aquaculture,” Aquaculture and Fisheries, vol. 7, no. 2, p. 111, Jun. 2021,

[24] D. Rotolo, D. Hicks, and B. R. Martin, “What is an emerging technology?,” Research Policy, vol. 44, no. 10, p. 1827, Aug. 2015, 10.1016/j.respol.2015.06.006.

[25] M. Yenugula et al., "Enhancing Mobile Data Security with Zero-Trust Architecture and Federated Learning: A Comprehensive Approach to Prevent Data Leakage on Smart Terminals," Journal of Recent Trends in Computer Science and Engineering (JRTCSE), 2023, 11(1), 52-64.

[26] C. Tumma et al., "Data Security and Privacy Protection in Artificial Intelligence Models: Challenges and Defense Mechanisms," Int. J. Sci. Res. Eng. Manag., vol. 7, no. 12, pp. 1–11, 2022.

[27] S. Ayyamgari et al., "Quantum Computing: Challenges and Future Directions," Int. J. Adv. Res. Sci. Commun. Technol., vol. 3, no. 3, pp. 1343–1347, 2023.

[28] A. R. Yadulla et al., A. R., Kasula, V. K., Yenugula, M., & Konda, B. (2023). Enhancing Cybersecurity with AI: Implementing a Deep Learning-Based Intrusion Detection System Using Convolutional Neural Networks. European Journal of Advances in Engineering and Technology, 10(12), 89-98.

[29] P. P. Pawar et al., “SINN based federated learning model for intrusion detection with blockchain technology in digital forensic,” in Proc. 2024 Int. Conf. Data Sci. Netw. Secur. (ICDSNS), July 2024, pp. 01–07.

[30] Y. Abdulrahman, E. Arnautović, V. Parezanović, and D. Svetinović, “AI and Blockchain Synergy in Aerospace Engineering: An Impact Survey on Operational Efficiency and Technological Challenges,” IEEE Access, vol. 11, p. 87790, Jan. 2023, 10.1109/access.2023.3305325.

[31] M. H. Najmi, S. Iqbal, and S. A. Khan, “Aligning Supply Chain Functions with Emerging Technologies: A Strategic Approach,” p. 34, Oct. 2024, 10.3390/engproc2024076034.

[32] B. Konda et al., "A Public Key Searchable Encryption Scheme Based on Blockchain Using Random Forest Method," International Journal Of Research In Electronics And Computer Engineering, 2024, 12(1), 77-83.

[33] R. K. Sinha, “The role and impact of new technologies on healthcare systems,” Discover Health Systems, vol. 3, no. 1, Nov. 2024, 10.1007/s44250-024-00163-w.

[34] D. Kumar et al., “Enhanced stock market trend prediction on the Indonesia stock exchange using improved bacterial foraging optimization and elitist whale optimization algorithms,” in Proc. 2024 Int. Conf. Integrated Intelligence and Communication Systems (ICIICS), Nov. 2024, pp. 1–8.

[35] M. A. Naeem, N. Alfaoui, and L. Yarovaya, “The Contagion Effect of Artificial Intelligence across Innovative Industries: From Blockchain and Metaverse to Cleantech and Beyond,” SSRN Electronic Journal, Jan. 2024, 10.2139/ssrn.4816366.

[36] Misra, N. K., et al. (2024). “Covid-19 pandemic: A worldwide critical review with the machine learning model-based prediction,” Journal of The Institution of Engineers (India): Series B, vol. 106, no. 1, pp. 339–349, Sep. 2024.

[37] P. P. Pawar et al., “A patient-centric blockchain framework for transparent and secure medical data sharing using modified AES,” in Proc. 2024 Int. Conf. Integrated Intelligence and Communication Systems (ICIICS), Nov. 2024,p. 1

[38] R. Kumar, Arjunaditya, D. Singh, K. Srinivasan, and Y. Hu, “AI -Powered Blockchain Technology for Public Health: A Contemporary Review, Open Challenges, and Future Research Directions,” Healthcare, vol. 11, no. 1. Multidisciplinary Digital Publishing Institute, p. 81, Dec. 27, 2022. 10.3390/healthcare11010081.

[39] A. Shrivastava, U. Jain, M. Al-Farouni, Y. Kumar, R. J. Anandhi, and M. Bhavana, “Proposed Framework for Modifications to Artificial Intelligence/Machine Learning (Ai/Ml)-Based Software as A Medical Device (SAMD),” p. 1755, Sep. 2024, 10.1109/ic3i61595.2024.10829073.

[40] Sajja, G. S., et al. (2024, November). Automation using robots, machine learning, and artificial intelligence to enhance production and quality. In 2024 Second International Conference on Computational and Characterization Techniques in Engineering & Sciences (IC3TES) (pp. 1–4). IEEE.

[41] Deng S., Yu H., Wei C., Yang T., & Tatsuro S. (2021). The profitability of Ichimoku Kinkohyo based trading rules in stock markets and FX markets. International Journal of Finance & Economics, 26(4), 5321–5336.

