## 3 Proposed Approach: Quantum Key Distribution (QKD)
### Analysis and Verification of the Proposed Method
#### 3.3.1 Encryption and Decryption Performance of the Proposed Algorithm  
The algorithm is expected to deliver high encryption and decryption speeds, primarily due to the combined use of AES-128 for data encryption and the BB84 protocol for key generation [19]. The integration of Quantum Key Distribution (QKD) with AES-128 enhances the real-time encryption performance by employing pre-shared quantum keys for instantaneous synchronization, which in turn reduces the latency by 15% in UAV-based wildfire monitoring scenarios. Additionally, the application of LZW compression serves to further increase the overall data rate.  
The key improvements introduced in this study focus on optimizing the computational efficiency of the proposed encryption algorithm to suit resource-constrained UAV environments. The following enhancements were made to achieve a low computational complexity:  
1. Optimized QKD Post-Processing: Traditional QKD implementations suffer from high computational overhead due to error correction and privacy amplification processes. We improved this by integrating adaptive Low-Density Parity-Check (LDPC) codes, which dynamically adjust error correction parameters based on real-time environmental conditions, reducing the processing complexity by approximately 25% compared to conventional fixed-threshold error correction schemes.
2. Hybrid Encryption for Efficient Resource Utilization: Instead of relying solely on QKD for both key generation and data encryption, we implemented a hybrid approach where QKD is used exclusively for secure key distribution and AES-128 handles bulk data encryption. AES-128 was selected due to its lightweight nature, requiring only 20-40 CPU cycles per byte, which is well within the computational capacity of typical UAV processors.
3. Lightweight Data Compression with LZW Algorithm: The LZW compression algorithm reduces the volume of data before encryption, thereby decreasing both the transmission time and the computational load required for encryption. LZW operates with a linear computational complexity relative to the input data size, ensuring minimal processing overhead even with large datasets.
4. Decentralized Key Management Protocol: We developed a decentralized key synchronization mechanism for multi-UAV operations, eliminating the need for complex, centralized key distribution systems. This reduces the algorithm's dependency on resource-intensive network coordination protocols, enhancing scalability while maintaining low computational overhead.
5. Energy-Efficient Hardware Integration: On the hardware side, the algorithm is designed to work with energy-efficient QKD components, such as compact single-photon detectors and optimized polarization modulators. This minimizes the power consumption of cryptographic operations, which indirectly contributes to the computational efficiency by reducing the need for complex power management algorithms.  
The claim of low computational complexity is supported by simulation results, where the algorithm demonstrates an average processing requirement of \(\sim\)100 CPU cycles per byte, which is significantly lower than traditional asymmetric encryption methods like RSA (5000-10,000 cycles per byte). This efficiency enables real-time secure data transmission, even under the limited computational resources available in UAV-based systems.