The Importance of AI in Cybersecurity

A typical cyber-attack attempt is when adversaries or cybercriminals try to reach, modify, or harm a targeted computer device or network for malicious purposes. Systematic, intended and measured misuse of technology has the effect of influencing computer networks and systems to interrupt organizations and operations that rely on them.

Fremont, CA: The landscape of cybersecurity is evolving with the emergence of patterns and situations. Cybercrimes are a hazard to all sorts of companies, organizations, and customers and users who use them. Breaches are an economic burden on consumers. These costs include warning costs, audit costs, damage management, government sanctions, rapid investment in security clearance, and maintenance. According to the IBM report, these costs have risen by 12 percent over the last five years. And with personal data leaking to hundreds of thousands of people, each is potentially a new victim of fraud and other cybercrimes. In addition, public disclosure of a breach of data will result in a company's average share price dropping by 7.27 percent along with a low share value and underperformance growth that has become a reality for years to come.

A typical cyber-attack attempt is when adversaries or cybercriminals try to reach, modify, or harm a targeted computer device or network for malicious purposes. Systematic, intended and measured misuse of technology has the effect of influencing computer networks and systems to interrupt organizations and operations that rely on them.

However, innovations such as Artificial Intelligence and Machine Learning (ML) are also crucial new tools in the global battle against cybercrime. AI techniques will turn the current asymmetrical defense-versus-adversary balance in cybersecurity. The pace and accuracy of these advances may allow the systems to act independently, respond and defend at wire speed, and to detect open and covert adverse reactions and attacks. Also Machine learning-based applications using techniques such as statistical analysis, keyword matching, and anomaly detection can support this cause by detecting whether a given data packet varies sufficiently from the database of data packets used in the training dataset. AI systems can also be used in multi-factor authentication situations to provide users with entry. AI and ML are also an essential tool to combat cybercrimes. According to the survey, 61 percent of businesses state that they cannot detect infringement attempts today without the use of AI technologies.