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Computing systems that use AI and machine learning are becoming more common and important in cyber operations. They have become a major focus of cybersecurity research and development in both the public and private sectors.
FREMONT, CA: People now conduct more of their personal and professional lives online than ever before, making cybersecurity a critical issue of the time. Thus, understanding the future of cybersecurity will teach one how to make the most of the resources and stay secure today and tomorrow. Cybersecurity's future is difficult to predict because the market is constantly evolving in response to cybercriminals' shifting operations and new attacks. For example, the number of worldwide ransomware attacks jumped by nearly 25 percent between 2019 and 2020, prompting cybersecurity developers and companies to create new applications to combat the phenomenon.
Despite the difficulties, there is hope for reducing human dependency and strengthening cybersecurity capabilities. A wide range of emerging cognitive technologies can help us enhance cybersecurity and navigate the increasingly malicious and disruptive cyber threat landscape. They cover:
By giving hackers a new way to attack target organizations, Artificial Intelligence (AI) is changing the world of cybersecurity. Cybersecurity developers will use AI to address vulnerabilities, detect security problems before they can be exploited, and thwart cyberattacks once they have begun. Computing systems that use AI and machine learning are becoming more common and important in cyber operations. They have become a major focus of cybersecurity research and development in both the public and private sectors. Data discovery, categorization, and synthesizing are all benefits in combating cybersecurity threats.
In a broader sense, AI technologies can help defend against increasingly sophisticated and malicious malware, ransomware, and social engineering attacks. AI has the potential to become cognitively autonomous in the future by predicting and preventing cyber-attacks.
Machine Learning (ML) can help cybersecurity systems identify patterns and learn from them to help prevent repeat attacks and respond to changing behavior. It can help cybersecurity teams be more proactive in preventing threats and responding to active attacks in real-time. This would allow businesses to spend less time on repetitive tasks and focus their resources more strategically. In short, machine learning will make cybersecurity more accessible, proactive, cost-effective, and efficient. But it can only do so if the underlying data supporting machine learning provides a complete picture of the world.