Data Classification and Methods to Secure Data
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Professor Messer. (2023, November 28). Data Types and Classifications - CompTIA Security+ SY0-701 - 3.3 [Video]. YouTube. https://www.youtube.com/watch?v=R0W0_gZCVzk
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Data Classifications
Data classifications help organizations protect sensitive information based on its importance, sensitivity, and regulatory requirements.
Data classifications:
- Sensitive
- Confidential
- Public
- Restricted
- Private
- Critical
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Data Classifications Types
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Classifications of Data – Knowledge Check
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Methods to Secure Data
Securing data involves a combination of technical, procedural, and policy-driven methods. Here are some of the best practices for securing data:
Encryption
Permission Restrictions
Geographic Restrictions
Tokenization
Masking
Hashing
Obfuscation
Segmentation
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Obfuscation
A technique used to make data, code, or information unintelligible or difficult to understand, even if it is accessed by unauthorized individuals. Unlike encryption, obfuscation does not require a key for decryption but rather transforms data into a format that is hard to interpret without additional context.
Restricted Data
Restricted data is the most highly sensitive category and requires the strongest security measures to prevent exposure, espionage, or cyberattacks.
Restricted data is the most sensitive type of data that, if exposed, could cause severe harm to an individual, organization, or government.
Examples of restricted data:
- Top Secret Military Intelligence
- Proprietary Trade Secrets
- High-Value Financial Records
- Confidential Source Code
Masking
A technique used to obscure or hide sensitive data while maintaining its usability for certain operations. Unlike encryption, which fully converts data into an unreadable format, masking replaces specific portions of the data with substitute characters like asterisks or Xs.
Sensitive Data
Sensitive data refers to information that, if disclosed or accessed without authorization, could potentially cause harm, discrimination, or adverse consequences to an individual.
This type of data includes any information that requires a high level of security and protection due to its privacy implications.
Examples of sensitive data:
- medical records
- financial information
- biometric data
- racial origin
- political opinions
- religious beliefs
Hashing
A cryptographic process that converts input data (like passwords or files) into a fixed-length string (hash) using a mathematical algorithm. It’s a one-way function, meaning it cannot be reversed to retrieve the original data.
Permission Restrictions
Security measures that control who can access, modify, or share data based on predefined rules and policies.
Geographic Restrictions
These are restrictions for securing legal, regulatory, and technical measures that control where data can be stored, processed, and accessed based on location. These restrictions ensure compliance with data protection laws, mitigate risks, and prevent unauthorized access from certain regions.
Regulated Data: This is data where third parties or governments set the rules for protection, such as credit card information (PCI standards) or data subject to specific government laws [00:20]. Proprietary Data & Trade Secrets: Unique information owned by an organization, such as internal processes or intellectual property, that would not be found outside the company [00:42, 03:46]. Sensitive Personal Data: PII (Personally Identifiable Information): Details like names, dates of birth, biometric info, or addresses that can link back to an individual [03:59]. PHI (Protected Health Information): Health status, records, or healthcare payment details specific to an individual [04:23]. Human vs. Non-Human Readable: Data can range from easily readable spreadsheets to encoded formats like barcodes, which may require machine interpretation [02:13]. Classification Levels: Organizations use labels to determine access rights [04:45]: Public/Unclassified: Accessible to anyone [05:11]. Private/Restricted: Requires additional rights or a non-disclosure agreement (NDA) [05:18]. Confidential: High sensitivity requiring specific access levels [05:03]. Critical: Data that must remain available at all times, requiring high-uptime procedures [05:32].
Public Data
Public data is information that is intentionally made available to anyone without any restrictions.
This classification poses no confidentiality risk but should still be protected from integrity and availability threats such as tampering, misinformation, or denial-of-service attacks.
Examples of public data:
- Census data
- Investor reports
- Open-source academic research papers
- Social media posts
Private Data
Private data refers to personal or sensitive information about individuals that must be protected to prevent unauthorized access, identity theft, fraud, or privacy violations. This data is often subject to privacy laws and compliance regulations that dictate how it must be handled, stored, and transmitted.
Examples of private data:
- Personally Identifiable Information (PII)
- Financial & Payment Information
- Health & Medical Information
- Usernames & Passwords
- IP Addresses
Segmentation
The practice of dividing a network into smaller, isolated sections to enhance security by limiting the spread of potential attacks and controlling access to sensitive data.
Encryption
Converts data into an unreadable format that can only be accessed with a decryption key, protecting sensitive information like credit card details even if compromised.
Tokenization
The process of substituting a sensitive data element with a non-sensitive equivalent, referred to as a token, that has no intrinsic or exploitable meaning or value.
Critical Data
Critical data refers to information essential for the operations, security, or survival of an organization, government, or system. The data should always be avaliable. If this data is lost, compromised, or unavailable, it can cause severe financial loss, operational failure, national security risks, or life-threatening consequences.
Examples of critical data:
- Corporate Financial Reports & Payroll Data
- Emergency Response & Dispatch Systems
- Power Grid & Utility Control Systems
- Incident Response & Cyber Threat Intelligence Reports
Confidential Data
Confidential data refers to information that, if disclosed, could cause harm to individuals, businesses, or governments.
