At Google Cloud, we continue to invest in key technologies to progress towards our true north star on invisible security: making strong security pervasive and simple for everyone. Our investments are based on insights from our world-class threat intelligence teams and experience helping customers respond to the most sophisticated cyberattacks. Customers can tap into these capabilities to gain perspective and visibility on the most dangerous threat actors that no one else has. 

Recent advances in artificial intelligence (AI), particularly large language models (LLMs), accelerate our ability to help the people who are responsible for keeping their organizations safe. These new models not only give people a more natural and creative way to understand and manage security, they give people access to AI-powered expertise to go beyond what they could do alone. 

At the RSA Conference 2023, we are excited to announce Google Cloud Security AI Workbench, an industry-first extensible platform powered by a specialized, security LLM, Sec-PaLM. This new security model is fine-tuned for security use cases, incorporating our unsurpassed security intelligence such as Google’s visibility into the threat landscape and Mandiant’s frontline intelligence on vulnerabilities, malware, threat indicators, and behavioral threat actor profiles. 

Google Cloud Security AI Workbench powers new offerings that can now uniquely address three top security challenges: threat overload, toilsome tools, and the talent gap. It will also feature partner plug-in integrations to bring threat intelligence, workflow, and other critical security functionality to customers, with Accenture being the first partner to utilize Security AI Workbench. 

The platform will also let customers make their private data available to the platform at inference time; ensuring we honor all our data privacy commitments to customers. Because Security AI Workbench is built on Google Cloud’s Vertex AI infrastructure, customers control their data with enterprise-grade capabilities such as data isolation, data protection, sovereignty, and compliance support. 

Preventing threats from spreading beyond the first infection

We already provide best-in-class capabilities to help organizations immediately respond to threats. But what if we could not just identify and contain initial infections, but also help prevent them from happening anywhere else? With our AI advances, we can now combine world class threat intelligence with point-in-time incident analysis and novel AI-based detections and analytics to help prevent new infections. These advances are critical to help counter a potential surge in adversarial attacks that use machine learning and generative AI systems. That’s why we’re excited to introduce:  

• VirusTotal Code Insight uses Sec-PaLM to help analyze and explain the behavior of potentially malicious scripts, and will be able to better detect which scripts are actually threats. 
• Mandiant Breach Analytics for Chronicle leverages Google Cloud and Mandiant Threat Intelligence to automatically alert you to active breaches in your environment. It will use Sec-PaLM to help contextualize and respond instantly to these critical findings.

These new updates build on the existing AI in Google’s industry-leading solutions. For example, Chronicle Security Operations already uses frontline intelligence, integrated reasoning, and machine learning to identify initial infections, prioritize impact, and contain threats. Another example is reCAPTCHA Enterprise, which uses image noising capabilities to help protect your site from adversaries that leverage novel AI advances, greatly enhancing our defenses against bots. 

Adding intelligence to reduce toil

At Google Cloud, we help organizations modernize security wherever they are, in part by simplifying their security tools and controls whenever possible. Advances in generative AI can help reduce the number of tools organizations need to secure their vast attack surface areas and ultimately, empower systems to secure themselves. This will minimize the toil it takes to manage multiple environments, to generate security design and capabilities, and to generate security controls. Today, we’re announcing: 

• Assured OSS will use LLMs to help us add even more open-source software (OSS) packages to our OSS vulnerability management solution, which offers the same curated and vulnerability-tested packages that we use at Google.
• Mandiant Threat Intelligence AI, built on top of Mandiant’s massive threat graph, will leverage Sec-PaLM to quickly find, summarize, and act on threats relevant to your organization. 

These announcements build on existing capabilities that help customers centralize visibility and control, detect targets, and improve security across their platform. For example, Security Command Center (SCC) uses always-on machine learning to detect malicious scripts executing in the customer container environment and immediately alert the customer. In addition, Cloud Data Loss Prevention leverages machine learning to find and classify data, and with Confidential Computing you can collaborate on, train, and deploy sensitive and regulated AI models in the cloud, all while preserving confidentiality. 

Evolving how practitioners do security to close the talent gap 

At Google, we believe that to truly democratize security, we need to first acknowledge that AI will soon usher in a new era for security expertise that will profoundly impact how practitioners “do” security. Most people who are responsible for security — developers, system administrators, SRE, even junior analysts — are not security specialists by training. 

