The Cloud Security Revolution: Unlocking the Potential of AI and Machine Learning to Stay Ahead of Threats - Okereke, Ruth Onyekachi; Ojemerenvhie, Grace Alele; Azeez, Oladimeji Lamina; Oko-odion, Terry Uwagbae; Samson, Iyanu Opeyemi; Anosike, Chijioke Nnaemeka; Owan, Faith Obun; Nnamani, Chinenye Cordelia (Darul Yasin Al Sys, 2024)
As we navigate the digital world, cybersecurity has become a top priority. With each technological advancement, new vulnerabilities emerge, making robust defenses essential. The fusion of machine learning and artificial intelligence has become a game-changer in the fight against cyber threats. This paper delves into the latest applications of these technologies in network security, shedding light on their critical roles in addressing pressing concerns and identifying areas for further exploration. We also examine the ethical and legal implications of implementing these technologies. Our research highlights current challenges and open questions, with a focus on recent breakthroughs in network security leveraging AI and ML. The findings are promising, suggesting that further innovation in integrating AI and ML into network security frameworks holds significant potential. Exciting applications include bolstering network security, detecting malware, and responding to intrusions. Interestingly, while 45% of organizations recognize the need to adopt these technologies, half have already done so, while 5% remain hesitant.