# Secure Cryptographic Key Encapsulation and Recovery Scheme in Noisy Network Conditions
## 8 Future Work  
Building on the findings of this work, we will focus on two key areas to further develop and refine the error correction system. First, we will improve its integration with biometric cryptosystems by implementing adaptive techniques to counteract environmental noise and template variability, ensuring more reliable key recovery. Second, we will improve its application in noise-resistant key exchange mechanisms by analyzing its performance under various error models and jamming conditions.  
Biometric responses, in particular, are subject to relatively high amounts of response noise compared to items more consistent such as a memory PUF, to the point that brute-force keyspace search algorithms like RBC cannot feasibly correct enough key error tobe useful in a biometric application. Whereas an RBC approach can correct four-to-six bit errors in a key recovery process, our new system is capable of correcting up to 20 or 25 bit errors promptly, rendering our system an ideal choice for a templateless biometry application. To empirically evaluate the efficacy of this protocol, we plan to test it using a variety of front-facing face image databases, including a large set of faces purpose-generated by Artificial Intelligence (AI), which contains a great deal of diversity across age, gender, and ethnicity. Due to the uniqueness of facial images generated through AI, this dataset is optimal for testing this key recovery protocol to its limit. For instance, as the images will have variations, i.e., an individual gaining weight and/or changing facial hair over a period of time, it will create an impact on regenerating the right key during the authentication phase to match it with enrollment, which will have been taken before this transformation has occurred. Also, lighting conditions have an impact on landmark placing technology, as they are sensitive and would result in error bits in the recovered key. For this, we need a robust key recovery scheme that will operate efficiently in a noisy environment. The source of this noise can be any factor, and the protocol should withstand all sorts of situations. These circumstances show the effectiveness and importance of noisy key recovery protocol in the field of templateless biometry, where most of the current research is focused, as it enables biometric authentication without retaining any biometric information of an individual.  
The ability to withstand significant response noise is crucial in the design of response-based key exchange systems that are robust against substantial signal corruption, such as poor signal reception or the presence of military jamming. By applying this technology to systems that conduct ephemeral key recoveries from hash-based challenge-response mechanisms, the performance of these systems can be significantly enhanced, surpassing their conventional capabilities. To rigorously evaluate the resilience of this approach, we plan to conduct both simulated and physical tests on rovers or drones configured to operate using the hash-based challenge-response system. These tests will be designed to assess how these systems will perform under actual (realized) conditions. This empirical testing will provide valuable insights into the systems' robustness and their ability to maintain operational integrity in environments with high levels of signal interference.