Gen AI Based File Transfer Using Protocols

Yogadharani M; Sathishwar R; Mohamed Kamil M; Anbu Selavan K; Vinoth M1

1

Publication Date: 2024/12/21

Abstract: File transfer protocols are the backbone of digital communication, enabling seamless and efficient data exchange across networks. These protocols standardize the process of transferring files, addressing key challenges such as reliability, security, efficiency, and compatibility. As the demand for rapid and secure data exchange grows across domains, file transfer protocols play a pivotal role in ensuring smooth operations. Prominent protocols such as File Transfer Protocol (FTP), Secure File Transfer Protocol (SFTP), and Hypertext Transfer Protocol (HTTP/HTTPS) cater to specific use cases ranging from simple file sharing to secure data exchange. Peer-to-peer (P2P) protocols like BitTorrent offer decentralized solutions for large-scale file sharing, while lightweight protocols like Trivial File Transfer Protocol (TFTP) focus on small-scale, resource- constrained environments. Each protocol addresses unique requirements, offering flexibility for diverse applications such as cloud synchronization, multimedia distribution, enterprise data sharing, and remote device management. Security is a critical aspect of file transfer, with protocols like SFTP and HTTPS incorporating encryption to safeguard data during transmission. Reliability is achieved through features like error detection and retransmission mechanisms. Efficiency is enhanced by optimizing bandwidth usage, particularly in P2P networks, where decentralized sharing reduces the load on centralized servers. In addition to addressing traditional file transfer needs, emerging trends in networking and computing are influencing protocol evolution. Artificial intelligence (AI) is being integrated to optimize routing and transmission decisions, improving speed and efficiency. Blockchain technology is enhancing security and integrity in decentralized systems by providing transparent and tamper-proof records of file transactions. The growing importance of file transfer protocols is evident in their widespread application across industries. In cloud computing, these protocols enable seamless access and synchronization of files across devices. In multimedia streaming, they ensure smooth delivery of high-quality content to users. In enterprise environments, secure file transfer protocols are vital for regulatory compliance and protecting sensitive information. Despite their advancements, challenges remain. High-latency networks, limited bandwidth in resource- constrained areas, and the increasing size of data files necessitate ongoing innovation. Research continues to focus on developing protocols that strike a balance between speed, security, and resource utilization. As digital ecosystems expand, file transfer protocols will continue to evolve, shaping the way data is exchanged in increasingly interconnected environments. Their ability to adapt to emerging technologies and address complex requirements ensures they remain at the core of modern networking, driving innovation and efficiency in data transmission.

Keywords: No Keywords Available

DOI: https://doi.org/10.5281/zenodo.14539933

PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24DEC599.pdf

REFERENCES

  1. P. M. N. G. Ms. Naziya Shaikh, " File Sharing System And     Methodology " IOSR Journal of Computer Engineering (IOSR-JCE), pp. 1-5, 2021.
  2. H. A. O. and N. I. O. Eman J. Coco, "File transfer using network," An International Journal (CAIJ), vol. 5, no. 2, pp. 1-18, May 2018.
  3. N. F. R. J. I. M. Christie Thottam, "Intelligent Python Code Analyzer [IPCA]," International Journal of Creative Research Thoughts (IJCRT), vol. 12, no. 3, pp. 1-11, March 2024.
  4. N. M. S., S. J., L. R., Z. R., F. A., R. T., N. N., H. W., and H. H. Chongzhou Fang, "Large Language Models for Code Generation and Translation," ACM Transactions on Programming Languages and Systems (TOPLAS), vol. 45, no. 7, pp. 1-15, July 2023.
  5. R. D. Patel and M. K. Vyas, "Automated SQL Query Generator Using Natural Language Processing," International Journal of Advanced Trends in Computer Science and Engineering (IJATCSE), vol. 9, no. 4, pp. 34-42, August 2021.
  6. Y. Liu, T. Chen, and K. Y. Lee, "AI-Driven Data Visualization and SQL Query Automation," IEEE Transactions on Big Data, vol. 9, no. 2, pp. 112-126, April 2023.
  7. J. K. Varun and L. E. Susan, "Towards Efficient SQL Query Generation for Business Intelligence Systems," Journal of Applied Computational Intelligence and Soft Computing, vol. 2022, Article ID 659742, pp. 1-9, 2022.