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Various Security issues and its
Solutions in the domain of Fog
Computing
by
Manash Kumar Mondal
Dept. Computer Science and Engg.
University of Kalyani
Content
• Fog computing
• Architecture of Fog Computing
• Application of Fog in Real Word
• Loop holes in fog architecture
• Fog Security Technique
• Conclusion
Fog computing
• Fog computing is an extension of Cloud Computing. Few researchers
treat fog computing as edge computing. Nowadays, billions of users
use fog/ edge enable IoT devices. Simultaneously, a trillion GB of data
is generated every second.
• That massive amount of data is needed to be secured. IoT has
become popular day by day, and Cisco introduced Fog Computing (FC)
for the excellent management of the devices[4]. A three-layer
architecture is suggested by CISCO that supports several real-life
items like energy grid, buildings, smart cities etc.
Architecture of Fog Computing
Application of Fog in Real Word
• Fog computing is becoming popular daily due to the advancement of
fog computing over cloud computing like bandwidth, latency, and
connectivity issues.
• Many-reputed organizations prefer fog in real-life. Nowadays, almost
all IoT devices are associated with fog computing. Such applications
widely use fog computing as a backbone of the entire system rather
than cloud computing.
• The following example cover two major applications of fog
computing.
Vehicular Ad Hoc Networks (VAETs)
Smart Cities
Loop holes in fog architecture
End user device layer Virtualization Core layer,
Local Data Center layer
Network layer
Information injecting Resource misuse Hardware damage (physical) Man in the
Middle attack
Privileges escalation Rogue Gateway
Leakage of privacy Denial-of-Service (DoS) attack
Service
manipulation
Virtual Machine (VM)
manipulation
Rogue DCs
Fog Security Technique
Conclusions:
• This article covers the architecture of fog computing in details. Few
real life applications along with their working principles is also
highlighted.
• In this particular article, we have mainly focus the security issues and
its solution in different aspects.
• This paper also highlighted the loopholes in every layer in FC. We also
make a roadmap to the future researcher that they can find the all
related work in one umbrella.
References
• [1] H. Madsen and B. Burtschy, “Reliability in the Utility Computing Era : Towards Reliable Fog Computing,” pp. 43–46, 2013.
• [2] I. Stojmenovic and S. Wen, “The Fog Computing Paradigm:Scenarios and Security Issues,” Proc. 2014 Fed. Conf. Comput. Sci. Inf. Syst., vol. 2, pp. 1–8, 2014.
• [3] B. Tang, Z. Chen, G. Hefferman, T. Wei, H. He, and Q. Yang, “A Hierarchical Distributed Fog Computing Architecture for Big Data Analysis in Smart Cities,” Proc. ASE BigData Soc. 2015, p. 28:1- 28:6, 2015.
• [4] F. Bonomi, R. Milito, J. Zhu, and S. Addepalli, “Fog Computing and Its Role in the Internet of Things,” Proc. first Ed. MCC Work. Mob. cloud Comput., pp. 13–16, 2012.
• [5] T. H. Luan, L. Gao, Z. Li, Y. Xiang, and L. Sun, “Fog Computing: Focusing on Mobile Users at the Edge,” eprint arXiv:1502.01815, pp. 1–11, 2015.
• [6] S. J. Stolfo, M. Ben Salem, and A. D. Keromytis, “Fog computing: Mitigating insider data theft attacks in the cloud,” Proc. - IEEE CS Secur. Priv. Work. SPW 2012, pp. 125–128, 2012.
• [7] S. M. Oriol, J. Jacob, and T. Dimitrakos, “Security Challenges in Cloud Computing,” Gerontologist, vol. 53, no. 2, p. NP, 2013.
• [8] A. Kanuparthi, R. Karri, and S. Addepalli, “Hardware and embedded security in the context of internet of things,” Proc. 2013 ACM Work. Secur. Priv. dependability cyber Veh. - CyCAR ’13, pp. 61–64, 2013.
• [9] K. Lee, D. Kim, D. Ha, U. Rajput, and H. Oh, “On Security and Privacy Issues of Fog Computing supported Internet of Things Environment.”