Imagine a world where novices and security experts are paired with AI expertise to free themselves from repetition and burnout, and accomplish tasks that seem impossible to us today. To help power this evolution, we’re embedding Sec-PaLM-based features that can make security more understandable while helping to improve effectiveness with exciting new capabilities in two of our solutions: 

• Chronicle AI: Chronicle customers will be able to search billions of security events and interact conversationally with the results, ask follow-up questions, and quickly generate detections, all without learning a new syntax or schema.
• Security Command Center AI: Security Command Center will translate complex attack graphs to human-readable explanations of attack exposure, including impacted assets and recommended mitigations. It will also provide AI-powered risk summaries for security, compliance, and privacy findings for Google Cloud.

These new releases bolster our existing efforts to tackle these issues through capabilities like IAM Recommender, which suggests permissions better suited to actual usage patterns. We will soon be augmenting this capability to cover organizational policies, further enabling the administrator to help improve the security posture of their organization. In addition, Mandiant Automated Defense applies machine learning to help reduce the repetitive Tier 1 alert triage problem and address alert fatigue. 

Offering availability 

VirusTotal Code Insight, available now in Preview, is our first example of putting Security AI Workbench to work for our customers. We will be rolling out other offerings to trusted testers in coming months, and they will be available in Preview more broadly this summer. Click here for the demo. 

Security AI Workbench, including Sec-PaLM and partner integrations, in addition to the product innovations described in our demo, are all building blocks for a larger effort to elevate security across the ecosystem. So far, that effort: 

• Provides assistive functions to rapidly develop IT generalist talent to Tier 1 security operator status in a way that wasn’t previously feasible. Security Command Center now can summarize threat intelligence insights and findings for Google Cloud, and Chronicle can quickly generate YARA-L rules or other detections. 
• Provides advanced functions such as iterative query and multivariate detection generation, conversational filtering and interaction with results, and smart case awareness to empower advanced Tier 2 and 3 security operators to focus on threat analysis instead of struggling with process and toil. Mandiant Threat Intelligence users now can elevate their core competencies to hunt, investigate, and remediate threats — using the same tools our own Mandiant experts use. 
• Fuses threat intelligence and AI-based analytic capabilities, which are unsurpassed in the market. VirusTotal Code Insight enables security teams to help gain insights and identify threats in suspicious code. This can significantly enhance their ability to detect and mitigate potential attacks.

However, this is just an initial step. We’ll continue to iterate and innovate, and we encourage customers and partners to leverage Security AI Workbench in new and exciting ways. Moving forward, we anticipate many new use cases to emerge over time. 

Building a safer future

While generative AI has recently captured the imagination, Sec-PaLM is based on years of foundational AI research by Google and DeepMind, and the deep expertise of our security teams. This work includes new efforts to expand our partner ecosystem to provide businesses with security capabilities at every layer of the cybersecurity stack. We have only just begun to realize the power of applying generative AI to security, and we look forward to continuing to leverage this expertise for our customers and drive advancements across the security community.

Cloud-based solutions were a technology life raft for organizations during the COVID-19 pandemic as employees took to the virtual office and companies scrambled to adjust to a distributed, remote reality. However, these rapid and substantial changes in the role of cloud technologies on the business came with an increased focus on security. 

The accelerated move to the cloud also meant companies needed to rapidly evolve existing security practices to protect everything that matters at the core of business—from their people and their operational and transactional data to customers and their most sensitive personal information. Suddenly, enterprises were keenly aware of where business practices, employee training, and security policies were falling short. 

A recent Google-commissioned study by IDG explored the details behind the heightened focus on security solutions since the start of the pandemic while highlighting the role cloud-based security solutions are playing in helping keep customers safe. The survey of 2,000 global IT leaders serves to illustrate that in this new and unfamiliar world, enterprises are more ready than ever to embrace cloud security.LEARN MOREIT Leaders Research ReportWhat are the biggest IT priorities in 2021? Explore insights from a survey of 2,000 Senior IT leaders conducted by IDG, in collaboration with Google Cloud.

Security is an even higher priority post-pandemic

In the wake of the pandemic, many organizations are facing a broader attack surface than ever before as employees moved to temporarily working from remote home offices (and in some cases, encouraged to stay there for the foreseeable future). With fewer inherent security protections on personal internet connections and more work meetings happening via video conferencing, attackers have launched a cyber pandemic of their own designed to take advantage of and exploit new weaknesses. 