Confidential data is more sensitive than public or internal data but may not always be the most restricted form of information. Often very sensetive, must be approved to view.
Confidential Data examples:
- Employee Records
- Company Financials
- Insurance Information
- Internal Government Reports
Module 1 Lesson 4 Data Classification and Methods to Secure Data
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Transcript
Data Classification and Methods to Secure Data
Click here or there to move to the next page!
Professor Messer. (2023, November 28). Data Types and Classifications - CompTIA Security+ SY0-701 - 3.3 [Video]. YouTube. https://www.youtube.com/watch?v=R0W0_gZCVzk
Text
Next
Data Classifications
Data classifications help organizations protect sensitive information based on its importance, sensitivity, and regulatory requirements.
Data classifications:
Back
Next
Data Classifications Types
Back
Next
Click on the dots to see more information about the topic.
Classifications of Data – Knowledge Check
Back
Next
Methods to Secure Data
Securing data involves a combination of technical, procedural, and policy-driven methods. Here are some of the best practices for securing data:
Encryption
Permission Restrictions
Geographic Restrictions
Tokenization
Masking
Hashing
Obfuscation
Segmentation
Back
Click on the dots to see more information about the topic.
Obfuscation
A technique used to make data, code, or information unintelligible or difficult to understand, even if it is accessed by unauthorized individuals. Unlike encryption, obfuscation does not require a key for decryption but rather transforms data into a format that is hard to interpret without additional context.
Restricted Data
Restricted data is the most highly sensitive category and requires the strongest security measures to prevent exposure, espionage, or cyberattacks. Restricted data is the most sensitive type of data that, if exposed, could cause severe harm to an individual, organization, or government.
Examples of restricted data:
Masking
A technique used to obscure or hide sensitive data while maintaining its usability for certain operations. Unlike encryption, which fully converts data into an unreadable format, masking replaces specific portions of the data with substitute characters like asterisks or Xs.
Sensitive Data
Sensitive data refers to information that, if disclosed or accessed without authorization, could potentially cause harm, discrimination, or adverse consequences to an individual. This type of data includes any information that requires a high level of security and protection due to its privacy implications.
Examples of sensitive data:
Hashing
A cryptographic process that converts input data (like passwords or files) into a fixed-length string (hash) using a mathematical algorithm. It’s a one-way function, meaning it cannot be reversed to retrieve the original data.
Permission Restrictions
Security measures that control who can access, modify, or share data based on predefined rules and policies.
Geographic Restrictions
These are restrictions for securing legal, regulatory, and technical measures that control where data can be stored, processed, and accessed based on location. These restrictions ensure compliance with data protection laws, mitigate risks, and prevent unauthorized access from certain regions.
Regulated Data: This is data where third parties or governments set the rules for protection, such as credit card information (PCI standards) or data subject to specific government laws [00:20]. Proprietary Data & Trade Secrets: Unique information owned by an organization, such as internal processes or intellectual property, that would not be found outside the company [00:42, 03:46]. Sensitive Personal Data: PII (Personally Identifiable Information): Details like names, dates of birth, biometric info, or addresses that can link back to an individual [03:59]. PHI (Protected Health Information): Health status, records, or healthcare payment details specific to an individual [04:23]. Human vs. Non-Human Readable: Data can range from easily readable spreadsheets to encoded formats like barcodes, which may require machine interpretation [02:13]. Classification Levels: Organizations use labels to determine access rights [04:45]: Public/Unclassified: Accessible to anyone [05:11]. Private/Restricted: Requires additional rights or a non-disclosure agreement (NDA) [05:18]. Confidential: High sensitivity requiring specific access levels [05:03]. Critical: Data that must remain available at all times, requiring high-uptime procedures [05:32].
Public Data
Public data is information that is intentionally made available to anyone without any restrictions. This classification poses no confidentiality risk but should still be protected from integrity and availability threats such as tampering, misinformation, or denial-of-service attacks.
Examples of public data:
Private Data
Private data refers to personal or sensitive information about individuals that must be protected to prevent unauthorized access, identity theft, fraud, or privacy violations. This data is often subject to privacy laws and compliance regulations that dictate how it must be handled, stored, and transmitted.
Examples of private data:
Segmentation
The practice of dividing a network into smaller, isolated sections to enhance security by limiting the spread of potential attacks and controlling access to sensitive data.
Encryption
Converts data into an unreadable format that can only be accessed with a decryption key, protecting sensitive information like credit card details even if compromised.
Tokenization
The process of substituting a sensitive data element with a non-sensitive equivalent, referred to as a token, that has no intrinsic or exploitable meaning or value.
Critical Data
Critical data refers to information essential for the operations, security, or survival of an organization, government, or system. The data should always be avaliable. If this data is lost, compromised, or unavailable, it can cause severe financial loss, operational failure, national security risks, or life-threatening consequences.
Examples of critical data:
Confidential Data
Confidential data refers to information that, if disclosed, could cause harm to individuals, businesses, or governments. Confidential data is more sensitive than public or internal data but may not always be the most restricted form of information. Often very sensetive, must be approved to view.
Confidential Data examples: