A Survey on Network Security Using Fog Computing

References

[1] Sangeetha K.S, Prakash P, "Big Data and cloud: A survey", (2015) Advances in Intelligent Systems and Computing, 325, pp. 773-778.

[2] Shiva Jegan R.D, Vasudevan S.K, Abarna K., Prakash P, Srivathsan S., Gangothri V., "Cloud computing: A Technical Gawk", (2014) International Journal of Applied Engineering Research, 9(14), pp. 2539-2554.

[3] Viraj G. Mandlekar, VireshKumarMahale, SanketS.Sancheti, Maaz S. Rais, "Survey on Fog Computing Mitigating Data Theft Attacks in Cloud", International Journal of Innovative Research in Computer Science & Technology, Nov - 2014.

[4] Ramin Elahi, "Fog Computing and its Ecosystem", SNIA Global Education, 2015.

[5] Tom H. Luan, Longxiang Gao, Zhi Li, Yang Xiang, Guiyi We, and Limin Sun, "Fog Computing: Focusing on mobile Users at the Edge", Mar 2016.

[6] Shanhe Yi, Zhengrui Qin and Qun Li, “Security and Privacy Issues of Fog Computing: A Survey”, International Conference on Wireless Algorithms, Systems, and Applications, 2015, pp. 685-695.

[7] Shanhe Yi, Zijiang Hao, Zhengrui Qin, and Qun Li, "Fog Computing: Platform and Applications", dept. Of Computer Science, College of William and Mary, IEEE - 2015.

[8] Harshit Gupta, Amir Vahid Dastjerdi, Soumya K. Ghosh and Rajkumar Buyya, “iFogSim: A Toolkit for Modeling and Simulation of Resource Management Techniques in Internet of Things, Edge and Fog Computing Environments”, Cloud Computing and Distributed Systems Laboratory, The University of Melbourne, June 6, 2016.

[9] Shanhe Yi, Zijiang Hao, Zhengrui Qin, and Qun Li, "Fog Computing: Platform and Applications", dept. Of Computer Science, College of William and Mary, IEEE - 2015.

[10] Shanhe Yi, Zhengrui Qin, and Qun Li, "Security and Privacy Issues Of Fog Computing: A Survey", College of William and Mary.

[11] Shanhe Yi, Zijiang Hao, Zhengrui Qin, and Qun Li, "Fog Computing: Platform and Applications", dept. Of Computer Science, College of William and Mary, IEEE - 2015.

[12] Shanhe Yi, Zijiang Hao, Zhengrui Qin, and Qun Li, "Fog Computing: Platform and Applications", dept. Of Computer Science, College of William and Mary, IEEE - 2015.

[13] Tom H. Luan, Longxiang Gao, Zhi Li, Yang Xiang, Guiyi We, and Limin Sun, "Fog Computing: Focusing on mobile Users at the Edge", Mar 2016.

[14] Amir Vahid Dastjerdi, Harshit Gupta, Rodrigo N. Calheiros, Soumya K. Ghosh, and Rajkumar Buyya, "Fog Computing: Principles, Architectures, and Applications", IEEE -21016.

[15] Anuj Kumar, K.P Saharan, "Fog in comparison to cloud: A survey", International Journal of Computer Applications, Jul – 2015.

[16] S. Wu et al., “Survey on Prediction Algorithms in Smart Homes,” IEEE Internet Things J., vol. 4, no. 3, pp. 636–644, Jun. 2017.

[17] Z. M. Fadlullah et al., “State-of-the-Art Deep Learning: Evolving Machine Intelligence Toward Tomorrow’s Intelligent Network Traffic Control Systems,” IEEE Commun. Surv. Tutorials, vol. 19, no. 4, pp. 2432–2455, 2017.

[18] H.-C. Shih, “A robust occupancy detection and tracking algorithm for the automatic monitoring and commissioning of a building,” Energy Build., vol. 77, pp. 270–280, Jul. 2014.

@article{1704094,
      author = {V. Suresh Kumar, Dr. P. E. Elango},
      title = {A Survey on Network Security Using Fog Computing},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {8},
      pages = {97-100},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1704094.pdf},
      abstract = {Due to the current exponential growth of data, a brand-new paradigm known as fog computing has emerged, providing low-latency real-time network access. It is simple to access and process our personal data or corporate information using cloud computing technology, which provides large cloud storage and a central cloud server, but its main negatives are its high latency and security issues. Therefore, fog computing technology is crucial for enabling real-time applications like AI, IOT, and 5G The three-tier architecture of fog computing and its network links are modelled in this article. The exponential expansion of multimedia data makes cloud storage highly expensive and unsuitable for applications that require low latency. High bandwidth and data mobility are provided by fog computing facilities. The Fogonomics business model is an efficient way to deliver all cloud capabilities to the edge of the computer network while only charging for computational services, saving money on both data processing and data transit. Both technology and economics are improved. This study's findings demonstrate how the IOT networks' capabilities and income potential are greatly increased by the inclusion of fog.},
      keywords = {Networks, Fog, cloud, IOT},
      month = {February},
  }