AWS Knowledge
Mastering Data Security in Google Cloud BigQuery
Piyush Kalra
Oct 4, 2024
The challenge of securing sensitive information within the cloud has become more pronounced in modern organizations. As people and organizations utilize more and more cloud storage, being able to protect your data from any form of breach or tampering becomes a paramount concern. BigQuery by Google Cloud is such a powerful analytics platform that it provides a great [and secure] way of handling large amounts of information. The present article will highlight essential tips for protecting your data in Google BigQuery so that many people including data analysts, IT managers, cloud engineers, and Dev operation specialists will find it useful. Recent studies show that following these steps may help reduce the data breach risks by more than 70%.
Understanding Data Security in Google BigQuery
What is Data Security?
(Image source: Google Cloud)
Data security is typically understood as a combination of processes, policies, and technologies that are deployed with the objective of protecting information from theft, corruption, or unauthorized data access. This perspective defines data security as a very large set of procedures whose goal is the assurance of the trust, reliability, and availability of data, ringing its substantive core, information safeguarding. This includes the use of encryptions, access restraints, and data protection appraisals periodically on systems in place.
Even when the data resides within cloud environments like Google BigQuery, data security refers to a full range of strategies that focus on the data protection from the time of its creation until its deletion, providing protection at every stage. This may include the advanced technique of data encryption when data is stored and when data is being sent, effective identity control mechanisms and vigilant surveillance and response systems to potential threat signs. To supplement systems for the ‘safe’ management of information, data redundancy and backup security measures are commonly put items to ensure that loss or corruption of information does not occur.
Common Threats to Cloud Storage
Cloud storage is impressive and very easy to scale up, however, it does have some threats to it as well. These consist of data loss, data breach, insider breach, misconfigured cloud accounts and other cloud service vulnerabilities. For a person to address these risks properly, it is important to understand them first.
Furthermore, poor user access control can put users and their documents at risk since sensitive information may be open to be seen or edited by unauthorized persons. To reduce the likelihood of such occurrences quite significantly, companies must conduct regular security checks and implement the zero-trust approach. Again, with lots of information about cloud computing in the market, it is very hazardous to take data abroad without any security measures.
Navigating Compliance Requirements
Outlaw data breaching is very important. This is relevant when one is working with pieces of information that are much more sensitive than others, for instance, the records one comes across in the business sector. It is necessary to recognize these legal structures to keep confidence between all parties and prevent the risk of legal suits resulting in extensive financial loss. If these policies are met, up to 90% of your organization’s exposure to the risks of data handling will be assured leading to a more assured feeling.
Best Practices for Securing Data in Google BigQuery
Identity and Access Management (IAM)
Understanding IAM Roles and Permissions
IAM roles is the access management for BigQuery resources and controls all the effective access to any or all resources. Different assignments are given in order to restrict users from utilizing everything and keep to a certain level of the role that was intended to them. Refer to our article to understand better about GCP IAM for User Access Management.
The Principle of Least Privilege
Least privilege principles are the process of providing the user keys, credentials, and rights that are sufficient and not more as the given task requires. The advantage of this is that any data which may be lost or rendered inaccessible is contained, as, in this case, only the user’s authorized login credentials pose a risk.
Configuring Identity and Access Management (IAM) for BigQuery
Initiating the configuration on IAM for BigQuery simply involves stating the roles and assigning permissions for the respective users. The settings also need to be reviewed periodically in compliance with the principle of least privilege. Here’s how you can do it:
Add Members and Set Permissions:
Open the IAM page of the Google Cloud console, select the relevant project, click “Grant Access” and key in the user or group email you wish to invite.
On the popup window, add users in the principals fields and click on the drop-down to select a certain role: BigQuery >> BigQuery Admin etc.
Grant Access to a Dataset:
Open the BigQuery page and in the Explorer pane expand the project and click on a dataset
Click on 'Sharing', then select 'Permissions', look for 'Add principal', type in a principal, choose the role, and press 'Save.'
Apply IAM Conditions:
You need to have the Project IAM Admin role, which includes the resourcemanager.projects.setIamPolicy permission to apply IAM Conditions to BigQuery resources.
Grant a Role to a Principal:
Go to the BigQuery IAM page, select a project/folder/organization, and click on the principal icon.
If the principal who is being edited already holds roles under ‘Edit principal,’ click on ‘Add another role.’ If the principal doesn’t have such roles, click on ‘Add’ and fill in the email address and click on ‘Save’.
BigQuery resource permissions can be assigned at different levels such as scope of organization, folder or project, connection, datasets, tables or views, policy tags and row access policy.
Data Encryption
Types of Encryption
BigQuery provides offshore as well as onshore encryption which means your data is safe if it’s on a disk and also if it is being sent over the network.
Customer-Managed Encryption Keys (CMEKs)
CMEK allows organizations who wish to take control to use their own management over the IT munition materials such as the keys, which are utilized to lock the IT position. This is the additional security control aside from the normal encryption provided by BigQuery.
Default Encryption by Google
Any data that is included in Bigquery database Street will be encrypted. This will work for cases where the users do not wish to control the encryption keys or use the default level of encryption provided by BigQuery.
