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Utilizing Google Cloud’s PII Security Features

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Are you concerned about the security and privacy of personal identifiable information (PII) in your organization? If so, you're not alone. In this post, we'll show you how to use Google Cloud's tools and features to find and protect PII.

BigQuery is a leading data warehouse solution in the market today, and is valued by customers who need to gather insights and advanced analytics on their data. Many common BigQuery use cases involve the storage and processing of Personal Identifiable Information (PII)—data that needs to be protected within Google Cloud from unauthorized and malicious access.

Too often, the process of finding and identifying PII in BigQuery data relies on manual PII discovery and duplication of that data. One common way to do this is by taking an extract of columns used for PII and copying them into a separate table with restricted access. However, creating unnecessary copies of this data and processing it manually to identify PII increases the risks of failure and subsequent security events.

In addition, the security of PII data is often mandated by multiple regulations and failure to apply appropriate safeguards may result in heavy penalties. To address this issue, customers need solutions that 1) identify PII in BigQuery and 2) automatically implement access control on that data to prevent unauthorized access and misuse, all without having to duplicate it.

This blog will discuss a solution developed by Google Professional Services for leveraging Google Cloud DLP to inspect and classify sensitive data and suggest a solution for using these insights to automatically tag and protect data in BigQuery tables.

BigQuery Auto Tagging solution overview

Automatic DLP can help to identify sensitive data, such as PII, in BigQuery. Organizations can leverage Automatic DLP to automatically search across their entire BigQuery data warehouse for tables that contain sensitive data fields and report detailed findings in the console (see Figure 1 below,) in Data Studio, and in a structured format (such as a BigQuery results table.) Newly created and updated tables can be discovered, scanned, and classified automatically in the background without a user needing to invoke or schedule it. This way you have an ongoing view into your sensitive data.

Figure 1: Visibility of sensitive data fields in BigQuery

In this blog, we show how a new open source solution called BigQuery Auto Tagging Solution solves our second goal—automating access control on data. This solution sits as a layer on top of Automatic DLP and automatically enforces column-level access controls to restrict access to specific sensitive data types based on user-defined data classification taxonomies (such as high confidentiality or low confidentiality) and domains (such as Marketing, Finance, or ERP System.) This solution minimizes the risk of unrestricted access to PII and ensures that there is only one copy of data maintained with appropriate access control applied down to the column level.

The code for this solution is available on Github at GoogleCloudPlatform/bq-pii-classifier. Please note that while Google does not maintain this code, you can reach out to your Sales Representative to get in contact with our Professional Services team for guidance on how to implement it.

BigQuery and Data Catalog Policy Tags (now Dataplex) have some limitations that you should be aware of before implementing this solution to ensure that it will work for your organization:

  • Taxonomies and Policy Tags are not shared across regions: If you have data in multiple regions you will need to create or replicate your taxonomy in each region that you want to apply policy tags.
  • Maximum number of 40 taxonomies per project: If you require different taxonomies for different business domains or have replications to support multiple Cloud regions those will count against this quota.
  • Maximum number of 100 policy tags per taxonomy: Cloud DLP supports up to 150 infoTypes for classification, however, a single policy taxonomy can only support up to 100 including any nested categories. If you need to support more than 100 data types, you may need to split these across more than one taxonomy.

High-level overview of the solution

Figure 2: High level architecture of solution

The solution is composed mainly of the following components: Dispatcher Requests topic, Dispatcher service, BigQuery Policy Tagger Requests topic, and BigQuery Policy Tagger service and logging components.

The Dispatcher Service is a Cloud Run service that expects a BigQuery scope to be expressed as inclusion and exclusion lists of projects, datasets, and tables. This Dispatcher service will query Automatic DLP Data Profiles to check if the tables in-scope have data profiles generated. For these tables, it will publish one request per table to the “BigQuery Policy Tagger Requests” PubSub topic. This topic enables rate limiting of BigQuery column tagging operations and apply auto-retries with backoffs.

