2019–2023 in Review: Projecting DDoS Threats With ARIMA and ETS Forecasting Techniques

Falowo, Olufunsho I.; Abdo, Jacques Bou

doi:10.1109/access.2024.3367240

IEEE Access

2024

DOI: 10.1109/access.2024.3367240

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2019–2023 in Review: Projecting DDoS Threats With ARIMA and ETS Forecasting Techniques

Olufunsho I. Falowo,

Jacques Bou Abdo

Abstract: The data used or referenced in this study is derived from the Significant Cyber Incidents report that is consolidated by the Center for Strategic & International Studies but cross-referenced and validated with insights from Data Breach Investigation Reports.

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Cited by 2 publications

References 65 publications

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Enhancing Cybersecurity With Artificial Immune Systems and General Intelligence: A New Frontier in Threat Detection and Response

Falowo,

Edinam Botsyoe,

Koshoedo

et al. 2024

IEEE Access

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Enhancing Cybersecurity With Artificial Immune Systems and General Intelligence: A New Frontier in Threat Detection and Response

Falowo,

Edinam Botsyoe,

Koshoedo

et al. 2024

IEEE Access

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A DDoS Tracking Scheme Utilizing Adaptive Beam Search with Unmanned Aerial Vehicles in Smart Grid

Guo,

Zhang,

Chang

et al. 2024

Drones

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As IoT technology advances, the smart grid (SG) has become crucial to industrial infrastructure. However, SG faces security challenges, particularly from distributed denial of service (DDoS) attacks, due to inadequate security mechanisms for IoT devices. Moreover, the extensive deployment of SG exposes communication links to attacks, potentially disrupting communications and power supply. Link flooding attacks (LFAs) targeting congested backbone links have increasingly become a focal point of DDoS attacks. To address LFAs, we propose integrating unmanned aerial vehicles (UAVs) into the Smart Grid (SG) to offer a three-dimensional defense perspective. This strategy includes enhancing the speed and accuracy of attack path tracking as well as alleviating communication congestion. Therefore, our new DDoS tracking scheme leverages UAV mobility and employs beam search with adaptive beam width to reconstruct attack paths and pinpoint attack sources. This scheme features a threshold iterative update mechanism that refines the threshold each round based on prior results, improving attack path reconstruction accuracy. An adaptive beam width method evaluates the number of abnormal nodes based on the current threshold, enabling precise tracking of multiple attack paths and enhancing scheme automation. Additionally, our path-checking and merging method optimizes path reconstruction by merging overlapping paths and excluding previously searched nodes, thus avoiding redundant searches and infinite loops. Simulation results on the Keysight Ixia platform demonstrate a 98.89% attack path coverage with a minimal error tracking rate of 2.05%. Furthermore, simulations on the NS-3 platform show that drone integration not only bolsters security but also significantly enhances network performance, with communication effectiveness improving by 88.05% and recovering to 82.70% of normal levels under attack conditions.

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2019–2023 in Review: Projecting DDoS Threats With ARIMA and ETS Forecasting Techniques

Abstract: The data used or referenced in this study is derived from the Significant Cyber Incidents report that is consolidated by the Center for Strategic & International Studies but cross-referenced and validated with insights from Data Breach Investigation Reports.

Cited by 2 publications

References 65 publications

Enhancing Cybersecurity With Artificial Immune Systems and General Intelligence: A New Frontier in Threat Detection and Response

Enhancing Cybersecurity With Artificial Immune Systems and General Intelligence: A New Frontier in Threat Detection and Response

A DDoS Tracking Scheme Utilizing Adaptive Beam Search with Unmanned Aerial Vehicles in Smart Grid

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