Learn how AI-powered anomaly detection techniques like real-time monitoring and alerts can significantly boost the security of software systems by identifying suspicious activities.
Table of Contents
Question
How can Al-based anomaly detection techniques be used in software engineering to increase system security?
A. By automatically fixing all security vulnerabilities in the code
B. By conducting real-time monitoring and alerting for suspicious activities
C. By encrypting all data transmissions within the software
D. By implementing strict access control policies for user authentication
Answer
B. By conducting real-time monitoring and alerting for suspicious activities
Explanation
AI-based anomaly detection techniques can substantially improve software system security by continuously monitoring the system in real-time and alerting security teams of any unusual or potentially malicious activities. These AI algorithms are trained on large datasets of normal system behavior, enabling them to recognize patterns that deviate from the norm which may indicate a security threat.
Some key benefits of using AI anomaly detection for software security include:
- 24/7 Vigilance: AI monitoring operates continuously, analyzing system logs, network traffic, user actions and other data sources to detect anomalies as soon as they occur. This allows security issues to be identified and responded to much faster than periodic manual checks.
- Recognizing Novel Threats: While traditional signature-based security tools can only detect known attack patterns, AI anomaly detection can spot never-before-seen suspicious behaviors that could represent zero-day exploits or insider threats. This helps protect against emerging attack vectors.
- Scalability: As software systems grow in size and complexity, AI tools can still effectively monitor the expanded attack surface without getting overwhelmed like human analysts would. The AI scales to handle big data from many disparate sources.
- Reducing Alert Fatigue: By learning over time what is and isn’t a real security issue, AI anomaly detection generates more reliable, high-priority alerts. This minimizes alert fatigue for security teams so they can focus on investigating and responding to true threats.
In summary, AI-powered real-time anomaly detection and alerting is a robust technique for bolstering the security of software systems against both known and novel threats, enabling faster and more effective responses to suspicious activities. The other answer options, while relevant security practices, do not represent core applications of AI anomaly detection in software engineering.
Infosys Certified Applied Generative AI Professional certification exam assessment practice question and answer (Q&A) dump including multiple choice questions (MCQ) and objective type questions, with detail explanation and reference available free, helpful to pass the Infosys Certified Applied Generative AI Professional exam and earn Infosys Certified Applied Generative AI Professional certification.