This comprehensive study investigates the trends, impacts, and global distribution of major Distributed Denial of Service (DDoS) attacks from 2019 to 2023, aiming to understand their evolution and predict future trends. Over the past five years, we have observed a significant escalation in both the frequency and severity of major cybersecurity incidents associated with DDoS attacks, underscoring their evolution from sporadic disruptions to more persistent and globally distributed threats. This study meticulously analyzes data from major incidents reported by reputable institutions, providing a focused insight into impactful cyberattacks. This approach highlights the increasing sophistication of threat actors and the expanding scope of targets, including critical national infrastructures and key economic sectors. The impact analysis reveals that these attacks not only cause immediate operational disruptions but also lead to substantial economic and reputational damages, reflecting the growing dependency of modern societies on digital infrastructure. Additionally, this study explores the correlation between these cyberattacks and geopolitical tensions, suggesting their use as strategic tools in broader political and economic conflicts. To predict future trends, the study employs ARIMA and Exponential Smoothing State Space (ETS) models, offering a quantitative forecast for 2024-2026. These models provide valuable insights, although they also exhibit limitations due to the dynamic nature of cyber threats and technological advancements. The study, contributed by authors with over 40 years of combined experience in cybersecurity, underscores the need for adaptive and resilient cybersecurity strategies. It highlights the importance of continuous monitoring and evolving defense mechanisms to counter the unpredictable nature of DDoS attacks in an increasingly interconnected world.
CITATION STYLE
Falowo, O. I., & Abdo, J. B. (2024). 2019-2023 in Review: Projecting DDoS Threats With ARIMA and ETS Forecasting Techniques. IEEE Access, 12, 26759–26772. https://doi.org/10.1109/ACCESS.2024.3367240
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