CISSP Domain 2 Flashcards

1
Q

Information lifecycle

A

Creation
Classification
Storage
Usage
Archive
Destruction

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2
Q

Data classification and damage level

A

Value of data by labeling

Top secret: Gracve damage

Secret: Serious damage

Confidential: Damage

Unclassified : No damage

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3
Q

Data classification non governmental

A

Confidential or Proprietary - Grave damage

Private - Serious damage - PII or PHI

Sensitive - Damage - IP address, OS, software

Public - No damage

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4
Q

Data States

A

Data at rest - Strong symmetric encryption

Data in transit - combo

Data in use -

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5
Q

Steps in Data management

A

Define data

Asset classification

Define security requirements

Identify security controls to implement

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6
Q

Establishing information and asset handling requirements

A

Data maintenance

DLP: Network and Endpoint

Marking sensitive data and assets: Tags and meta tags

Handling assets and data

Data collection limitation

Data location: Data center and redundancy

Storing sensitive data

Data destruction

Eliminating data remnanence

Ensuring appropriate data and assets retention

Data destruction

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7
Q

Data remnanence

A

Left over data after supposedly erased

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8
Q

Slack space

A

Unused space within disk cluster

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9
Q

Degausser and SSD

A

Heavy magnetic field and effective only in magnetic media

Does not effect cd, dvd and SSD

SSD include built in earse command

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10
Q

Erasing

A

Delete operations in file but actual data remains on drive

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11
Q

Clearing

A

Overwrite for reuse and ensure clear data cannot be recovered and three separate phases

First character

Complement

Seperate bits

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12
Q

Purging

A

A level of assurance that data is not recoverable

Repeat clearing process several times

But not always trusted

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13
Q

Destruction

A

Most Secure method for sanitizing

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14
Q

Cryptographic erasures

A

If data is encrypted then crypto shed to destroy

They only destroy encryption key and decryption keys but data remains encrypted

Better overwrite the data just in case if encryption isn’t strong

Especially cloud destroy cryptography keys

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15
Q

Retention policies (lawsuit)

A

Cannot delete potential evidence after a lawsuit is filed however if retention policy dictates it’s legal to delete

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16
Q

Data protection methods - DRM solutions methods

A

DRM liscencing : Grants access to product

Persistent online authentication: System to be connected to internet to use product

Continus audit trail

Automatic expiration

They use steganography to detect person who pirated

17
Q

Cloud access security broker

A

Monitors all activities and enforces admin defined security policies

Software placed logically between users and cloud based resources

Can be on premise or cloud

Effective detection of shadow IT- By collecting and analysis of network logs

18
Q

Psudonymization

A

Replace data with artificial identifiers

19
Q

Tokenization

A

Use of random string of characters to replace other data..

Credit card transactions

20
Q

Anonymization

A

Removing all relevant data

Randomised masking

Anonymization cannot be reversed unlike psudonymization and tokenization

21
Q

Data owners

A

Identify classification of data and label

22
Q

Asset owners

A

Owns asset

Devlop security plan
Maintain and devlop
Aup
Updates

23
Q

Business owners/ Mission owners

A

Own processes - like sales department

System provides value to organization

24
Q

Data processor

A

Natural or legal person processes data on behalf of data controller

25
Q

Dara controller

A

Person or entity that controls data

26
Q

Data custodian

A

Helps protect cia

27
Q

Admins

A

Elevated previliges

28
Q

4 types of baseline

A

Low impact baseline: Loss of CIA will have low impact

Moderate impact

High impact

Privacy control baseline: PII

29
Q

Tailoring

A

Modify list of security controls within a baseline to align with organization mission

30
Q

Scoping

A

Part of tailoring process and review the baseline security controls and selecting those which are applicable

31
Q

homomorphic encryption

A

Data in use - some cases, it’s possible for an application to work on encrypted data using homomorphic encryption (in cipher text format itself . This limits the risk because memory doesn’t hold unencrypted data.

32
Q

Air gap

A

One network processes unclassified data only. Another network processes classified data. Techniques such as air gaps ensure the two networks never physically touch each other. An air gap is a physical security control and means that systems and cables from the classified network never physically touch systems and cables from the unclassified network.

33
Q

DLP discovery

A

Most DLP solutions also include discovery capabilities. The goal is to discover the loca- tion of valuable data within an internal network. When security administrators know where the data is, they can take additional steps to protect it. As an example, a database server may include unencrypted credit card numbers. When the DLP discovers and reports this, database administrators can ensure the numbers are encrypted. As another example, company policy may dictate that employee laptops do not contain any PII data. A DLP content discovery system can search these and discover any unauthorized data. Additionally, many content dis- covery systems can search cloud resources used by an organization.

34
Q

What are the criteria to be considered (esp. csp) when data location of backups ?

A

Some organizations maintain data in large data centers. It’s common to replicate this data to one or more other data centers to maintain the availability of the critical data. These data centers are typically located in separate geographical locations. When using cloud storage for backups, some organizations may need to verify the location of the cloud storage to ensure it is in a separate geographical location.

35
Q

What is sanitisation ?

A

Sanitization can refer to the destruction of media or using a trusted method to purge clas- sified data from the media without destroying it.

36
Q

pseudonymization and tokenization, anonymization

A

Unlike pseudonymization and tokenization, anonymization cannot be reversed. After the data is randomized using an anonymization process, it cannot be returned to the original state.

Randomized masking can be an effective method of anonymizing data.

Pseudo aka Artificial identifiers and token needs db and vault to maintain original data