However, even as businesses amp up security initiatives and preventative measures, the growing wave of threats continue to keep security top of mind for IT leaders. Security risks and concerns remain one of the top pain points impeding innovation according to the IDG study respondents—only surpassed by insufficient IT and developer skills. 

Enterprises looking to cloud providers for help with security

As a result, addressing security risks is a leading area where IT leaders turn to cloud providers for support. For these organizations, the ability to control access to data while using cloud services was the most required infrastructure security and compliance features from a cloud provider.

Cloud security is more trusted than ever 

A deeper look into the results also revealed a shift in perspective about whether cloud security is really up to the task of protecting enterprises against modern attacks. Despite skepticism in the past, the majority of IT leaders are now comfortable with using cloud-based security solutions. 

Confidence in the security of cloud infrastructure is extremely high with 85% of respondents stating they feel secure (or more secure) than on-premises infrastructure—compared to just 15% who believe on-premises is still safer.

This is a clear indication that there are fewer reservations around the efficacy of cloud-based security solutions, signaling an increase in trust as organizations invest in cloud-based infrastructure and solutions. 

We are committed to safe, secure solutions 

Google Cloud protects your data, applications, and infrastructure, as well as your customers, from fraudulent activity, spam, and other types of online abuse. We protect you against a growing list of cybersecurity threats using the same infrastructure foundation and security services that we use for our own operations, so you never have to compromise between ease of use and advanced security. 

To learn more about the IDG findings and how IT leaders are addressing security concerns post-COVID, download the full report.

^{Interested in how Google Cloud’s commitment to providing safe, secure solutions helps you address your security needs?}

^{Our networking, data storage, and compute services encrypt data at rest and in transit to ensure the integrity, authenticity, and privacy of your data and your customers’ data. We also offer the ability to encrypt data in use, while it’s being processed in VM and container workloads, and our advanced security tools support compliance and data confidentiality with minimal operational overhead.}

June is the month that holds the summer solstice, and some of us in the northern hemisphere get to enjoy the longest days of sunshine out of the entire year. We used all the hours we could in June to deliver a flurry of new features across BigQuery, Dataflow, Data Fusion, and more.  Let’s take a look!

Simple, Sophisticated, and Secure

Usability is a key tenant of our data analytics development efforts. Our new user-friendly BigQuery improvements this month include:

• Flexible data type casting
• Formatting to change column descriptions 
• GRANT/REVOKE access control commands using SQL

We hope this will delight data analysts, data scientists, DBAs, and SQL-enthusiasts who can find out more details in our blog here.

Beyond simplifying commands, we also recognize that it’s equally important to have more sophistication when dealing with transactions. That’s why we introduced multi-statement transactions in BigQuery.

As you probably know, BigQuery has long supported single-statement transactions through DML statements, such as INSERT, UPDATE, DELETE, MERGE and TRUNCATE, applied to one table per transaction. With multi-statement transactions, you can now use multiple SQL statements, including DML, spanning multiple tables in a single transaction. 

This means that any data changes across multiple tables associated with all statements in a given transaction are committed atomically (all at once) if successful—or all rolled back atomically in the event of a failure. 

We also know that organizations need to control access to data, down to the granular level and that, with the complexity of data platforms increasing day by day, it’s become even more critical to identify and monitor who has access to sensitive data. 

To help address these needs,  we announced the general availability of BigQuery row-level security. This capability gives customers a way to control access to subsets of data in the same table for different groups of users. Row-level security in BigQuery enables different user personas access to subsets of data in the same table and can easily be created, updated, and dropped using DDL statements. To learn more, check out the documentation and best practices.

Simple, Safe, and Smart

Beyond building a simpler, more sophisticated and more secure data platform for customers, our team has been focused on providing solutions powered by built-in intelligence. One of our core beliefs is that for machine learning to be adopted and useful at scale, it must be easy to use and deploy.  

BigQuery ML, our embedded machine learning capabilities, have been adopted by 80% of our top customers around the globe and it has become a cornerstone of their data to value journey.  

As part of our efforts, we announced the general availability of AutoML tables in BigQuery ML.  This no-code solution lets customers automatically build and deploy state-of-the-art machine learning models on structured data. With easy integration with Vertex AI, AutoML in BQML makes it simple to achieve machine learning magic in the background. From preprocessing data to feature engineering and model tuning all the way to cross validation, AutoML will “automagically” select and ensemble models so everyone—even non-data scientists—can use it.   

