4 Cloud Security Trends to Watch Out for in 2022
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When it comes to cloud security, 2022 will be the year that the past catches up with the future. Trends that businesses have been ignoring for too long will force organizations large and small to confront and control their security debt.
That’s according to Google Cloud’s own cybersecurity experts, who have identified four security trends that organizations need to watch out for—and get ahead of. We have predictions on what to expect in the coming year from MK Palmore, director of the Office of the CISO; Brian Roddy, vice president of engineering for Cloud Security; Tim Dierks, engineering director for data protection; and Panos Mavrommatis and Vikram Makhija, senior directors of security engineering for Google Cloud.
Supply chain shenanigans
“We will see continued asymmetric attacks from adversaries as they exploit supply chains and other previously ‘trusted’ third-party entities,” says Palmore.
Supply-chain problems in cloud computing should be easily solvable, right? Software versions and any vulnerabilities they contain should be trackable and patchable, but the reality of fixing software is that “just patch it” is hard to execute—just look at the challenges posed by the Log4j 2 vulnerability. Supply chain is such a huge problem that President Biden addressed it in an Executive Order in May 2021. Customers can expect the issue to be top of mind at Google Cloud.
Not exactly many happy returns (to the office)
“Return to office around the world will drive changes as office infrastructure has not been invested in for a year and a half while the focus has been on remote users. This likely will drive a short-term boom in traditional on-prem security, but it will be the last boom for that as people adapt their remote, zero-trust style strategies to a more modern on-prem approach,” says Roddy.
The misconception that on-prem infrastructure is categorically more secure than cloud is driven by the desire to have physical access to servers and backups so that only the organization which owns the data controls it and has access to it, even in cases of a catastrophic failure or successful cyberattack. In the early years of cloud computing, that may even have been true. But the conditions that drove the myth of on-prem security primacy changed years ago, and the needs driving secure cloud infrastructure help ensure that cloud stays more secure.
Paying down your security debt
“While there’s all the new hotness of cutting-edge concerns, many enterprises still carry security risks and security debt from not yet fully adopting controls which have been broadly accepted as important for years. For example, loads of companies are still not using phishing-resistant two-factor authentication such as FIDO keys,” says Dierks.
Authentication keys such as those made by Yubico and Google’s own Titan Security key support the zero-trust security principles that require user identities to be authenticated, authorized, and then continuously validated before they can access applications and data. Strong authentication is such an important part of contemporary user security that even weaker forms of it that rely on text messages are significantly more secure than not using it at all. That said, why use a less-secure standard when you can reduce risks to your data and bottom line even further by requiring a phishing-resistant hardware key?
Dierks stresses another challenging but important part of eliminating security debt: using social connections to encourage best security practices. “It’s important for CISOs to use their business relationships to emphasize the importance of baseline controls [such as 2FA] for their partners. Enterprises have close relationships that attackers can leverage, so it’s critical that partners hold each other accountable to maintain high security.”
KYD (Know Your Data)
The impact of a data breach can harm organizations as they currently are as well as far into the future. Current tough-to-crack encryption standards protecting data could become easier to decode in the years ahead, so even if cybercriminals can’t access stolen data now there’s no guarantee that paradigm will hold. This means it’s crucially important that organizations understand what data they’re storing, how they’re storing it, and where they’re storing it, say Mavrommatis and Makhija.
“You can’t secure what you don’t know about, and not all data breaches are equal. Stolen machine logs are not as bad as customer data. But how many security teams know the difference? So you have to crawl your own data to automatically classify and discover where sensitive data lives,” they say.
Makhija adds that the shared fate model requires the cloud providers and cloud customers to have a mutual understanding of the quantitative risks each faces. “Shared fate models will pick up significantly in 2022,” he says, as more organizations move to the cloud, and those already using cloud infrastructure improve their security postures.
“To date, there’s been a disparate set of tools for understanding your posture. It’s difficult for third-party tools to stitch together what cloud services should be providing from the start,” he says.
What you can do to make your organization more secure
One cloud security trend that’s ever-present is the ever-increasing importance of keeping cloud deployments secure. As cloud infrastructure becomes more commonplace across businesses and industries of all sizes, it will continue to grow as an attractive target for cybercriminals and other threat actors.
- Because enterprise data has expanded exponentially, the ability to identify and detect threats have become increasingly challenging. To better secure the enterprise software supply chain, use advanced threat detection and analysis tools—especially those designed to catch anomalies.
- The faster that organizations adopt a zero-trust architecture, the more secure the new normal can be. Zero trust helps limit the blast radius of any potential intrusion, while maximizing new enterprise access expectations. Part of adopting zero trust means many end-users can abandon legacy technology like VPNs, but the benefits of segmentation and context-aware access for both identity and device will make all the difference for large scale enterprises. When coupled with a full zero-trust approach and the use of a zero-trust maturity model for improvement, organizations will be better positioned to manage their digital risks.
- Security debt can come in many forms and one critical payoff that needs to be made is for organizations to migrate en masse to hardware two-factor authentication keys. They make user accounts significantly more resistant to takeovers, and are much harder to circumvent than two-factor authentication over SMS.
- It’s past time to get to know your data, and a bouquet of flowers and a bottle of red wine won’t help. There are third-party tools that can do this, but for Google Cloud customers who use BigQuery there’s automatic Data Loss Prevention. It continuously monitors existing tables and profiles new ones; it can be customized for selected folders or projects, or for an entire organization; and it generates data profiles in the same geographic region as the original data.
