## 3 Proposed Approach: Quantum Key Distribution (QKD)
### Analysis and Verification of the Proposed Method
#### 3.3.2 Security Analysis: Resistance to Cyber Attacks
However, the minor 0.5% gap--observed under specific conditions involving timing and network jitter--indicates that even slight vulnerabilities must be addressed to ensure absolute security in sensitive environments. Data forgery detection was tested by introducing subtle modifications into 3000 of the 10,000 messages. The system successfully identified 97% of these forgeries, though the 3% of missed instances points to the need for more advanced anomaly detection techniques. Similarly, Denial-of-Service (DoS) resilience was assessed by overwhelming the network with illegitimate traffic. The system maintained functionality in 9600 out of 10,000 legitimate requests, reflecting a robust 96% resilience, with performance degradation suggesting that the further optimization of load balancing and resource management could be beneficial. Multi-vector attack scenarios, where attackers simultaneously employed MITM, data forgery, and DoS techniques, demonstrated that the hybrid approach maintained an overall effectiveness between 92% and 95% across all metrics. Stress testing under a simulated 50% increase in the network load confirmed that the system's performance remained consistent, with deviations within \(\pm\)1-2% of the baseline measurements. This consistency under an increased load reinforces the system's scalability and its ability to operate effectively in high-traffic environments. In conclusion, the empirical validation confirms that the hybrid security approach is highly effective: QKD delivers 98% resistance to data interception, AES-128 provides a 99% encryption strength, and MITM attack prevention achieves 99.5% accuracy. The system also demonstrates robust data forgery detection (97%) and DoS resilience (96%). These results underscore the strength of a layered defense strategy, while the minor vulnerabilities observed highlight opportunities for further optimization and adaptation, especially as emerging cyber threats and quantum computing advancements continue to evolve. 6. Resistance to Specific Attack Vectors. The proposed encryption framework exhibits robust protection against a variety of cyber threats. It addresses the following attack vectors:  
* Brute-Force Attacks: Quantum Key Distribution (QKD) confers information-theoretic security, thereby rendering the system resistant to brute-force attacks--even in the context of adversaries equipped with quantum computing capabilities. * Side-Channel Attacks: By implementing QKD at the hardware level, the approach significantly mitigates the risk of side-channel attacks, particularly those stemming from information leakage through power consumption or variations in the computation time. * Data Interception and Manipulation: The utilization of the BB84 protocol enables the detection of any attempts to intercept or alter the quantum states used for key transmission, thus protecting against data interception and manipulation. It is noteworthy that factors such as the receiver noise and environmental conditions--specifically fog and aerosol density--can elevate quantum channel error rates by up to 30%, necessitating the deployment of enhanced reconciliation processes [20]. Experimental refinements in photon polarization alignment have effectively countered these adverse effects, thereby recovering approximately 80% of the communication range. Figure 8 delineates the entire process--from data acquisition, compression, and encryption, to QKD-based key exchange and secure transmission--demonstrating the practical application of this framework in secure data transfer for UAVs. 7. Comparative Analysis of Encryption Methods. The proposed hybrid approach offers several advantages over traditional encryption schemes. Its decentralized key management system eliminates the reliance on centralized Public Key Infrastructure (PKI), enabling secure key exchanges among multiple UAVs without external key authorities. The implementation of LZW compression optimizes bandwidth utilization by reducing the data volume before encryption.