Final Exam: Enhancing Enterprise Security with Generative AI and AI
Final Exam: Enhancing Enterprise Security with Generative AI and AI will test your knowledge and application of the topics presented throughout the Enhancing Enterprise Security with Generative AI and AI journey.
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Final Exam: Enhancing Enterprise Security with Generative AI and AI
Recognize the growing role artificial intelligence (AI) is playing in cybersecurity
identify ethical considerations when employing AI in cybersecurity
formulate strategies for integrating AI into existing cybersecurity frameworks
outline the role of AI in enhancing various aspects of cybersecurity, such as threat detection and prevention
Classify the types of threats that AI and generative AI can help mitigate
Outline a basic plan for implementing AI in a hypothetical cybersecurity scenario
Use various prompts to get answers in HuggingChat
Use AI to enhance an existing security tool or process
List commonly used tools in cybersecurity and their primary functions
Troubleshoot common issues in AI-enhanced security tools
Compare AI-enhanced security tools to a traditional one handling the same threat
Interpret the output of a generative AI model in a security scenario
Integrate a simple AI model with a common security tool
Design a migration plan for transitioning from a traditional security tool to an AI-enhanced one
Formulate strategies for maintaining and updating AI-enhanced security tools
Outline potential challenges and solutions when integrating AI with existing security tools
classify various types of AI models suitable for different security tools and contexts
Identify strategies for integrating AI into existing identity security frameworks
Recognize ethical and privacy considerations relate to the use of AI for identity security
Describe how generative AI can have a real-world impact on many industries
Predict future trends in AI-powered identity security based on current industry advancements
Compare AI-powered and traditional identity verification methods in action
Outline the potential of AI in preventing identity theft and other related security threats
Use AI to detect potential identity threats
Outline how to use AI for identity verification
discuss how AI email security can help reduce administrative efforts and strengthen an organizations security posture
outline various AI approaches suitable for enhancing email security
demonstrate how an AI model can detect spam and phishing emails and enhance predictive capabilities
discuss challenges and risks associated with an ever evolving email threat landscape
exhibit a comparison of AI-powered and traditional email security measures in action
list common benefits when automating email security including greater cost savings and cyber resilience
discuss the privacy implications and potential drawbacks of using AI for email security
list common email threats to organizations including URL phishing, spear phishing, brand impersonation, malware, and spam
show how to ensure AI data model integrity
formulate strategies for integrating AI into existing data protection and validation frameworks
discuss ethical considerations and potential bias when using AI for user data protection
analyze the potential benefits and risks of leveraging AI for user data protection and validation
provide an overview of data protection and validation
exhibit a comparison of AI-powered and traditional methods of user data protection in action
describe how to protect sensitive data and AI models
discuss factors when designing AI with data privacy
identify key areas where AI can enhance user data protection and validation
differentiate between data protection and data privacy
list common authentication vulnerabilities including SQL injection, username enumeration, and weak login credentials
describe AI's role in authentication
outline how adaptive authentication can be used to verify user identity
provide an overview of behavioral biometrics and how it can analyze a user’s digital physical and cognitive behavior to determine threats
outline how continuous authentication assesses user behavior patterns on an ongoing basis to identify potential risk factors
describe how AI authentication systems can help mitigate AI bias
outline how speech recognition has become a significant part of AI applications
describe how anomaly detection can be used to identify unusual or suspicious activity
discuss the three key roles AI plays in cybersecurity: prediction, detection, response
discuss challenges of AI-based intrusion detection
recognize how AI can detect and prevent security threats
differentiate between intrusion detection systems, vulnerability management systems, behavioral analytics, and security auditing systems
discuss concerns and possible future trends as they related to security threats
provide an overview of intrusion detection system (IDS)
differentiate between intrusion detection systems including network intrusion, network node, host intrusion, protocol based, and application protocol-based intrusion detection systems
describe intrusion detection system methods including signature-based intrusion, anomaly-based, and hybrid intrusion detection
list benefits of AI-based intrusion detection
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