Want to take this feature for a test drive? Try it today on BigQuery’s NYC Taxi public dataset following the instructions in this blog! 

Speaking of public datasets, we also introduced the availability of Google Trends data in BigQuery to enable customers to measure interest in a topic or search term across Google Search.  This new dataset will soon be available in Analytics Hub and will be anonymized, indexed, normalized, and aggregated prior to publication. 

Want to ensure your end-cap displays are relevant to your local audience?  You can take signals from what people are looking for in your market area to inform what items to place. Want to understand what new features could be incorporated into an existing product based on what people are searching for?  Terms that appear in these datasets could be an indicator of what you should be paying attention to.

All this data and technology can be put to use to deploy critical solutions to grow and protect your business. For example,  it can be difficult to know how to define anomalies during detection. If you have labeled data with known anomalies, then you can choose from a variety of supervised machine learning model types that are already supported in BigQuery ML. 

But what if you don’t know what kind of anomaly to expect, and you don’t have labeled data? Unlike typical predictive techniques that leverage supervised learning, organizations may need to be able to detect anomalies in the absence of labeled data. 

That’s why, we were particularly excited to announce the public preview of new anomaly detection capabilities in BigQuery ML that leverage unsupervised machine learning to help you detect anomalies without needing labeled data.  

Our team has been working with a large number of enterprises who leverage machine learning for better anomaly detection. In financial services for example, customers have used our technology to detect machine-learned anomalies in real-time foreign exchange data.  

To make it easier for you to take advantage of their best practices, we teamed up with Kasna to develop sample code, architecture guidance, and a data synthesizer that generates data so you can test these innovations right away. 

Simple, Scalable, and Speedy

Capturing, processing and analyzing data in motion has become an important component of our customer architecture choices. Along with batch processing, many of you need the flexibility to stream records into BigQuery so they can become available for query as they are written.  

Our new BigQuery Storage Write API combines the functionality of streaming ingestion and batch loading into a single API. You can use it to stream records into BigQuery or even batch process an arbitrarily large number of records and commit them in a single atomic operation.

Flexible systems that can do batch and real-time in the same environment is in our DNA: Dataflow, our serverless, data processing service for streaming and batch data was built with flexibility in mind.  

This principle applies not just to what Dataflow does but also how you can leverage it—whether you prefer using Dataflow SQL right from the BigQuery web UI, Vertex AI notebooks from the Dataflow interface, or the vast collection of pre-built templates to develop streaming pipelines.

Dataflow has been in the news quite a bit recently. You might have noted the recent introduction of Dataflow Prime, a new no-ops, auto-tuning functionality that optimizes resource utilization and further simplifies big data processing. You might have also read that Google Dataflow is a Leader in The 2021 Forrester Wave™: Streaming Analytics, giving Dataflow a score of 5 out of 5 across 12 different criteria.  

We couldn’t be more excited about the support the community has provided to this platform. The scalability of Dataflow is unparalleled and as you set your company up for more scale, more speed, and “streaming that screams”, we suggest you take a look at what leaders at Sky, RVU or Palo Alto Networks have already accomplished.

If you’re new to Dataflow, you’re in for a treat: this past month, Priyanka Vergadia (AKA CloudGirl) released a great set of resources to get you started. Read her blog here and watch her introduction video below!

https://youtube.com/watch?v=WRspZRG9e90%3Fenablejsapi%3D1%26

Simple structure that sticks together

We thrive to be the partner of choice for your transformation journey, regardless where your data comes from and how you choose to unify your data stack.  

Our partners at Tata Consultancy Services (TCS) recently released research that highlights the importance of a unifying digital fabric and how data integration services like Google Cloud Data Fusion can enable their clients to achieve this vision.

We also  announced SAP Integration with Cloud Data Fusion, Google Cloud’s native data integration platform, to seamlessly move data out of SAP Business Suite, SAP ERP and S4/HANA. To date, we provide more than 50 pipelines in Cloud Data Fusion to rapidly onboard SAP data.  

This past month, we introduced our SAP Accelerator for Order to Cash.  This accelerator is a sample implementation of the SAP Table Batch Source feature in Cloud Data Fusion and will help you get started with your end-to-end order to cash process and analytics. 

