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Top 7 Data Security Technologies

The most important aspect of a corporate cybersecurity strategy revolves around how to protect corporate data and prevent data loss. This includes data at rest, in transit and in use.

Each of these has the same goal of keeping your data safe.

What is data security and why is it important?

Data security refers to how data is protected against theft, loss, or unauthorized access throughout its lifecycle.

Data breaches are an ongoing problem for organizations. According to a ThoughtLab report, the number of data breaches and cyberattacks in 2021 will increase by 15.1% compared to 2020. Data breaches not only expose corporate data, they also subject companies to lawsuits and fines.

Data security practices, policies, and technology are also key to preventing internal users from taking inappropriate actions on data.

Data security is important because it helps you:

  • Keep your intellectual property safe.
  • Prevent financial loss.
  • Maintain customer trust.When
  • Ensures compliance with several regulatory standards.

That last point is important because organizations have a variety of industry and federal regulations to comply with, from GDPR and CCPA to the Sarbanes-Oxley Act and PCI DSS.

Types of data security technology

Data security is a top priority as attackers relentlessly look for every vulnerability to penetrate corporate networks. To properly protect data, companies can use these seven technologies from her:

1. Firewall

A firewall is the first security layer of a system. Designed to prevent unauthorized sources from accessing corporate data. A firewall acts as an intermediary between a personal or corporate network and the public Internet. Firewalls use pre-configured rules to inspect every packet entering or leaving your network, helping to stop malware and other malicious traffic from connecting to devices on your network.

Different types of firewalls include:

  • Basic packet filtering firewall
  • circuit level gateway
  • Application level gateway
  • Stateful inspection firewall
  • next generation firewall

2. Authentication and Authorization

Two processes are used to ensure that only the right people have access to enterprise data: authentication and authorization.

Authentication involves providing proof that a user is who they say they are. This proof can provide secrets such as passwords, her PIN, or biometrics. Depending on the authentication scenario, the user may be required to provide one or more additional factors when he signs in. Two-factor authentication Also multi-factor authentication (MFA). Step-up authentication may also be required when a user attempts more restricted actions after successfully logging in the first time.

Examples of authentication are:

  • Password/PIN
  • MFA
  • biometric scan
  • behavioral scan

Once a user proves their identity, authorization determines whether the user has the correct permissions to access and manipulate specific data. By authorizing users, they gain permission to read, edit, and write various resources within the system.

Examples of authorization are:

  • Principle of Least Privilege Access
  • Attribute-based access control
  • Role-based access control

3. Data encryption

Data encryption transforms data into coded ciphertext to keep it safe at rest and in transit between authorized parties. Encrypting the data ensures that only someone with the proper decryption key can view the data in its original plaintext form. Encrypted data is meaningless if obtained by an attacker.

Examples of data encryption are:

  • Also known as asymmetric encryption public key cryptography; When
  • symmetric encryption, aka private key encryption.

Endpoint encryption is required to protect data at rest. This can be done with file encryption or full disk encryption methods.

4. Data masking

Data masking obscures data so that even if criminals steal it, they won’t be able to understand what they have stolen. Unlike encryption, which uses a cryptographic algorithm to encode data, data masking involves replacing legitimate data with similar fake data. This data can also be used in scenarios that don’t require the use of real data, such as software testing and user training.

Tokenization is an example of data masking. This involves replacing data with unique strings that hold no value and cannot be reverse engineered if obtained by a malicious person.

Other examples of data masking are:

  • Data anonymization
  • data generalization
  • Data anonymization
  • pseudonymization

5. Hardware-based security

Hardware-based security involves physical protection of the device rather than relying solely on software installed on the hardware. Attackers target all IT layers, so businesses need protection built into silicon to harden their devices.

Examples of hardware-based security are:

  • hardware-based firewall
  • proxy server
  • hardware security module

Hardware-based security is often run separately from the main processor, such as Apple’s Secure Enclave.

6. Data backup and resilience

Organizations should store multiple copies of their data. Especially if you want to fully recover after a data breach or other disaster. With data backups in place, businesses can resume normal business functions faster and with fewer disruptions. To ensure data resilience, organizations need to keep backed up data safe and readily available.

An example of data backup protection is data vaulting, which creates air-gapped versions of backup data. Also, organizations should follow a 3-2-1 backup strategy. This will save at least three copies of your data in different locations.

Other types of data backup protection include:

  • Redundancy
  • cloud backup
  • external hard drive
  • hardware appliance

7. Data erasure

It’s important that your organization deletes data properly and that deleted data cannot be recovered.known as erase data, this process involves completely overwriting the saved data so that it cannot be recovered.also known as data destructiondata erasure often makes data unreadable after erasure.

Organizations need to be able to properly dispose of data, especially with regulations such as GDPR, which stipulate that customers can request erasure of personal data.

Other types of data erasure include:

  • erase data
  • Overwrite
  • physical destruction
  • demagnetization