ABSTRACT. Digital data theft poses a significant risk to an organisation's financial well-being. This situation can be addressed through dynamic encryption, which generates distinct ciphertexts for the same unique plaintext. In this study, we investigate cybersecurity strategies that they incorporate random noisy schemes and artificial intelligence, highlighting their potential benefits and challenges because these are our aims of research. A new approach to cybersecurity involves injecting noise into ciphertext, they are well known as random noisy strategies. These methodologies have shown to be effective in thwarting cyber threats. This research is future work of random noisy alternatives because it was observed that they have not experimented with the IDEA-128 encryption algorithm over ciphertext. It is not considered good for the organisations. In particular, those who have opted for the employment of IDEA-128 standard, taking into account that the random noisy strategies have revealed very promising results. This research is important because it builds on experiments that they have used artificial intelligence to inject noise into IDEA-encrypted ciphertext, offering organisations a new approach to enhance security. This work introduces the random noisy IDEA-128 strategy, as a novel dynamic data encryption method. We also compare its performance to four random noisy schemes based on DES, 3DES, AES-256, and GOST R 34.12-2015 algorithms because the experimental results have shown an increasing of the noisy injection performance on ciphertext. In conclusion, the novel alternatives that have been suggested here might be difficult for the strategies of cybercriminals to decrypt, and even for algorithms based on quantum computing.