It includes sample Cloud Data Fusion pipelines that you can configure to connect to your SAP data source, perform transformations, store data in BigQuery, and set up analytics in Looker. It also comes with LookML dashboards which you can access on Github.

Countless great organizations have chosen to work with Google for their SAP data. In June, we wrote about ATB Financial’s journey and how the company uses data to better serve over 800,000 customers, save over CA$2.24 million in productivity, and realize more than CA$4 million in operating revenue through “D.E.E.P”, a data exposure enablement platform built around BigQuery.

Finally, if you are an application developer looking for a unified platform that brings together data from Firebase Crashlytics, Google Analytics, Cloud Firestore, and third party datasets, we have good news!  

This past month, we released a unified analytics platform that combines Firebase, BigQuery, Google Looker and FiveTran to easily integrate disparate data sources,  and infuse data into operational workflows for greater product development insights and increased customer experience. This resource comes with sample code, a reference guide and a great blog!  We hope you enjoy it. See you all next month!

https://youtube.com/watch?v=L25Vfzr2Ciw%3Fenablejsapi%3D1%26

State and local government (SLG) agencies are reeling from a combination of unbudgeted COVID-related expenses and reduced tax revenue caused by unemployment and business closures. Any way you look at it, the situation is challenging. To understand how SLG agencies are coping, Google Cloud collaborated with MeriTalk to survey 200 SLG IT and program managers, uncovering some revealing trends in SLG technology innovation. Unsurprisingly, approximately 84% of SLG organizations report making budgetary tradeoffs to bridge funding the gaps the ongoing pandemic has created. 

However, researchers discovered a silver lining: The pandemic has also been a catalyst to modernize the legacy infrastructure in states and cities. The majority of survey respondents (88%) reported that their agency made greater modernization progress this past year than in the prior 10 years.

Walking a tightrope between innovation and budget pressure

According to 89% of state and local leaders, now is the time to invest in technology modernization. But 80% are experiencing a funding gap due to unbudgeted expenses related to the pandemic and declining tax revenue, which makes finding that balance between innovation and budget a serious challenge.

Some agencies are achieving the impossible, though. For example, the City of Pittsburgh Department of Innovation and Performance is working with Google Cloud to migrate  and modernize its legacy IT infrastructure. By decommissioning their data center and moving to Google Cloud, the city can build new data analytics tools to drive smart city initiatives and create entirely new applications to improve digital service delivery for its residents. As a result, the city will save costs, abandon its brittle legacy IT structure, and create a cloud-based technology platform for the future—becoming the region’s leader in cloud-native software development.

Google Cloud is enabling the city’s IT team by curating and delivering our certification training at no cost. The program includes live training sessions as well as on-demand training. 

Bridging funding gaps

In their drive to modernization, many SLG leaders are turning to grants as an important source of funding. Approximately 84% of those surveyed report making tradeoffs to bridge funding gaps, such as moving resources away from operations and maintenance (37%), increasing reliance on pandemic-related funding (31%), and delaying internal modernization efforts to enable remote work for employees (29%). One way that states are dealing with this tension between budget gaps and the need for innovation is to turn to Google Cloud for cost savings and improved capabilities.

For example, Google Cloud is helping the State of West Virginia innovate and enhance IT security despite decreased state funding. The state entered a multi-year agreement to ensure full access to enterprise-level Google Workspace capabilities for 25,000 state employees, keeping the state at the forefront of technology advancements at a projected cost savings of $11.5 million.

Similarly, Google Cloud helped build the Rhode Island Virtual Career Center to help the state’s constituents get back to work. Using familiar productivity tools within Google Workspace, employees can access new career opportunities quickly, while employers can reach more candidates. Skipper, the CareerCompass RI bot, uses data and machine learning to connect Rhode Islanders with potential new career paths and reskilling opportunities.

Enhancing services

Google Cloud is also helping agencies enhance services, including working with the State of Illinois to get unemployment funding to constituents in need.The state is using Contact Center AI to rapidly deploy virtual agents that help more than 1 million out of work citizens file unemployment claims faster. Capable of engaging in human-like conversations, these intelligent agents provide constituents with 24/7 access and enable government employees to focus on more complex, mission-critical tasks—such as combating fraud. In summer 2020, the virtual agents handled more than 140,000 phone and web inquiries per day, including 40,000 after-hours calls every night. The state anticipates an estimated annual savings of $100 million from the solution, which was deployed in just two weeks.