The “BigQuery Policy Tagger” Service is also a Cloud Run service that receives the information of the DLP scan results of a BigQuery table. This service will determine the final InfoType of each column and apply the appropriate Policy Tags as defined in the InfoType – Policy Tags mapping. Only-one INFO_TYPE is selected and the function assigns the associated policy tag.

Lastly, all Cloud Run services maintain structured logs that are exported by a log sink to BigQuery. There are multiple BigQuery views that help with monitoring and debugging Cloud Run call chains and tagging actions on columns.

Deployment options

After deploying the solution, it can be used in two different ways:

[Option 1] Automatic DLP-triggered immediate tagging:

Figure 3: Deployment option 1 – Automatic DLP triggered tagging and inspection

Automatic DLP is configured to send a Pub/Sub notification on each inspection job completion. The Pub/Sub notification includes the resource name and it triggers the Tagger service directly

[Option 2] Scheduled tagging:

Figure 4: Deployment option 2 – Scheduled tagging and inspection

In this scenario, the Dispatcher service is invoked on a schedule with a payload representing a BigQuery scope to list inspected tables by Automatic DLP and create a tagging request per table. You could use Cloud Scheduler (or any Orchestration tool) to invoke the Dispatcher service. If the solution is deployed within a VPC-SC perimeter, other schedulers that support VPC-SC should be used (such as Composer or Custom App.)

In addition, more than one Cloud Scheduler/Trigger could be defined to group projects/datasets/tables that have the same tagging schedule (such as daily or monthly.)

To learn more about Automatic DLP, see our webpage. To learn more about the BQ classifier, see the open source project on Github: GoogleCloudPlatform/bq-pii-classifier and get started today!

Case Study

Partnering for Stronger Security: Google and Mandiant Join Forces

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In this blog post, we'll delve into how Google and Mandiant are working together to transform security operations and incident response, helping you stay ahead of potential threats and protect your business.

Over the past two decades, Google has innovated to build some of the largest and most secure computing systems in the world. This scale requires us to deliver pioneering approaches to cloud security, which we pass on to our Google Cloud customers. We are committed to solving hard security problems like only Google can, as the tip of the spear of innovation and threat intelligence.

Today we’re excited to share the next step in this journey with the completion of our acquisition of Mandiant, a leader in dynamic cyber defense, threat intelligence and incident response services. Mandiant shares our cybersecurity vision and will join Google Cloud to help organizations improve their threat, incident and exposure management.

Combining Google Cloud’s existing security portfolio with Mandiant’s leading cyber threat intelligence will allow us to deliver a security operations suite to help enterprises globally stay protected at every stage of the security lifecycle. With the scale of Google’s data processing, novel analytics approaches with AI and machine learning, and a focus on eliminating entire classes of threats, Google Cloud and Mandiant will help organizations reinvent security to meet the requirements of our rapidly changing world.

We will retain the Mandiant brand and continue Mandiant’s mission to make every organization secure from cyber threats and confident in their readiness.

Context and threat intelligence from the frontlines

Our goal is to democratize security operations with access to the best threat intelligence and built-in threat detections and responses. Ultimately, we hope to shift the industry to a more proactive approach focused on modernizing Security Operations workflows, personnel, and underlying technologies to achieve an autonomic state of existence – where threat management functions can scale as customers’ needs change and as threats evolve.

Today Google Cloud security customers use our cloud infrastructure to ingest, analyze and retain all their security telemetry across multicloud and on-premise environments. By leveraging our sub-second search across petabytes of information combined with security orchestration, automation and response capabilities, our customers can spend more time defending their organizations.

The addition of Mandiant Threat Intelligence—which is compiled by their team of security and intelligence individuals spread across 22 countries, who serve customers located in 80 countries—will give security practitioners greater visibility and expertise from the frontlines. Mandiant’s experience detecting and responding to sophisticated cyber threat actors will offer Google Cloud customers actionable insights into the threats that matter to their businesses right now. We will continue to share groundbreaking Mandiant threat research to help support organizations, even for those who don’t run on Google Cloud.

Advancing shared fate for security operations

Google Cloud operates in a shared fate model, taking an active stake in the security posture of our customers. For security operations that means helping organizations find and validate potential security issues before they become an incident.

