Cybersecurity and AI, A better team?

What Is AI? And NO, it’s not Robots.

Artificial intelligence (AI) is a set of technologies that enable computers to perform many improved functions like reasoning, making decisions, or solving problems etc.

AI has played a very crucial role in the innovation of modern-day computing. AI in simple words is computer systems that are capable of performing complex tasks that historically only humans could do, such as the ability to see, understand, analyze, make recommendations, and more. It mirrors human intelligence, along with having computational power.

Why should AI be integrated with Security?

As technology is increasing at its peak, people, businesses, organizations, government, and everybody is concerned about security. Combining AI with cybersecurity in the right way will help us conquer digital threats and secure our data.

Where AI is more than capable of detecting cyber threats, vulnerabilities, and attacks more quickly and efficiently if trained for cybersecurity. Right now, AI is already used in automated threat detection, response and protection, resulting in a stronger robust security infrastructure.

Use of AI in cyber:

AI plays an important role in enhancing cybersecurity. Here are some key aspects:

1. Threat Detection: AI-powered systems can analyse vast amounts of data faster, helping in the identification of patterns and irregularities that might be an indication of a potential threat or attack. It facilitates early detection of emerging threats, which also include unseen threats and sophisticated attacks.
2. Automated Response: AI systems automatically respond to the detected threats, which reduces the time it takes to enclose, contain and mitigate incident attacks. This minimizes the attack surface and prevents further damage.
3. Network Efficiency: AI enhances network performance and can be used in detecting and blocking suspicious traffic and prioritizing critical network segments.
4. Vulnerability Detection: AI-powered tools identify vulnerabilities in systems, applications, and networks, much quicker enabling proactive remediation and reducing the attack surface.

5. Incident Response: AI-assisted incident response teams are able to provide contextual information about threats, enabling more effective and efficient response.

6. Predictive Analytics: AI analysis historical data and previous repetitive trends to predict potential threats, allowing organizations to proactively prepare and respond.

7. Anomaly Detection: AI can identify unusual behaviour in systems, networks, and applications, detecting potential threats before they are set up and intensified.

8. Ethical Considerations: When using AI in cybersecurity, requires cautious consideration of ethical principles to ensure responsible use and avoid unintended consequences, such as privacy breaches.

9. Integration with Human Teams: AI supplements human cybersecurity teams, freeing them to focus on high-priority tasks, such as strategic planning, threat hunting, and incident response.

10. Continuous Learning: AI systems learn from the previous data and adapt to new threats, ensuring that cybersecurity defenses remain effective and up to date.

Ultimately, AI enhances threat detection, response, and prevention, while also optimizing network efficiency, vulnerability detection, and incident response. However, it is essential to consider ethical principles and integrate AI with human teams to ensure effective and responsible use.

Benefits of AI in Security:

• Improved threat detection and response times
• Enhanced accuracy and reduced false positives
• Increased efficiency and productivity for security teams
• Proactive identification and mitigation of vulnerabilities
• Better resource allocation and prioritization
• Improved incident response and containment
• Reduced risk of data breaches and cyber attacks

Challenges Faced:

• Ensuring AI systems are properly trained and updated
• Addressing potential biases and inaccuracies in AI models
• Integrating AI with existing security infrastructure and processes
• Ensuring transparency and explainability of AI-driven decisions
• Managing the complexity and scale of AI-powered security systems

By the influence of AI in cybersecurity, organizations can strengthen their defenses, improve incident response, and reduce the risk of successful attacks.

AI in security, a PRO or CON?

While AI integrated security models may be faster and more efficient, it has major drawbacks as summarized:

• Malicious AI (Adversarial AI): AI can be used by criminals or hackers to make small changes to a network environment, which could lead to compromise in the behavior of AIML-based cybersecurity systems over time.
• Resource Constraints: AI-powered systems require significant computational resources, and if those system’s finite resources are not sufficient, it can compromise their intelligence and accuracy of the system.
• Privacy Concerns: AI technology may need to be outsourced to third-party vendors, raising concerns about data confidentiality and control.
• Lack of Customization: AI integrated security systems may not be adaptable to unique organizational needs, which can leave loopholes in security.
• Human faults: because of AI’s benefits, may lead to neglect of human expertise and oversight, just blindly over-emphasizing technology, creating cybersecurity concerns.
• Limited Real-Time Response: While AI can detect anomalies, it may not be able to respond quickly enough to contain emerging threats, requiring human intervention.

Written By: Nandni Joshi