Working with Google, Ohio also uncovered $2 billion in fraudulent unemployment claims. We will continue to partner with the state to find fraudulent claims, and prioritize the processing of legitimate claims.

 Focusing on cybersecurity

Despite expanding security threats topping NASCIO’s list of 2021 State CIO priorities, more than one in three IT managers (35%) say their organization reduces security measures to expedite timelines. Partnering with Google Cloud has enabled many agencies to enhance their security measures while modernizing and staying within budget, investing in support for remote work devices, digital services for residents, and cybersecurity.

NYC Cyber Command works with city agencies to ensure systems are designed, built, and operated in a highly secure manner. NYC3 followed a cloud-first strategy using the Google Cloud Platform. The virtual operations demanded by the pandemic have increased the importance of security and compliance in SLG. Google Cloud is committed to act as a security transformation partner and be the trusted cloud for public sector agencies. 

Finally, to strengthen public and private partnerships, SLG organizations told MeriTalk that they need vendor partners to support modernization efforts for flexibility and collaboration (46%), need innovation-focused leadership groups to help balance technology needs with budget constraints (41%), and they expect significant returns on investments in cloud computing (38%), and data management/analytics (33%).

Google Cloud is helping SLG customers across the country invest in innovation to walk the tech tightrope—balancing innovation and budgets—and helping to build a more resilient future. Visit the State and Local Government solutions page to learn more.

I’m excited to share our first Cloud CISO Perspectives post of 2022. It’s already shaping up to be an eventful year for our industry and we’re only in month one. There’s a lot to recap in this post, including the U.S. government’s recent efforts to address critical security issues, like open source software security and zero trust architectures. We’ve also released new resources from our Google Cybersecurity Action Team like the Cloud Security Megatrends and the Boards of Directors whitepaper on cloud risk governance. 

Cloud Security Megatrends 

We’re often asked if the cloud is more secure than on-prem (and why) so we shared our answer in a recent blog post. At Google Cloud, security by design is our priority. We’ve long adopted zero-trust principles for our baseline security architectures and built a global network that relies on defense in depth layers to protect against configuration errors and attacks. But security is always evolving and that is why we also take advantage of the following megatrends:

1. Economy of scale: Decreasing the marginal cost of security raises the baseline level of security. 
2. Shared fate: A flywheel of increasing trust drives more transition to the cloud, which compels even higher security and even more skin-in-the-game from the cloud provider.
3. Healthy competition: The race by deep-pocketed cloud providers to create and implement leading security technologies is the tip of the spear of innovation. 
4. Cloud as the digital immune system: Every security update the cloud gives the customer is informed by some threat, vulnerability, or new attack technique often identified by someone else’s experience. Enterprise IT leaders use this accelerating feedback loop to get better protection.
5. Software-defined infrastructure: Cloud is software defined, so it can be dynamically configured without customers having to manage hardware placement or cope with administrative toil. From a security standpoint, that means specifying security policies as code, and continuously monitoring their effectiveness.
6. Increasing deployment velocity: Because of cloud’s vast scale, providers have had to automate software deployments and updates, usually with automated continuous integration/continuous deployment (CI/CD) systems. That same automation delivers security enhancements, resulting in more frequent security updates.
7. Simplicity: Cloud becomes an abstraction-generating machine for identifying, creating and deploying simpler default modes of operating securely and autonomically. 
8. Sovereignty meets sustainability: The cloud’s global scale and ability to operate in localized and distributed ways creates three pillars of sovereignty. This global scale can also be leveraged to improve energy efficiency.

If you’re an IT decision maker, pay attention to these megatrends that will continue to drive and reinforce cloud security and will outpace the security of on-prem infrastructure well into the future. 