Detecting, investigating and responding to threats is only part of better cyber risk management. It’s also crucial to understand what an organization looks like from an attacker’s perspective and if an organization’s cybersecurity controls are as effective as expected.

By adding Mandiant’s attack surface management capabilities to Google Cloud’s portfolio, organizations will be able to continually monitor assets for exposures, enabling intelligence and red teams to move security programs from reactive to proactive to understand what’s vulnerable, misconfigured and exposed.

Once an organization’s attack surface is understood, validating existing security controls is critical. With Mandiant Security Validation, organizations will be able to continuously validate and measure the effectiveness of their cybersecurity controls across cloud and on-premise environments.

Transforming security operations and incident response

Security leaders and their teams often lack the resources and expertise required to keep pace with today’s ever changing threats. Organizations already harness Google’s security tools, expert advice and rich partner ecosystem to evolve their security program. Google’s Autonomic Security Operations also serves as a prescriptive solution to guide our customers through this modernization journey.

With the addition of Mandiant to the Google Cloud family, we can now offer proven global expertise in comprehensive incident response, strategic readiness and technical assurance to help organizations mitigate threats and reduce business risk before, during and after an incident.

In addition, Google Cloud’s security operations suite will continue to provide a central point of intelligence, analysis and operations across on-premise environments, Google Cloud and other cloud providers. Google Cloud is also deeply committed to supporting our technology and solution partners, and this acquisition will enable system integrators, resellers and managed security service providers to offer broader solutions to customers.

Comments on the news

“The power of stronger partnerships across the cybersecurity ecosystem is critical to driving value for clients and protecting industries around the globe. The combination of Google Cloud and Mandiant and their commitment to multicloud will further support increased collaboration, driving innovation across the cybersecurity industry and augmenting threat research capabilities. We look forward to working with them on this mission.” – Paolo Dal Cin, Global Lead, Accenture Security

“Google’s acquisition of Mandiant, a leader in security advisory, consulting and incident response services will allow Google Cloud to deliver an end-to-end security operations suite with even greater capabilities and services to support customers in their security transformation across cloud and on-premise environments.” – Craig Robinson, Research VP, Security Services, IDC

“Bringing together Mandiant and Google Cloud, two long-time cybersecurity leaders, will advance how companies identify and defend against threats. We look forward to the impact of this acquisition, both for the security industry and the protection of our customers.” – Andy Schworer, Director, Cyber Defense Engineering, Uber

We welcome Mandiant to the Google Cloud team, and together we look forward to helping security teams achieve so much more in defense of their organizations. You can read our release and Kevin Mandia’s blog for more on this exciting news.

Blog

Taking Maps Further: New Website Experience for Product Discovery, Budgeting and Access to Dev Documentation

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As new technologies emerge and customer preferences evolve, businesses and users of Google Maps Platform can leverage its brand new 'website experience' to explore products and solution that meet their objectives! Learn More.

For more than 15 years, developers have used Google Maps Platform to deliver location-based experiences to their end users and used location intelligence to optimize their businesses. Along this journey, we’ve made a variety of changes to better support our community as needs have changed and new industries and technologies have emerged. We started rolling out a new website experience, at https://mapsplatform.google.com, to help you better understand the products and solutions best suited to address your objectives. Plus, now you can directly connect to the developer documentation for each product to get started quickly, and you can visualize usage and associated costs to have a better idea of what to expect before getting started. 

Getting to your solution faster 

Maps, Routes, Places are building blocks that let you develop implementations for any use case. Building for specific use cases, however, typically requires using a combination of APIs and SDKs. To help you quickly understand what’s possible and what you need to build for your use case, you can now visit the solutions tab to select from a list of popular use cases or industries. Once you’ve selected a use case or industry, you’re taken to a page where you can explore relevant products, read helpful blog posts, see how other customers have deployed for similar use cases, and more.  

Find the ideal location

Direct access to developer documentation

Did you know there are more than a thousand pages of developer documentation created to help you get started, unblock you when you’re stuck, and share best practices? Now when you explore a product or solution from the Google Maps Platform website, you can easily navigate back and forth between our website and documentation. Just tap on JS, iOS, Android or API under the product name to get to the documentation you need. 

