Data in Use

Data in use is data that is being actively processed, accessed, or updated by users or software. It is stored in a non-persistent digital state, such as in a CPU register, CPU cache, or computer random-access memory.

Data in use is most vulnerable to security risks because it is immediately available to users and can be exposed to attack or human error. Some examples of data in use include files shared between employees, Online banking transactions, Real-time analytics, and Database queries.

To protect data in use, you can use authentication, identity management, and permissions to limit access to a subset of individuals. You can also encrypt the data while it is in use.

Data must be secured in three states: at rest, in use, and in motion. Each state presents unique security challenges.

 Data in Transit

Data in transit is data sent from one location to another, such as over a network or the Internet. It can also be referred to as data in motion or flight.

Emails, instant messages, video calls, file transfers, and website requests are examples of data in transit.

Data in transit should be encrypted to protect it from being intercepted or manipulated by attackers. Encryption algorithms ensure that only those with the decryption key can access the data.

Some ways to protect data in transit include:

Encryption: Prevents attackers from reading or modifying data

Network protection: Prevents attackers from intercepting data using TLS, IPSec, & VPNs

Authentication: Prevents attackers from impersonating the service

Access controls: Restricts access to files and ensures only authorized users can access them

 Data at Rest

Data at rest is stored in a physical location, such as a computer's hard drive or a server, and is not actively used or moved between devices or networks. It can include both structured and unstructured data.

Examples of data at rest include Spreadsheet files on a laptop, Videos on a mobile device, Employment records in a company's HR system, and Sales information in a company's database.

Data at rest is often the most sensitive data in an organization and can be very valuable to hackers. Data breaches at rest can have serious consequences, including Large financial losses, Damage to a company's reputation, Regulatory fines, and Civil liability.

To protect data at rest, organizations can use techniques such as:

Encryption: Makes the data indecipherable and useless to anyone who steals it using FDE (Full Disk Encryption), SED (Self-Encrypting Drives), and BitLocker.

Data tokenization: Replaces sensitive data with non-sensitive tokens that are meaningless on their own

Layered password protection: Sets access controls to data at different levels of sensitivity

 Geographic Restrictions

"Geographic restrictions" limit access to data based on a user's physical location, essentially meaning that people in certain areas can't access specific information due to their geographical position; this is often referred to as "geo-blocking" or "geo-restriction."

Key points about geographic restrictions:

How it works:

Usually, a user's IP address is used to determine their location, and access is restricted based on that information.

Reasons for use:

Copyright protection: To prevent unauthorized access to only licensed content for specific regions.

Local regulations: Complying with laws that may vary by country.

Content localization: Providing content relevant to a specific geographic area.

Examples:

Streaming services only allow access to certain content based on the user's country.

Online stores limit product availability to specific regions.

Certain websites are being blocked in particular countries due to censorship.

 Phishing Campaigns

Yes, organizations use phishing campaigns as employee training to help employees identify and respond to phishing attacks:

Phishing tests

Also known as simulated phishing, these tests send fake phishing emails to employees to assess their response. The goal is to evaluate the effectiveness of the organization's phishing training program and identify employees who may need additional training.

Phishing awareness training

This type of training can be delivered in various ways, including computer-based, classroom-based, and simulated phishing exercises. The goal is to equip employees as the organization's first line of defense against cyberattacks.

Tailored training

Some training programs use employee behavior and user attributes to customize phishing campaigns, training assignments, and reporting.

Phishing emails often include requests for sensitive information, bad grammar, or emotional appeals. Employees should be trained to look for suspicious subject lines and content and to check every email address for anomalies.

Mean Time to Remediate

 MTTR (Mean Time to Remediate)

Mean time to remediate (MTTR) is a key performance indicator (KPI) that measures how long it takes to fix a failed component or security vulnerability:

Definition

MTTR is the average time it takes to resolve a security vulnerability after it's been discovered. It's calculated by dividing the total time from detection to remediation by the number of incidents.

Importance

MTTR is crucial because it helps reduce the time systems are exposed to risk, which can lead to follow-on attacks and additional incidents. It also helps minimize potential damage and enhance customer trust.

Calculation

MTTR can be calculated on a case-by-case basis or on a macro level. It only includes closed vulnerabilities and doesn't include false positives or open vulnerabilities.

Security tools

Security tools like JFrog x-ray, Aquasec, PrismaCloud, Blackduck, Coverity, Synk, Veracode, Fortify, and Checkmarx can help identify vulnerabilities and classify their risk exposure.

Mean Time to Detect

 MTTD (Mean Time to Detect)

Mean Time to Detect (MTTD) measures how long it takes to identify and report a problem after it occurs. It's a key performance indicator that can help organizations improve security operations, reduce costs, and avoid attacks.

Here's some more information about MTTD:

How it's calculated

MTTD is calculated by dividing the total time spent detecting incidents by the number of incidents.

Why it's important

A low MTTD means an organization can detect and resolve issues faster, leading to better performance, fewer costs, and less downtime.

How it's used

MTTD can be used to evaluate security operations, test new tools and processes, and identify areas for improvement.

Benefits

MTTD can help organizations:

Prevent threats from escalating

Maintain system reliability

Reduce the scope of damage from security incidents

Adhere to compliance

Enhance overall system performance and efficiency