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Big Data Analytics Security and Privacy

This quiz covers the fundamentals of Big Data Analytics Security and Privacy, including data protection, access control, and privacy regulations.

15 Questions Published
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Questions

Question 1 Multiple Choice (Single Answer)

What is the primary goal of Big Data Analytics Security?

  1. To ensure the confidentiality, integrity, and availability of big data.
  2. To improve the performance and efficiency of big data analytics systems.
  3. To reduce the cost of big data storage and processing.
  4. To facilitate the sharing and collaboration of big data among different stakeholders.
Question 2 Multiple Choice (Single Answer)

Which of the following is NOT a common type of Big Data Analytics Security threat?

  1. Data breaches
  2. Malware attacks
  3. Denial-of-service attacks
  4. Data manipulation
Question 3 Multiple Choice (Single Answer)

What is the purpose of access control in Big Data Analytics Security?

  1. To restrict access to big data based on user roles and permissions.
  2. To encrypt big data at rest and in transit.
  3. To detect and respond to security incidents in real time.
  4. To ensure the integrity and authenticity of big data.
Question 4 Multiple Choice (Single Answer)

Which of the following is NOT a common type of access control mechanism used in Big Data Analytics Security?

  1. Role-based access control (RBAC)
  2. Attribute-based access control (ABAC)
  3. Discretionary access control (DAC)
  4. Mandatory access control (MAC)
Question 5 Multiple Choice (Single Answer)

What is the purpose of data encryption in Big Data Analytics Security?

  1. To protect big data from unauthorized access.
  2. To ensure the integrity and authenticity of big data.
  3. To improve the performance and efficiency of big data analytics systems.
  4. To facilitate the sharing and collaboration of big data among different stakeholders.
Question 6 Multiple Choice (Single Answer)

Which of the following is NOT a common type of data encryption algorithm used in Big Data Analytics Security?

  1. Advanced Encryption Standard (AES)
  2. Triple DES (3DES)
  3. RSA
  4. Blowfish
Question 7 Multiple Choice (Single Answer)

What is the purpose of data masking in Big Data Analytics Security?

  1. To protect sensitive data from unauthorized access.
  2. To ensure the integrity and authenticity of big data.
  3. To improve the performance and efficiency of big data analytics systems.
  4. To facilitate the sharing and collaboration of big data among different stakeholders.
Question 8 Multiple Choice (Single Answer)

Which of the following is NOT a common type of data masking technique used in Big Data Analytics Security?

  1. Tokenization
  2. Encryption
  3. Pseudonymization
  4. Generalization
Question 9 Multiple Choice (Single Answer)

What is the purpose of data provenance in Big Data Analytics Security?

  1. To track the origin and lineage of big data.
  2. To ensure the integrity and authenticity of big data.
  3. To improve the performance and efficiency of big data analytics systems.
  4. To facilitate the sharing and collaboration of big data among different stakeholders.
Question 10 Multiple Choice (Single Answer)

Which of the following is NOT a common type of data provenance technique used in Big Data Analytics Security?

  1. Lineage tracking
  2. Watermarking
  3. Fingerprinting
  4. Hashing
Question 11 Multiple Choice (Single Answer)

What is the purpose of security information and event management (SIEM) in Big Data Analytics Security?

  1. To collect, analyze, and respond to security events in real time.
  2. To ensure the integrity and authenticity of big data.
  3. To improve the performance and efficiency of big data analytics systems.
  4. To facilitate the sharing and collaboration of big data among different stakeholders.
Question 12 Multiple Choice (Single Answer)

Which of the following is NOT a common type of SIEM tool used in Big Data Analytics Security?

  1. Splunk
  2. ArcSight
  3. LogRhythm
  4. QRadar
Question 13 Multiple Choice (Single Answer)

What is the purpose of privacy regulations in Big Data Analytics Security?

  1. To protect the privacy of individuals whose data is collected and analyzed.
  2. To ensure the integrity and authenticity of big data.
  3. To improve the performance and efficiency of big data analytics systems.
  4. To facilitate the sharing and collaboration of big data among different stakeholders.
Question 14 Multiple Choice (Single Answer)

Which of the following is NOT a common type of privacy regulation that impacts Big Data Analytics Security?

  1. General Data Protection Regulation (GDPR)
  2. California Consumer Privacy Act (CCPA)
  3. Health Insurance Portability and Accountability Act (HIPAA)
  4. Payment Card Industry Data Security Standard (PCI DSS)
Question 15 Multiple Choice (Single Answer)

What is the purpose of data minimization in Big Data Analytics Security?

  1. To collect and store only the data that is necessary for a specific purpose.
  2. To ensure the integrity and authenticity of big data.
  3. To improve the performance and efficiency of big data analytics systems.
  4. To facilitate the sharing and collaboration of big data among different stakeholders.
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