Link to documentation

Budgeting for your project

To help you calculate pricing for your project, we’ve introduced a new pricing calculator. Once you find the product and API or SDK you plan to use, pull the slider to reflect your estimated number of monthly requests. This will automatically update the “monthly cost” column for each product and API or SDK you plan to use. If your estimated monthly requests exceed the slider limit, contact our sales team to ​​learn about volume discounts that start at 20% off. 

Pricing calculator

We hope our new website makes it easier to discover our products and solutions, estimate your budget, and start building with our documentation so you can deliver helpful experiences to your users and optimize your business. 

For more information on Google Maps Platform, visit https://mapsplatform.google.com.

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Latest Enhancements in reCAPTCHA Enterprise Helps Govts Sites Protect against Digital Frauds

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The Google Cloud reCAPTCHA Enterprise expands bot detection to safeguard public sector websites from a range of digital frauds and automated attacks. Read this blogpost to boost website security with the reCAPTCHA Enterprise handbook!

Download our guidebook to learn how reCAPTCHA Enterprise can help strengthen your website security quickly.

Cyber threats on the rise


In 2021, the United States saw 40.5% of website attacks committed through “bad bots” on the internet, with 37.2% of government website traffic being bad bots, according to research by cybersecurity firm Imperva1. As cyber threats increase, government agencies need a way to safely let constituents access digital services. Google Cloud reCAPTCHA Enterprise protects websites by distinguishing between humans and bots. Full-scale implementation of reCAPTCHA Enterprise solution expands on bot detection to protect public sector websites from a broad range of digital fraud. Below are some highlights from our new reCAPTCHA Enterprise guidebook detailing functional enhancements and ways for government agencies to take advantage of enterprise capabilities.

Advanced website protection


reCAPTCHA Enterprise builds upon the existing reCAPTCHA API that has defended 5+ million websites for over a decade. It uses advanced risk analysis techniques to distinguish between humans and bots, protecting sites from spam and abuse as well as detecting other fraudulent activities, including credential stuffing, account takeovers (ATO), and automated account creation.

How it works


Detecting password leaks and credential breaches
With reCAPTCHA Enterprise’s password leak protection, agencies can conduct regular audits of user credentials, such as passwords, to detect leaks and breaches and prevent account takeovers (ATOs), as well as credential stuffing attacks.

UI challenge vs. frictionless
reCAPTCHA Enterprise returns a score, giving you the ability to take a number of actions, including requiring additional factors of authentication or throttling bots that may be scraping content. This functionality allows you to verify if an interaction is legitimate without any user interaction.

User-friendly migration
Google Cloud’s reCAPTCHA Enterprise offers a simple migration process in which your account is moved from the reCAPTCHA Admin to the Google Cloud Platform (GCP) after you create a project to migrate it to. Watch our 10-minute webinar to see how.

A cost-effective upgrade to a standard cybersecurity solution
Google reCAPTCHA Enterprise comes with 99.9%+ uptime, multi-factor authentication, and support for Android, iOS, and web applications. Our reCAPTCHA offering is structured in a way that allows you to fully control your investment and responsibly allocate taxpayer dollars.

reCAPTCHA Enterprise in action


Google Cloud’s reCAPTCHA protects against key automated attacks, including account creation, credential stuffing, cashing out, denial of inventory, and skewing. State governments have found success with using Google Cloud’s reCAPTCHA for cyber risk management. Wisconsin’s Workforce Development Agency used fraud detection and identification, including reCAPTCHA, to mitigate malicious bot logins on its external website, and several agencies in the Commonwealth of Pennsylvania have implemented reCAPTCHA to prevent bots from booking and reselling COVID-19 vaccine appointments.

Protecting public sector websites from bad actors can be challenging, especially with emerging threats from adversaries and extremist groups. Google Cloud’s reCAPTCHA Enterprise offers comprehensive website security solutions to successfully protect against cyber threats.

Download our reCAPTCHA Enterprise guidebook for a detailed look at how you can use reCAPTCHA Enterprise to strengthen your website security and implement the solution quickly and easily.

