The proliferation of sophisticated encryption techniques has meant the development of advanced detection mechanisms capable of distinguishing between legitimate and malicious activities. Traditional methods often struggle to keep pace with the rapid evolution of ransomware, leading to significant challenges in timely identification and mitigation. The Dynamic Encryption Signal Profiling (DESP) framework offers a novel approach to this issue, focusing on the real-time analysis of encryption patterns to detect ransomware activities. By capturing and analyzing encryption-related signals within data streams, DESP constructs dynamic profiles that effectively differentiate between benign and malicious behaviors. Comprehensive evaluations demonstrate that DESP achieves high detection accuracy across various ransomware strains, including CryptoLocker, TeslaCrypt, and Jigsaw, with minimal false positive rates. The framework's low detection latency and efficient resource utilization further demonstrate its suitability for deployment in diverse operational environments. Comparative analyses reveal that DESP outperforms existing detection methods, particularly in adapting to new ransomware variants employing advanced evasion techniques. These findings highlight the potential of DESP to enhance current cybersecurity defenses, providing a proactive and effective solution to the growing threat of ransomware attacks.