U.S. Federal government cybersecurity momentum 

• Open source software security: Earlier this month, Google participated in the White House Summit on open source software security. The meeting came at a critical time for the industry following December’s Log4j vulnerabilities and was both a recognition of the challenge and an important first step towards addressing it. The open source software ecosystem is not homogenous, despite the fact that the industry often thinks of or treats it this way. Some of it, like Linux, is highly curated, while other critical software is supported through diffuse communities including technology companies and other stakeholders. There is also a long tail of many other critical projects driven by a dedicated community of maintainers around the world, including Googlers. In light of this reality, we welcomed the chance to share our recommendations to advance the future of open source software security. Some work we’ve done includes founding the Open Source Security Foundation, which has been instrumental already in making security improvements. We’ve also helped drive a number of key security initiatives within the open source community including security scorecards, the SLSA framework to improve the security and integrity of open source packages, and Secure Open Source Rewards to financially incentivize improvements to critical open source security projects.  
• OMB’s Federal zero trust strategy: The publication of the Office of Management and Budget’s zero trust architecture strategy marks an important step for the U.S. federal government’s efforts to modernize under Executive Order 14028. Google Cloud supports this approach, which recognizes the immense security benefits offered by modern computing architectures. For the past decade, Google has successfully applied zero trust principles through our BeyondCorp and BeyondProd frameworks for providing end-user access and securing our cloud workloads. And we’ve brought these best practices from our own journey to global governments and businesses of any size through solutions like BeyondCorp Enterprise and capabilities like Binary Authorization and Anthos Service Mesh, which are embedded in Anthos, our managed application platform. For Federal agencies embarking on this zero trust journey, the Google Cybersecurity Action Team will offer our expertise by conducting Zero Trust Foundations strategy workshops, which can help organizations in the public and private sectors develop actionable and achievable strategies and plans for zero trust implementation. 

Google Cybersecurity Action Team Highlights 

Here are the latest updates, products, services and resources across our security teams this month: 

Security

• Democratizing security operations: We recently announced that Siemplify, a leading security orchestration, automation and response (SOAR) provider, is joining Google Cloud to help companies better manage their threat response. Providing a proven SOAR capability with Chronicle’s approach to security analytics is an important step forward in our vision to advance invisible security and democratize security operations for every organization.
• Security by design: The Highmark Health security team is using “secure-by-design” techniques to address the security, privacy, and compliance aspects of its Living Health solution with Google Cloud’s Professional Services Organization (PSO). Google has long advocated for and followed security by design principles, which is why we’re continuously building enhanced security, controls, resiliency and more into our cloud products and services. 
• Secure collaboration for hybrid work environments: The Google Workspace team shared its recommendations for businesses as they prepare for the future of work,  where the hybrid/flexible work model is becoming standard practice and a new approach to security is essential.
• Anthos Policy Controller CIS Benchmark enforcement: A big part of our shared fate philosophy is to build secure products and not just security products. A recent example of this in action is embedding CIS benchmark policy conformance in the Anthos Policy Controller. We believe the more we embed approaches like this into our products, the more application and infrastructure teams can intrinsically embed security at the start and reduce toil for the security team.
• DevOps for technology-driven organizations and startups: A key success factor for many security programs is the partnership and integration with development teams, and there are some great resources and lessons in our DORA research.
• Security by design with Chrome OS: ABN AMRO’s Asia-Pacific region team recently shared how they are using Chrome OS and CloudReady to work securely in the cloud, reduce total cost of ownership, and add flexibility for employees. This is a great example of secure by design principles in the use of Chromium.

Risk & Compliance

• Boards of Directors summary guide to cloud risk governance: The latest whitepaper from the Google Cybersecurity Action Team outlines how boards of directors can prioritize safe, secure, and compliant adoption processes for cloud technologies within their organizations.  
• TruSight Risk Assessment of Google Cloud: TruSight recently released a comprehensive
  risk assessment report on Google Cloud. Our Enterprise Trust team collaborated on this robust assessment of Google Cloud services to validate the design and implementation of controls. TruSight’s risk assessment of our security controls will help customers accelerate and complete their risk management due diligence.
• Data governance: Check out this new blog series on data governance where our teams explain the role of data governance, its importance, and the necessary processes to run an effective data governance program. Implementing data governance will help maximize value derived from business data, build user trust, and ensure compliance with required security measures.

Controls and Products

• Encrypting Data Fusion: To help meet the security, privacy and compliance requirements of customers in regulated industries like finance or public sector, we announced the general availability of Customer Managed Encryption Keys (CMEK) integration for Cloud Data Fusion, which enables encryption of both user data and metadata at rest with a key that customers can control through our Cloud Key Management Service (KMS). 

Don’t forget to sign-up for our newsletter if you’d like to have our Cloud CISO Perspectives post delivered every month to your inbox. We’ll be back next month with more updates and security-related news.