References:

  1. Bad Bot Report 2021: The Pandemic of the Internet

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The {$persona} Survival Guide: A Roadmap for Successful Transformation

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Transform your security strategy with the {$persona} Survival Guide. Get answers to vital questions and achieve success in today's rapidly changing landscape. Empower your organization with a solid security foundation.

Part of being a security leader whose organization is taking on a digital transformation is preparing for hard questions – and complex answers – on how to implement a transformation strategy.

In our previous CISO Survival Guide blog, we discussed how financial services organizations can more securely move to the cloud. We examined how to organize and think about the digital transformation challenges facing the highly-regulated financial services industry, including the benefits of the Organization, Operation, and Technology (OOT) approach, as well as embracing new processes like continuous delivery and required cultural shifts.

As part of Google Cloud’s commitment to shared fate, today we offer tips on how to ask the right questions that can help create the conversations that lead to better transformation outcomes for your organization. While there often is more than one right answer, a thoughtful, methodical approach to asking targeted questions and maintaining an open mind about the answers you hear back can help achieve your desired result. These questions are designed to help you figure out where to start and where to end your organization’s security transformation. By asking the following questions, CISOs and business leaders can develop a constructive, focused dialogue which can help determine the proper balance between implementing security controls and fine-tuning the risk tolerance set by the executive management and the board of directors.

To start the conversation, begin by asking:

  • What defines our organization’s culture?
  • How can we best integrate the culture with our security goals?

CISOs should ask business leaders:

  • What makes a successful transformation?
  • What are the key goals of the transformation?
  • What data is (most) valuable?
  • What data can be retired, reclassified, or migrated?
  • What losses can we afford to take and still function?
  • What is the real risk that the organization is willing to accept?

Business leaders should ask CISOs and the security team:

  • What are the best practices for protecting our valuable data?
  • What is the business impact of implementing those controls?
  • What are the top threats that we need to address?

CISOs and business leaders should ask:

  • Which threats are no longer as important?
  • Where could we potentially use spending for more cost-effective controls such as firewalls and antivirus software?
  • What benefits do we get from refactoring our applications?
  • Are we really transforming, or lifting and shifting?
  • How should we perform identity and access management to meet our business objectives?
  • What are the core controls needed to ensure enterprise-level performance for the first workloads?

CISOs and risk teams should ask:

  • How can we use the restructuring of an existing body of code to streamline security functions?
  • How should we monitor our security posture to ensure we are aligned with our risk appetite?

Business and technical teams should ask:

  • What’s our backup plan?
  • What do we do if that fails?

Practical advice and the realities of operational transformation

Some organizations have been working in the cloud for more than a decade and have already addressed many operational procedures, sometimes with painful lessons learned along the way. If you’ve been operating in the cloud securely for that long, we recognize that there’s a lot to be gained from understanding your approaches to culture, operational expertise, and technology.

However, there are still many organizations that have not thought through how they will operate in a cloud environment until it’s almost ready – and at that point, it might be too late. If you can’t detail how a cloud environment will operate before its launch, how will you know who should be responsible for maintaining it?

Who are the critical stakeholders, along with those responsible for engineering and maintaining specific systems, who should be identified at the start of the transformation? There are likely several groups of stakeholders, such as those aligned with operations for transformation, and those focused on control design for cloud aligned with operations.

If you don’t have the operators involved in the design phase, you’re destined to create clever security controls with very little practical value because those tasked with day-to-day maintenance most likely won’t have the expertise or training to effectively operate these controls.

This is complicated by the fact that many organizations are struggling to recruit and retain resources with the right skills to operate in the cloud. We believe that training current employees to learn new cloud skills, and giving them the time away from other responsibilities, can help build skilled, diverse cloud security teams.

If your organization continually experiences high turnover in security leadership and skilled staff, it’s up to you to navigate your culture to ensure greater consistency. You can, of course, choose to supplement internal knowledge with trusted partners – however, that’s an expensive strategy for ongoing operational cost.