• 10] B. P. Panciatici, G. Bareux, and L. Wehenkel, “Security Management Under Uncertainty,” no. october, 2012.
• [11] W. Wang and Z. Lu, “Cyber security in the Smart Grid: Survey and challenges,” Comput. Networks, vol. 57, no. 5, pp. 1344–1371, 2013.
• [12] A. Volokyta, I. Kokhanevych, and D. Ivanov, “Secure virtualization in cloud computing,” 11th Int. Conf. Mod. Probl. Radio Eng. Telecommun. Comput. Sci., p. 395, 2012.
• [13] P. V. Madhwai and 1D. C. Saste, “FOG COMPUTING : Comprehensive Approach For Avoiding Data Theft Attack Using,” vol. 3, no. 3, pp. 3132–3139, 2015.
• [14] C. Dsouza, G. J. Ahn, and M. Taguinod, “Policy-driven security management for fog computing: Preliminary framework and a casestudy,” Proc. 2014 IEEE 15th Int. Conf. Inf. Reuse Integr. IEEE IRI 2014, pp. 16–23,
2014.
• [15] P. Kumar, N. Zaidi, and T. Choudhur, “Fog Computing : Common
• Security Issues and Proposed Countermeasures,” pp. 311–315, 2016.
• [16] C. Chen, H. Raj, S. Saroiu, I. Nsdi, and A. Wolman, “cTPM : A Cloud TPM for Cross-Device Trusted Applications,” 11th USENIX Conf. Networked Syst. Des. Implement., vol. 8, pp. 187–201, 2014.
• [17] R. Lu, K. Heung, A. Lashkari, and A. Ghorbani, “A Lightweight Privacy-Preserving Data Aggregation Scheme for Fog Computing- Enhanced IoT,” IEEE Access, vol. 5, pp. 1–1, 2017.
• [18] Z. Qin, S. Yi, Q. Li, and D. Zamkov, “Preserving secondary users’ privacy in cognitive radio networks,” Proc. - IEEE INFOCOM, pp. 772–780, 2014.

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Various security issues and its solutions in the

  • 1. Various Security issues and its Solutions in the domain of Fog Computing by Manash Kumar Mondal Dept. Computer Science and Engg. University of Kalyani
  • 2. Content • Fog computing • Architecture of Fog Computing • Application of Fog in Real Word • Loop holes in fog architecture • Fog Security Technique • Conclusion
  • 3. Fog computing • Fog computing is an extension of Cloud Computing. Few researchers treat fog computing as edge computing. Nowadays, billions of users use fog/ edge enable IoT devices. Simultaneously, a trillion GB of data is generated every second. • That massive amount of data is needed to be secured. IoT has become popular day by day, and Cisco introduced Fog Computing (FC) for the excellent management of the devices[4]. A three-layer architecture is suggested by CISCO that supports several real-life items like energy grid, buildings, smart cities etc.
  • 5. Application of Fog in Real Word • Fog computing is becoming popular daily due to the advancement of fog computing over cloud computing like bandwidth, latency, and connectivity issues. • Many-reputed organizations prefer fog in real-life. Nowadays, almost all IoT devices are associated with fog computing. Such applications widely use fog computing as a backbone of the entire system rather than cloud computing. • The following example cover two major applications of fog computing.
  • 6. Vehicular Ad Hoc Networks (VAETs)
  • 8. Loop holes in fog architecture End user device layer Virtualization Core layer, Local Data Center layer Network layer Information injecting Resource misuse Hardware damage (physical) Man in the Middle attack Privileges escalation Rogue Gateway Leakage of privacy Denial-of-Service (DoS) attack Service manipulation Virtual Machine (VM) manipulation Rogue DCs
  • 10. Conclusions: • This article covers the architecture of fog computing in details. Few real life applications along with their working principles is also highlighted. • In this particular article, we have mainly focus the security issues and its solution in different aspects. • This paper also highlighted the loopholes in every layer in FC. We also make a roadmap to the future researcher that they can find the all related work in one umbrella.
