A Review of Network Attacks and Security Solutions in a Networked Environment

Authors

  • O. D. Okeh Babcock University, Ilesia, Ogun State, Nigeria
  • O. F. Ajayi Babcock University, Ilesia, Ogun State, Nigeria
  • E. A. Emuobonuvie University of Delta, Agbor, Delta State, Nigeria
  • D. A. Ekokotu University of Delta, Agbor, Delta State, Nigeria

DOI:

https://doi.org/10.51983/ajeat-2023.12.2.3965

Keywords:

Network Security, Internet of Things (IoT), Cryptography, Firewall, Blockchain

Abstract

The advancement in technology has led to the interconnectivity of devices referred to as networking. Not only that computers are networked, but the technology also now incorporates all devices giving rise to Internet of Things (IoT). The wide range of connectivity calls for security and protection of data and information as malicious users of the internet have taken advantage of the system. In this paper, we reviewed most of the common threading types of network attack. The paper has x-rayed the different challenges accompanying a network and how they could be detected and handled accordingly. Moreso, the different types of attacks have been looked into with a view to understanding the emerging attacks and how they could be curbed as well. Different security solutions such as cryptography, firewall and blockchain technology were discussed. Obviously, while implementing these security strategies, we are aware that our data and information cannot be fully secured but measures can be put in place to minimize the extent of attack and damages.

References

S. Pandey, “Modern network security: Issues and challenges,” International Journal of Engineering Science and Technology, vol. 3, no. 5, pp. 4351-4357, 2011.

J. X. Wu, “Cyberspace endogenous safety and security,” Engineering, 2021, DOI: 10.1016/j.eng.2021.05.015.

J. X. Wu, Cyberspace Endogenous Safety and Security: Mimic Defense and General Robust Control (in Chinese). Beijing: Science Press, 2020.

L. Caviglione et al., “Tight arms race: Overview of current malware threats and trends in their detection,” IEEE Access, vol. 9, pp. 5371-5396, December 2020.

S. Bhattacharya et al., “A novel PCA-firefly based XGBoost classification model for intrusion detection in networks using GPU,” Electronics, vol. 2, no. 19, pp. 219, 2020.

K. T. Nguyen et al., “Survey on secure communication protocols for the internet of things,” Ad Hoc Netw., 2015.

M. Alazab et al., “Malicious spam emails developments and authorship attribution,” in 2013 Fourth Cybercrime and Trustworthy Computing Workshop, IEEE, pp. 58-68, 2013.

R. Rammanohardas, “Artificial Intelligence in Cyber Security,” Journal of Physics, Conference on Artificial Intelligence and modern applications, 240-ECS Meeting, 2021.

K. D. B. Utama et al., “Digital signature using MAC address based AES-128 and SHA-2 256-bit,” in Proc. 2017 International Seminar on Application for Technology of Information and Communication (iSemantic), Indonesia, pp. 72-78, 2017.

Md. Shafiur Rahman et al., “An Efficient Hybrid System for Anomaly Detection in Social Networks,” Springer, vol. 4, DOI: https://doi.org/10.1186/s42400-021-00074-w, 2021.

S. Namasudra, “Fast and secure data accessing by using DNA computing for the cloud environment,” IEEE Transactions on Services Computing, 2020.

S. Kumari and S. Namasudra, “System reliability evaluation using budget-constrained real d-mc search,” Computer Communications, vol. 171, pp. 10-15, 2021.

S. Kumari et al., “Intelligent deception techniques against adversarial attack on the industrial system,” International Journal of Intelligent Systems, vol. 36, no. 5, pp. 2412-2437, 2021.

P. Pavithran et al., “A novel cryptosystem based on DNA cryptography and randomly generated Mealy machine,” Computers & Security, vol. 104, pp. 102160, 2021.

M. Humayun and M. Niazi, “Cyber Security Threats and Vulnerabilities: A Systematic Mapping Study,” Arabian Journal of Science & Engineering, DOI: 10.1007/s13369-019-04319-2, pp. 1245-1250, 2020.

Alex Mathew, “Machine Learning in Cyber-Security Threats,” International Conference on IoT Based Control Networks & Intelligent Systems, DPI: 10.2139/ssrn.3769194, 2020.

M. Coutinho et al., “Learning perfectly secure cryptography to protect communications with adversarial neural cryptography,” Sensors, vol. 18, no. 5, pp. 1306, 2018.

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Published

28-11-2023

How to Cite

Okeh, O. D., Ajayi, O. F., Emuobonuvie, E. A., & Ekokotu, D. A. (2023). A Review of Network Attacks and Security Solutions in a Networked Environment. Asian Journal of Engineering and Applied Technology, 12(2), 24–28. https://doi.org/10.51983/ajeat-2023.12.2.3965