We met recently with a security organization that turns over skilled staff and leadership every two to three years. This rate of churn results in a continual resetting of security goals. This particular team joked that it’s like “Groundhog Day” as they constantly re-evaluate their best security approaches yet make no meaningful progress. This is not a model to emulate.

Many security controls fail not because they are improperly engineered, but because the people who use them – your security team – are improperly trained and insufficiently motivated. This is especially true for teams with high turnover rates and other organizational misalignments. A security control that blocks 100% of attacks might be engineered correctly, but if you can’t efficiently operate it, the effectiveness of the control will plummet to zero over time. Worse, it then becomes a liability because you incorrectly assume you have a functioning control.

In our next blog, we will highlight several proven approaches that we believe can help guide your security team through your organization’s digital transformation.

To learn more now, check out:

Case Study

Case Study: How Exabeam Unlocked its Ability to Scale for Storage & Ingest Data from More Than 500 Security Vendors

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Exabeam, a leader in SIEM and XDR, harnesses the power of Google Cloud products including BigQuery, Dataflow, Looker, Spanner and Bigtable enabling its customers to search multi-year data and detect threats in seconds.

Editor’s note: The post is part of a series highlighting our awesome partners, and their solutions, that are Built with BigQuery.

Exabeam, a leader in SIEM and XDR, provides security operations teams with end-to-end Threat Detection, Investigation, and Response (TDIR) by leveraging a combination of user and entity behavioral analytics (UEBA) and security orchestration, automation, and response (SOAR) to allow organizations to quickly resolve cybersecurity threats. As the company looked to take its cybersecurity solution to the next level, Exabeam partnered with Google Cloud to unlock its ability to scale for storage, ingestion, and analysis of security data.

Harnessing the power of Google Cloud products including BigQuery, Dataflow, Looker, Spanner and Bigtable, the company is now able to ingest data from more than 500 security vendors, convert unstructured data into security events, and create a common platform to store them in a cost-effective way. The scale and power of Google Cloud enables Exabeam customers to search multi-year data and detect threats in seconds


Google Cloud provides Exabeam with three critical benefits.

  • Global scale security platform. Exabeam leveraged serverless Google Cloud data products to speed up platform development. The Exabeam platform supports horizontal scale with built-in resiliency (backed by 99.99% reliability) and data backups in three other zones per region. Also, multi-tenancy with tenant data separation, data masking, and encryption in transit and at rest are backed up in the data cloud products Exabeam uses from Google Cloud.
  • Scale data ingestion and processing. By leveraging Google’s compute capabilities, Exabeam can differentiate itself from other security vendors that are still struggling to process large volumes of data. With Google Cloud, Exabeam can provide a path to scale data processing pipelines. This allows Exabeam to offer robust processing to model threat scenarios with data from more than 500 security and IT vendors in near-real time.
  • Search and detection in seconds. Traditionally, security solutions break down data into silos to offer efficient and cost-effective search. Thanks to the speed and capacity of BigQuery, Security Operations teams can search across different tiers of data in near real time. The ability to search data more than a year old in seconds, for example, can help security teams hunt for threats simultaneously across recent and historical data.

Exabeam joins more than 700 tech companies powering their products and businesses using data cloud products from Google, such as BigQuery, Looker, Spanner, and Vertex AI. Google Cloud announced the Built with BigQuery initiative at the Google Data Cloud Summit in April, which helps Independent Software Vendors like Exabeam build applications using data and machine learning products. By providing dedicated access to technology, expertise, and go-to-market programs, this initiative can help tech companies accelerate, optimize, and amplify their success.

Google’s data cloud provides a complete platform for building data-driven applications like those from Exabeam — from simplified data ingestion, processing, and storage to powerful analytics, AI, ML, and data sharing capabilities — all integrated with the open, secure, and sustainable Google Cloud platform. With a diverse partner ecosystem and support for multi-cloud, open-source tools, and APIs, Google Cloud can help provide technology companies the portability and the extensibility they need to avoid data lock-in.

To learn more about Exabeam on Google Cloud, visit www.exabeam.com. Click here to learn more about Google Cloud’s Built with BigQuery initiative.

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