Social Response and Management of Cybersecurity Incidents

Authors

  • Qiang Chen Sun Yat-sen University
  • Lun Wang Meta Platforms

DOI:

https://doi.org/10.5281/zenodo.12754425

ARK:

https://n2t.net/ark:/40704/AJSM.v2n4a08

Keywords:

Cybersecurity incidents, incident Response Planning, Cyber Threats, Cyber Resilience, Public Awareness, AI in Cybersecurity, Blockchain Security, Cyber Risk Management

Abstract

This paper explores the social response and management of cybersecurity incidents, emphasizing the importance of public awareness, robust policies, technological innovations, and collaboration. By examining the rise of cyber threats, the impact of cybersecurity incidents, and the role of public education and corporate responsibility, this study highlights the necessity of a comprehensive approach to cybersecurity. Furthermore, it discusses incident response planning, the function of Cybersecurity Incident Response Teams (CSIRTs), and the value of information sharing. Technological advancements such as Artificial Intelligence (AI), Machine Learning (ML), and blockchain are identified as key tools in enhancing cybersecurity defenses. The paper also addresses challenges such as the evolving threat landscape, skill shortages, and regulatory complexities, providing insights into future directions for improving global cybersecurity resilience. Through continuous effort, adaptation, and innovation, it is possible to build a safer digital future and mitigate the risks associated with cyber threats.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Author Biographies

Qiang Chen, Sun Yat-sen University

School of Space and Network at Sun Yat-sen University, Shenzhen.

Lun Wang, Meta Platforms

Electrical and computer engineering, Meta Platforms, USA.

References

Liu, T., Cai, Q., Xu, C., Zhou, Z., Ni, F., Qiao, Y., & Yang, T. (2024). Rumor Detection with a novel graph neural network approach. arXiv Preprint arXiv:2403. 16206.

Liu, T., Cai, Q., Xu, C., Zhou, Z., Xiong, J., Qiao, Y., & Yang, T. (2024). Image Captioning in news report scenario. arXiv Preprint arXiv:2403. 16209.

Xu, C., Qiao, Y., Zhou, Z., Ni, F., & Xiong, J. (2024a). Accelerating Semi-Asynchronous Federated Learning. arXiv Preprint arXiv:2402. 10991.

Zhou, J., Liang, Z., Fang, Y., & Zhou, Z. (2024). Exploring Public Response to ChatGPT with Sentiment Analysis and Knowledge Mapping. IEEE Access.

Zhou, Z., Xu, C., Qiao, Y., Xiong, J., & Yu, J. (2024). Enhancing Equipment Health Prediction with Enhanced SMOTE-KNN. Journal of Industrial Engineering and Applied Science, 2(2), 13–20.

Zhou, Z., Xu, C., Qiao, Y., Ni, F., & Xiong, J. (2024). An Analysis of the Application of Machine Learning in Network Security. Journal of Industrial Engineering and Applied Science, 2(2), 5–12.

Zhou, Z. (2024). ADVANCES IN ARTIFICIAL INTELLIGENCE-DRIVEN COMPUTER VISION: COMPARISON AND ANALYSIS OF SEVERAL VISUALIZATION TOOLS.

Xu, C., Qiao, Y., Zhou, Z., Ni, F., & Xiong, J. (2024b). Enhancing Convergence in Federated Learning: A Contribution-Aware Asynchronous Approach. Computer Life, 12(1), 1–4.

Wang, L., Xiao, W., & Ye, S. (2019). Dynamic Multi-label Learning with Multiple New Labels. Image and Graphics: 10th International Conference, ICIG 2019, Beijing, China, August 23--25, 2019, Proceedings, Part III 10, 421–431. Springer.

Wang, L., Fang, W., & Du, Y. (2024). Load Balancing Strategies in Heterogeneous Environments. Journal of Computer Technology and Applied Mathematics, 1(2), 10–18.

Wang, L. (2024). Low-Latency, High-Throughput Load Balancing Algorithms. Journal of Computer Technology and Applied Mathematics, 1(2), 1–9.

Smith, R. (2017). The WannaCry ransomware attack and its impact on global cybersecurity. *Journal of Information Security*, 11(3), 112-120.

Johnson, M. (2020). The SolarWinds cyber-espionage campaign: Lessons learned and future directions. *Cybersecurity Review*, 15(4), 305-318.

Cybersecurity Ventures. (2021). Cybercrime to cost the world $10.5 trillion annually by 2025. Retrieved from https://cybersecurityventures.com/

Ponemon Institute. (2020). Cost of a Data Breach Report 2020. Retrieved from https://www.ibm.com/security/data-breach

Federal Trade Commission. (2021). Identity Theft: A Recovery Plan.

Retrieved from https://www.identitytheft.gov/

Department of Homeland Security. (2020). National Cyber Security Awareness Month. Retrieved from https://www.dhs.gov/national-cyber-security-awareness-month

European Commission. (2018). The General Data Protection Regulation (GDPR). Retrieved from https://ec.europa.eu/info/law/law-topic/data-protection_en

Target Corporation. (2014). Improving security following the data breach. Retrieved from https://corporate.target.com/

National Institute of Standards and Technology. (2018). Computer Security Incident Handling Guide (SP 800-61 Rev. 2). Retrieved from https://csrc.nist.gov/publications/detail/sp/800-61/rev-2/final

Cybersecurity and Infrastructure Security Agency. (2020). United States Computer Emergency Readiness Team (US-CERT). Retrieved from https://www.cisa.gov/uscert/

Financial Services Information Sharing and Analysis Center. (2021). FS-ISAC Overview. Retrieved from https://www.fsisac.com/

Healthcare Information Sharing and Analysis Center. (2021). H-ISAC Overview. Retrieved from https://h-isac.org/

Darktrace. (2021). AI-Powered Cyber Defense. Retrieved from https://www.darktrace.com/

Guardtime. (2021). Blockchain for Cybersecurity. Retrieved from https://guardtime.com/

CyberCorps: Scholarship for Service. (2021). About the SFS Program. Retrieved from https://www.sfs.opm.gov/

Downloads

Published

2024-07-18

How to Cite

Chen, Q., & Wang, L. (2024). Social Response and Management of Cybersecurity Incidents. Academic Journal of Sociology and Management, 2(4), 49–56. https://doi.org/10.5281/zenodo.12754425

Issue

Section

Articles

ARK