Social Engineering Attacks and Human-Centric Defense Mechanism in Corporate Network

References

[1] Aditi M Jain. (2025). The Role of Predictive Analytics in E-Commerce Conversion Rate Optimization. Journal of Computer Science and Technology Studies, 7(2), 114-121. https://doi.org/10.32996/jcsts.2023.5.4.25

[2] Akinsuli, O. (2025). The rise of Al-enhanced ransomware-as-a-service (RaaS): A new threat frontier. World Journal of Advanced Engineering Technology and Sciences, 1(2), 85-97. https://doi.org/10.30574/wjaets.2021.1.2.0019

[3] Blake, H. (2025). Al-driven ransomware-as-a-service: The next wave of cybercrime innovation. ResearchGate Preprint.

[4] Chaudhary, A. (2025). How to combat the growing threat of ransomware. New Haven Register. NEW HAVEN REGISTER

[5] Jain, A. M. (2025). Enhancing e-commerce accessibility with AI-powered chatbots: Integrating accessibility tools and navigation assistants. Journal of Information Systems Engineering and Management, 10(15s), 797–809. https://doi.org/10.52783/jisem.v10i15s.2522

[6] Jain, A. M., & Jain, A. (2025). AI-based content creation and product recommendation applications in e-commerce: An ethical overview. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 11(1). https://doi.org/10.32628/CSEIT2410414

[7] K. S. Sharif, M. M. Uddin and M. Abubakkar, "NeuroSignal Precision: A Hierarchical Approach for Enhanced Insights in Parkinson's Disease Classification," 2024 International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA), Bali, Indonesia, 2024, pp. 1244-1249, https://doi.org/10.1109/ICICYTA64807.2024.10912990

[8] Liu, X., Liang, J., Yan, Q., Ye, M., Jia, J., & Xi, Z. (2025). Cyber defense reinvented: Large language models as threat intelligence copilots. arXiv Preprint. https://arxiv.org/abs/2502.20791 Mezzi, E., Massacci, F., & Tuma, K. (2025). Large language models are unreliable for cyber threat intelligence. arXiv Preprint. https://arxiv.org/abs/2503.23175

[9] Machireddy, J. R. (2024). Machine learning and automation in healthcare claims processing. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 6(1), 686-701.

[10] Machireddy, Jeshwanth,Automation in Healthcare Claims Processing: Enhancing Efficiency and Accuracy(April 16, 2023). International Journal of Science and Research Archive, 2023, 09(01), 825-834, Available at  http://dx.doi.org/10.2139/ssrn.5159747

[11] Mezzi, E., Massacci, F., & Tuma, K. (2025). Large language models are unreliable for cyber threat intelligence. arXiv Preprint. https://arxiv.org/abs/2503.23175

[12] Oyekunle, S. M., Tiwo, O. J., Adesokan-Imran, T. O., Ajayi, A. J., Salako, A. O., & Olaniyi, O. O. (2025). Enhancing data resilience in cloud-based electronic health records through ransomware mitigation strategies using NIST and MITRE ATT&CK frameworks. Journal of Engineering Research and Reports, 27(3), 436-457. https://doi.org/10.9734/jerr/2025/v27131444

[13] Saeed, S., Suayyid, S. A., Al-Ghamdi, M. S., Al-Muhaisen, H., & Almuhaideb, A. M. (2023). A systematic literature review on cyber threat intelligence for organizational cybersecurity resilience. Sensors, 23(16), 7273. https://doi.org/10.3390/s23167273

[14] Saeed, S., Suayyid, S. A., Al-Ghamdi, M. S., Al-Muhaisen, H., & Almuhaideb, A.

[15] Sorokoletova, O., Antonioni, E., & Colò, G. (2025). Towards a scalable Al-driven framework for data-independent cyber threat intelligence information extraction. arXiv Preprint. https://arxiv.org/abs/2501.06239

[16] Sorokoletova, O., Antonioni, E., & Colò, G. (2025). Towards a scalable Al-driven framework for data-independent cyber threat intelligence information extraction. arXiv Preprint. https://arxiv.org/abs/2501.06239

[17] Threat Intelligence 1. Liu, X., Liang, J., Yan, Q., Ye, M., Jia, J., & Xi, Z. (2025). Cyber defense reinvented: Large language models as threat intelligence copilots. arXiv Preprint. https://arxiv.org/abs/2502.20791

[18] Willie, A. (2025). The evolution of ransomware-as-a-service (RaaS): Al's role in cybercrime and countermeasures. ResearchGate Preprint. 4. Dhawan, A., Foley, S., & Mollica, V. (2025). Splitting the spoils: The economics of ransomware as a service. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5110191

@article{1708001,
      author = {Nageshwar Masakapalli, Rohith Vodapally},
      title = {Social Engineering Attacks and Human-Centric Defense Mechanism in Corporate Network},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {9},
      pages = {1632-1637},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1708001.pdf},
      abstract = {The exploitation of human characteristics through social engineering has become an important network security threat which addresses mental vulnerabilities instead of system weaknesses. The phishing baits pretext attacks force users to expose secrets or let their actions endanger the security infrastructure. Most traditional security defenses which primarily depend on technical methods do not address human vulnerabilities and therefore create an important hole in cyber security systems. The research evaluates defense systems that focus on human beings as a means to reduce social engineering attack risks across different environments. A combination of literature review and case study and comparative analysis demonstrates why organizations need awareness training with reinforced behavioral practices and culture changes to improve their defenses. Organizations need to combine psychological and behavioral scientific knowledge with their cyber security plans to establish enduring security systems for their corporate facilities.},
      keywords = {Social Engineering, Human-centric Security, Corporate Network, Phishing, Cyber security Awareness, Insider Threats, Social Manipulation},
      month = {March},
  }