Multi-Channel Power Scheduling Based on Intrusion Detection System Under DDoS Attack: A Starkberg Game Approach

Area of Science:

• Wireless Communication Networks
• Cybersecurity
• Optimization Theory

Background:

• Distributed Denial of Service (DDoS) attacks pose significant threats to wireless communication network availability.
• Existing defense mechanisms often lack optimal power allocation strategies under incomplete information and energy constraints.
• Strategic interactions between network defenders and attackers require sophisticated analytical frameworks.

Purpose of the Study:

• To investigate the optimal power allocation problem in wireless networks under DDoS attacks.
• To develop an effective Intrusion Detection System (IDS) for enhanced defense strategies.
• To derive optimal power allocation solutions considering energy constraints and strategic interactions.

Main Methods:

• Employed the Starkberg Equilibrium (SE) framework to model strategic interactions under incomplete information.
• Proposed an Intrusion Detection System (IDS) based on remote estimation, using Packet Reception Rate (PPR) for intrusion detection.
• Utilized the Adaptive Penalty Function (APF) method combined with the Differential Evolution (DE) algorithm to solve non-linear, non-convex optimization problems.
• Derived optimal power allocation solutions targeting leaders and followers, optimizing Signal-to-Interference-Noise Ratio (SINR) and transmission cost.

Main Results:

• The study successfully derived optimal power allocation strategies for wireless networks under DDoS attack scenarios.
• The proposed IDS effectively identified intrusions using Packet Reception Rate (PPR) as a key metric.
• The combination of APF and DE algorithms proved effective in solving complex, non-linear optimization problems related to power allocation.
• Case studies validated the effectiveness of the proposed defense and power allocation methods.

Conclusions:

• The developed optimal power allocation strategy enhances wireless network resilience against DDoS attacks.
• The proposed IDS offers a robust solution for detecting intrusions in energy-constrained wireless networks.
• The integration of game theory and advanced optimization algorithms provides a powerful approach to cybersecurity challenges in wireless communications.