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Does AI Improve or Worsen Cybersecurity

 AI and cybersecurity

Artificial Intelligence's (AI) role is becoming increasingly important in cybersecurity with rapid advancements. Today, organizations can utilize emerging AI-based cybersecurity tools to detect threats, understand patterns, and protect their infrastructures. At the same time, cybercriminals are also leveraging on AI-based tools to carry out more sophisticated attacks. However, the growing number of cyberattacks is also fueling AI advancements in cybersecurity, as the global AI cybersecurity products market is estimated to become $133.8 billion by 2030, compared to $14.9 billion in 2021. So, let's explore in detail how the advancements in AI are improving or worsening cybersecurity.

Advancements in AI Improving Cybersecurity

Although AI has been on the boom over the past few years, its use in cybersecurity is still limited. Organizations are seen utilizing AI in a limited fashion. Today, AI plays more of a role in pattern detection to reduce false positives and detect attacks more accurately. Some of the areas where the advancements of AI are improving cybersecurity are as follows:

  • Detection: One of the most common uses of AI in cybersecurity is to detect cyber threats. In fact, Capgemini reports 50% of organizations that deploy AI cybersecurity solutions mainly for detection purposes. AI algorithms are capable of scanning several data sets, including logs, network traffic, and other events, that help identify suspicious behavior and threat patterns.
  • Vulnerability Scanning: AI-based cybersecurity solutions are being used for vulnerability scanning, which helps identify weaknesses in the security infrastructure. AI solutions can continuously scan for vulnerabilities and loopholes in real-time, thereby letting cybersecurity teams react to weaknesses timely before cybercriminals.
  • Threat Responses: Other than assisting in predicting and detecting cyber threats, AI is also evolving into an automated threat response solution. Organizations can now deploy AI cybersecurity solutions to detect and stop attacks autonomously. This way, it helps organizations improve threat response time and lower costs.

Other than the above three main areas, AI is improving cybersecurity posture in many other ways, such as user behavior analysis to identify unusual activities, malware detection by analyzing code patterns and behavior, etc. Besides that, many AI-powered cybersecurity applications have started assisting organizations, such as IBM Watson, Darktrace, Amazon GuardDuty, etc. Overall, although the role of AI in cybersecurity is heading at a slower pace than it should, advancements in AI are uplifting the cybersecurity framework of organizations.

Adoption Challenges of AI in Cybersecurity

Despite the benefits of AI in cybersecurity, adopting AI is a lot challenging for organizations due to many complications, as follows:

  1. AI is expensive and requires significant capital and time in computing power, data centers, and memory to run AI systems.
  2. AI is difficult to implement and integrate into existing cybersecurity infrastructure.
  3. Shortage of talent.
  4. Lack of proper AI tools.
  5. Data complexity.
  6. AI can generate false positives.
  7. AI algorithms are complex, making understanding how they work complicated in some cases.

In short, advancements in AI have the potential to improve cybersecurity, but it also comes with many adoption challenges that organizations have to tackle to utilize the potential of AI to the maximum.

Advancements in AI Worsening Cybersecurity

Advancements in AI are also getting equal attention from cybercriminals. They are actively seeking and developing new tools and techniques to deploy more sophisticated AI cyber-attacks. Some of the ways cybercriminals can deploy AI are as follows:

  • Social Engineering: AI algorithms are capable of analyzing large data sets of individuals, such as personal information, social media activities, browsing habits, etc. This helps cybercriminals set up highly personalized and convincing social engineering scams.
  • Malware: AI algorithms can help cybercriminals create more sophisticated malware to bypass existing security defenses.
  • Identity Theft and Impersonation Fraud: AI is becoming a powerful generator of synthetic audio, images, text, etc. The growing buzz around deepfakes is a clear example. Owing to that, there is a growing threat of more involvement of AI in identity theft and impersonation fraud.
  • DDoS Attacks: AI empowers cybercriminals to analyze traffic patterns and look for vulnerabilities. This helps them conduct more targeted and effective DDoS attacks that can even bring down highly secure websites and networks.
  • Automated Attacks: AI can also facilitate cybercriminals to automate their attacks, which helps them carry attacks much faster and on a larger scale.

In short, cybercriminals are actively exploiting advancements in AI to test new methodologies and conduct more effective and sophisticated attacks.

Wrapping Up – AI is a Double-Edged Sword

With the ongoing advancements in AI, it is clear that AI is a double-edged sword. As per McKinsey, cyber-attacks are going to expedite leveraging AI, ML, and automation in the coming years. Similarly, organizations will also leverage similar AI techniques to deal with those attacks, such as more automatic responses to attacks. To sum up, advancements in AI are both improving and worsening the cybersecurity landscape.

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