[42] N. G. Nia, E. Kaplanoğlu, and A. Nasab, “Evaluation of artificial intelligence techniques in disease diagnosis and prediction,” Discover Artificial Intelligence, vol. 3, no. 1, Jan. 2023,

[43] Li, Z., Liang, X., Wen, Q., & Wan, E. (2024). The Analysis of Financial Network Transaction Risk Control based on Blockchain and Edge Computing Technology. IEEE Transactions on Engineering Management.

[44] D. Darne and S. Agrawal, “The Role of Artificial Intelligence in the Management of Long-term Care and Prevention,” p. 1, Nov. 2024, 10.1109/idicaiei61867.2024.10842723.

[45] A. Chang, “The Role of Artificial Intelligence in Digital Health,” in Computers in health care, Springer International Publishing, 2019, p. 71.

[46] B. Y. R. Thumma et al., "Cloud Security Challenges and Future Research Directions," Int. Res. J. Mod. Eng. Technol. Sci., vol. 4, no. 12, pp. 2157–2162, 2022.

[47] R. Azmeera et al., "Enhancing blockchain communication with named data networking: A novel node model and information transmission mechanism," J. Recent Trends Comput. Sci. Eng. (JRTCSE), vol. 10, no. 1, pp. 35–53, 2022.

[48] S. E. Vadakkethil et al., "Mayfly optimization algorithm with bidirectional long-short term memory for intrusion detection system in Internet of Things," in Proc. 2024 3rd Int. Conf. Distributed Computing and Electrical Circuits and Electronics (ICDCECE), Apr. 2024, pp. 1– 4.

How to cite this paper

Naveen Madipelli, Sriram Kuriseti, Sarath Babu Rakki, Amrutham Naresh Kumar, Rathla Roop Singh "Integrating Innovations: A Comprehensive Review of Emerging Technologies in AI, Cybersecurity, Blockchain, Mobile Systems, and Industrial Automation" Iconic Research And Engineering Journals Volume 8 Issue 5 2024 Page 1356-1362
Naveen Madipelli, Sriram Kuriseti, Sarath Babu Rakki, Amrutham Naresh Kumar, Rathla Roop Singh "Integrating Innovations: A Comprehensive Review of Emerging Technologies in AI, Cybersecurity, Blockchain, Mobile Systems, and Industrial Automation" Iconic Research And Engineering Journals, vol. 8, no. 5, Nov. 2024
Naveen Madipelli, Sriram Kuriseti, Sarath Babu Rakki, Amrutham Naresh Kumar, Rathla Roop Singh (2024). Integrating Innovations: A Comprehensive Review of Emerging Technologies in AI, Cybersecurity, Blockchain, Mobile Systems, and Industrial Automation. Iconic Research And Engineering Journals, 8(5).
Naveen Madipelli, Sriram Kuriseti, Sarath Babu Rakki, Amrutham Naresh Kumar, Rathla Roop Singh "Integrating Innovations: A Comprehensive Review of Emerging Technologies in AI, Cybersecurity, Blockchain, Mobile Systems, and Industrial Automation" Iconic Research And Engineering Journals, vol. 8, no. 5, Nov. 2024.
@article{1709579,
      author = {Naveen Madipelli, Sriram Kuriseti, Sarath Babu Rakki, Amrutham Naresh Kumar, Rathla Roop Singh},
      title = {Integrating Innovations: A Comprehensive Review of Emerging Technologies in AI, Cybersecurity, Blockchain, Mobile Systems, and Industrial Automation},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {5},
      pages = {1356-1362},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1709579.pdf},
      abstract = {This paper provides a comprehensive review of emerging technologies, including artificial intelligence (AI), cybersecurity, blockchain, mobile systems, and industrial automation, highlighting their revolutionary impact across various industries. These technologies are interconnected, with advancements in one often influencing others, leading to a need for a holistic understanding of their relationships. Their convergence offers solutions to current system limitations and fosters unprecedented growth in diverse sectors. However, these integrated technologies are still in their early stages due to the lack of mature reference models and best practices. The review focuses on how these convergent technologies address contemporary security concerns, emphasizing robust governance and protocols for cybersecurity measures at both the ongoing and micro levels within our interconnected world. In today's information environment, the highly inflated and merged of numerous (information) areas, where among many other things, artificial intelligence, cybersecurity, blockchain, mobile systems, and industrial automation constitute a groundbreaking revolution that recasts industrial branches and creates new operational dynamics, these technologies are not operating alone, but are intensively linked and interlinked interdependences and synergies, and are ways in which progress in one technology sends signals across a broad band of different technologies, requiring an appreciation of the systems of inter-relationship. The convergence of these technologies may solve today?s system limits and unlock revolutionary growth in various industry areas. Still, today, these integrated technologies are in their infancy because there are immature reference models and best practices. This paper will look into an overview and review of the emerging technologies under these new technologies from point of convergence to challenge one through advancements slated from your demands generated by convergence view that converges unclaimed by the central concept that yields the notion of the hub for the security concerns, focus on robust governance and/or protocol conducting security measures of the Cybersecurity at underway/micro level that address the issues of today in our inter connected generation.},
      keywords = {Artificial Intelligence (AI), Cybersecurity, Blockchain, Mobile Systems.},
      month = {November},
  }