Authenticating Signals Using Machine Learning
Aditya Anand, Aniket Khartade, Ankit Maurya, S.K. Moon · 2024
Signal authentication is an important frontier in the rapid evolution of digital security. This research explores the integration of machine learning and steganography techniques and highlights their important role in improving signal authentication. Machine learning algorithms enable the system to identify complex patterns in signals, making accurate identification possible. At the same time, steganography can hide authentication information in symbols, thus improving information integrity and confidentiality. This next article provides a review of the recent developments, classification and evaluation of various machine learning algorithms along with steganography techniques. It covers application areas such as cybersecurity, biometric authentication, and multimedia communications, showing successes and challenges. Topics such as counterterrorism, moral intervention and timely action were discussed during the discussions. By providing a perspective, this study informs researchers, practitioners and policy makers about the latest technology and how to build a future with powerful, flexible and safe lighting for the digital age.