  • 11. References • [1] H. Madsen and B. Burtschy, “Reliability in the Utility Computing Era : Towards Reliable Fog Computing,” pp. 43–46, 2013. • [2] I. Stojmenovic and S. Wen, “The Fog Computing Paradigm:Scenarios and Security Issues,” Proc. 2014 Fed. Conf. Comput. Sci. Inf. Syst., vol. 2, pp. 1–8, 2014. • [3] B. Tang, Z. Chen, G. Hefferman, T. Wei, H. He, and Q. Yang, “A Hierarchical Distributed Fog Computing Architecture for Big Data Analysis in Smart Cities,” Proc. ASE BigData Soc. 2015, p. 28:1- 28:6, 2015. • [4] F. Bonomi, R. Milito, J. Zhu, and S. Addepalli, “Fog Computing and Its Role in the Internet of Things,” Proc. first Ed. MCC Work. Mob. cloud Comput., pp. 13–16, 2012. • [5] T. H. Luan, L. Gao, Z. Li, Y. Xiang, and L. Sun, “Fog Computing: Focusing on Mobile Users at the Edge,” eprint arXiv:1502.01815, pp. 1–11, 2015. • [6] S. J. Stolfo, M. Ben Salem, and A. D. Keromytis, “Fog computing: Mitigating insider data theft attacks in the cloud,” Proc. - IEEE CS Secur. Priv. Work. SPW 2012, pp. 125–128, 2012. • [7] S. M. Oriol, J. Jacob, and T. Dimitrakos, “Security Challenges in Cloud Computing,” Gerontologist, vol. 53, no. 2, p. NP, 2013. • [8] A. Kanuparthi, R. Karri, and S. Addepalli, “Hardware and embedded security in the context of internet of things,” Proc. 2013 ACM Work. Secur. Priv. dependability cyber Veh. - CyCAR ’13, pp. 61–64, 2013. • [9] K. Lee, D. Kim, D. Ha, U. Rajput, and H. Oh, “On Security and Privacy Issues of Fog Computing supported Internet of Things Environment.” • 10] B. P. Panciatici, G. Bareux, and L. Wehenkel, “Security Management Under Uncertainty,” no. october, 2012. • [11] W. Wang and Z. Lu, “Cyber security in the Smart Grid: Survey and challenges,” Comput. Networks, vol. 57, no. 5, pp. 1344–1371, 2013. • [12] A. Volokyta, I. Kokhanevych, and D. Ivanov, “Secure virtualization in cloud computing,” 11th Int. Conf. Mod. Probl. Radio Eng. Telecommun. Comput. Sci., p. 395, 2012. • [13] P. V. Madhwai and 1D. C. Saste, “FOG COMPUTING : Comprehensive Approach For Avoiding Data Theft Attack Using,” vol. 3, no. 3, pp. 3132–3139, 2015. • [14] C. Dsouza, G. J. Ahn, and M. Taguinod, “Policy-driven security management for fog computing: Preliminary framework and a casestudy,” Proc. 2014 IEEE 15th Int. Conf. Inf. Reuse Integr. IEEE IRI 2014, pp. 16–23, 2014. • [15] P. Kumar, N. Zaidi, and T. Choudhur, “Fog Computing : Common • Security Issues and Proposed Countermeasures,” pp. 311–315, 2016. • [16] C. Chen, H. Raj, S. Saroiu, I. Nsdi, and A. Wolman, “cTPM : A Cloud TPM for Cross-Device Trusted Applications,” 11th USENIX Conf. Networked Syst. Des. Implement., vol. 8, pp. 187–201, 2014. • [17] R. Lu, K. Heung, A. Lashkari, and A. Ghorbani, “A Lightweight Privacy-Preserving Data Aggregation Scheme for Fog Computing- Enhanced IoT,” IEEE Access, vol. 5, pp. 1–1, 2017. • [18] Z. Qin, S. Yi, Q. Li, and D. Zamkov, “Preserving secondary users’ privacy in cognitive radio networks,” Proc. - IEEE INFOCOM, pp. 772–780, 2014.