Auditing and Monitoring
Importance of Data Monitoring Activity
Installations of regular audits on data activities helps to prevent unauthorized data accesses and other security threats before they develop. Therefore for the increased chances of facing threats, tracking who and in what manner these activities are being performed is vital. Refer to our article to understand better about GCP Monitoring.
Tools for Auditing in BigQuery
There are different tools for auditing using BigQuery including Cloud Audit Logs and Cloud data Monitoring. Such activities may include manipulation of your data in which case the access wall will track.
How To Configure The Suspicious Activity
By deploying suspicious activity alert systems, your team is able to act quickly to potential threats. In such, it prompts one to create alerts for data that does not seem to be biotech: the way that the data is accessed or used, or the data movement itself.
Go to the alerting page and select ‘New Condition’.
2. Select the ‘Metric’.
3. Go to the ‘Configure trigger’ and set up the Alert trigger.
4. Once completed, go to the ‘Review alert’ to preview the conditions and click on “Create Policy”.
Data Retention and Deletion Policies
Understanding the Data Lifecycle Management Policy
Good management of the data lifecycle mitigates the risks of keeping data for a long period or misplacing it by ensuring that data is only looped in its storage if warranted and deleted once it is no longer useful. This saves on storage costs and reduces chances of compromising data.
Creating Table and Partition Expiration
BigQuery allows users to set expiration time on the tables and the partitions. This makes sure that everything you want deleted is deleted without any further action, in an attempt to manage over compliance. Refer to the article to understand how to create Table and Partition Expiration.
Compliance with Legal Regulations
Data retention and deletion policies are fundamental in helping an entity comply with the law. Make sure that your practices are compliant with the proper and pertinent practices to avoid penalties and loss of trust from customers.
Authorized Views
Benefits of Authorized Views
Data such users will not have direct data access to the tables being queried, however, they will only be able to query views which contain only parts of the tables or data that is required. Authorized views are safe since most of the programs are sheltered within the corporation.
Creating and Managing Authorized Views
Customary administrative users are users defined in such a way, that views which contain somewhat more sensitive data do not need special permissions to access them. All administrative users with customized editable access permissions, permissions to view normal members statuses, usually monthly practices.
Navigate to the BigQuery page at the Google Cloud console >> In the Explorer pane, choose a project and expand what is contained within it to choose a dataset >> Click New Load and then click Open >> In the Dataset info pane, click person_add Sharing and then select Authorize Views >> In this regard, type the name of the view to be authorized under Authorize view >> Click Add authorization >> Click Close. Refer to the article to understand better about How to Create and Manage Authorized Views.
Use Cases for Authorized Views
These views are best suited for dealing with such circumstances where more than one person requires access to confidential information. Such views, for instance, can be used to restrict access to customer information while giving the sales department with marketing related data.
Fine-Grained Access Control
Row-Level and Column-Level Security
These access control methods permit the users to have access only to selected rows or columns among those in a given table. With this, users are presented with only data that is relevant to their duties improving security.
Implementing Policy Tags for Sensitive Data
BigQuery has a feature of policy tags that allows you to indicate what is or is not sensitive data. These tags allow compliance enforcement and usage monitoring. Refer to the article to understand How to Setup.
Examples of Fine-Grained Access Scenarios
Fine-grained access control is of great significance in particular in industries such as finance and healthcare, where various users may need to work with specific blocks of data. Implementing these controls helps sustain compliance and safeguard sensitive information.
Additional Security Measures
Strong Password Policies
Strong passwords are the backbone of cloud security and therefore help prevent unauthorized access to information and data breaches. Prescription on strong password policy policy/politics on policies on sinsure that such sensitive information will always remain safe. Policies discouraging short and weak passwords should impose that users construct long and complicated deep passwords containing letters numbers and symbols and fit into specific time periods. Reports indicate that poor selection of passwords accounts for 81% of all the breaches related to hacking which assimilates the need for good password policy enforcement.
Two-Factor Authentication (2FA)
Two-Factor authentication (2FA) adds an extra layer of security as it requires two forms of identification before a user is granted data access making it difficult for unauthorized personnel to gain access. Adopting 2FA within the Google Cloud platform is simple and encouraging your users to practice this can considerably improve security levels within the organization.
Regular Security Assessments
It is advisable to allocate time for each assessment so as to help in exposing weaknesses that need to be remedied and increasing security measures within an organization’s document management. Proactive assessment of your defenses is essential to ensure that they are not outdated and will withstand threats brought about by technological changes. Deploying vulnerability scanners or performing penetration testing is helpful in the evaluation of your security and provides you with information necessary for the correction of weaknesses.
Conclusion
The best way to protect your data in Google BigQuery is to deploy a range of known best practices such as the configuration of IAM, data encryption, and more importantly, conducting proper security assessments. Applying these approaches helps in protecting crucial data, compliance and gaining your customers trust. GCP security features should also be adapted in order to make sure your data protection is always improving and your company is protected from cyber threats in the competitive environment.
Join Pump for Free
If you found this post interesting, consider checking out Pump, which can save you up to 60% off AWS for early-stage startups, and it’s completely free (yes, that's right!). Pump has tailor-made solutions to take you in control of your AWS and GCP spend in an effective way. So, are you ready to take charge of cloud expenses and maximize the most from your investment in AWS? Learn more here.
