SECURING DATA TRANSMISSION: PREDICTIVE AI MODEL FOR CYBERSECURITY APPLICATIONS
Keywords:
Artificial Intelligence (AI), Cybersecurity, Artificial Neural Networks (ANNS)Abstract
Artificial intelligence (AI) is a game-changer in the field of cybersecurity. It gives enterprises a powerful toolkit to strengthen their digital defenses against a constantly changing range of threats. AI enables cybersecurity teams to quickly detect and respond to attacks, automate repetitive activities, and protect the integrity of data transactions. It does this by utilizing machine learning algorithms and advanced analytics. Cybersecurity teams may proactively mitigate risks when cyberattacks become more complicated and persistent by utilizing AI-driven solutions to spot aberrant patterns and possible breaches in real time. AI also has the potential to automate increasingly repetitive activities, freeing up human analysts to work on more strategic projects. The hybrid encryption in combining asymmetric and symmetric encryption for secure data transmission and storage. The benefits of symmetric encryption for secure key exchange and asymmetric encryption for effective data encryption are combined in this method. Artificial neural networks (ANNs) combined with hybrid encryption can offer a safe and effective method for protecting privacy while analyzing sensitive data and predict the threats. Applications like private-preserving machine learning, safe multiparty computations, and secure data analysis can all benefit from this integration. The outcome of this research is to identify threats more quickly and accurately than by humans and to Block suspicious activity automatically to avoid attacks.
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