Understanding and managing the security challenges of cloud infrastructure helps maximize its benefits, and makes for a safer security landscape in 2022—and beyond.
How to Evolve Security for the Cloud: McKinsey with Google Cloud
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Not too long ago, McKinsey released a report titled “Making a secure transition to the public cloud,” the result of interviews with IT security experts at nearly 100 enterprises around the world.
Leveraging the expertise of Google Cloud and McKinsey security experts, the research presents a strategic framework for IT security in cloud and hybrid environments, and provides recommendations on how to migrate to the cloud while keeping security top of mind.
The research shows what many already know: that public cloud adoption is accelerating thanks to increased technical flexibility, simpler scaling, and lower operating costs.
What’s exciting is that the research also reveals that many Chief Information Security Officers (CISOs) no longer view security as an inhibitor to adoption but instead an opportunity.
“In many cases [CISOs] acknowledge that cloud service providers’ security resources dwarf their own,” the authors write—and now these companies are focused on how to best adopt and configure cloud services for increased security.
The research identifies three common archetypes for perimeter security: backhauling, cleansheeting, and adopting cloud provider controls by default.
- Backhauling allows companies to continue managing IT security on-prem, with an external gateway connecting the data center to the public cloud. Approximately half of the companies surveyed currently use this model, but only 11% plan to continue doing so, since it can keep companies from realizing certain cloud benefits, such as agility.
- Cleansheeting requires greater investment and expertise, as it calls for redesigning IT security around a “virtual perimeter” and leveraging multiple cloud-native tools and services.
- Using cloud provider controls is the most cost-effective solution, but—depending on the cloud provider—can limit autonomy and may offer limited capabilities.
McKinsey uses these three models, along with the decision to re-architect applications for the cloud, to identify six “archetypes” for cloud security. Each archetype has its own tradeoffs.
The report also includes a tactical 10-step plan for successful cloud migration. Download it now.
Google Cloud Leads the Landscape for Unstructured Data Security Platform: Forrester
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As organizations expand their use of cloud computing services, more of their sensitive data inevitably moves to and lives in the cloud. Much of this sensitive data is unstructured and can be challenging to secure. Despite this potential challenge, the usefulness of cloud for data storage and processing is too big for most organizations to ignore and has in turn led to data sprawl, where their sensitive data is spread over many resources, both in the cloud and on-premise. Addressing data sprawl requires solutions that can discover, manage, and secure sensitive data, especially unstructured data, as it spreads.
To help organizations confidently move their sensitive data to the cloud, Google Cloud works diligently to earn and maintain customer trust. Control and transparency are pillars of our approach to offering a trusted cloud. Therefore, we’ve been expanding our capabilities to act on unstructured data as sprawl increases.
Given the importance of these capabilities to our strategy, we are happy to announce today that Forrester Research has named Google Cloud a Leader in The Forrester Wave™: Unstructured Data Security Platforms, Q2 2021 report, and rated Google Cloud highest in the current offering category among the providers evaluated.
The report evaluates the 11 most significant providers with platform solutions to secure and protect unstructured data, spanning from cloud providers to data security-focused vendors. The report notes that “Google offers breadth and depth with built-in data security in the cloud. Google Cloud Platform, Google Workspace, and BeyondCorp Enterprise have underlying data security products and features for protecting customer data.”
Google Cloud tools focused on protecting unstructured data were developed and battle-tested internally at Google to alleviate some of our own data security challenges. This brings the best of Google security to the organizations utilizing Google Cloud and our security tools. The report highlights that “Google productizes capabilities originally developed to secure its own business, and brings a disciplined approach to product enhancements for enterprise requirements. It serves a wide range of enterprise and mid-market, with a focus on emphasizing data protection needs by industry. ”
Google Cloud’s data security strategy focuses on meeting customers wherever they are in their cloud migration journey. The report highlights that “Google further enables a Zero Trust approach with third-party integrations through its BeyondCorp Alliance of partners in device management, endpoint security and gateways.”
Google Cloud received the highest possible score in sixteen criteria, in total receiving the most 5 out of 5 ratings among all vendors assessed. These criteria include: Data Intelligence, Access Control, Deletion, Obfuscation-Scope, Obfuscation-Key Management, Deployment, Security and Risk, APIs and Integration, Data Security Platform Vision, Data Security Execution Roadmap, Performance, Planned Enhancements, Zero Trust Enabling Partner Ecosystem, Diversity, Equity and Inclusion, Installed Base, and Revenue.
Notably, Google Cloud received the highest possible score in the Obfuscation criteria. Obfuscation can help protect sensitive data, like personally identifiable information (PII), which is critical to many enterprise workflows. Cloud DLP helps customers inspect and mask this sensitive data with techniques like redaction, bucketing, and tokenization, which help strike the balance between risk and utility. This is especially crucial when dealing with unstructured or free-text workloads, in which it can be challenging to know what data to redact. More than 150 detectors combine to power Cloud DLP’s masking, which can be deployed in data migrations and business workloads like real-time data collection and processing. For Obfuscation specifically, the report mentioned that Google “takes a broad view of DLP, which includes in-line redaction of sensitive elements in unstructured data and DLP APIs that extend support to additional data types like images or other media.”
We are honored to be a Leader in The Forrester Wave™ Unstructured Data Security Platforms Q2 2021 report, and look forward to continuing to innovate and partner with you on ways to make your digital transformation journey safer as we work to become your most trusted Cloud.
A copy of the full report can be viewed here.
Embracing Confidential Computing: Secure Your Data in the Cloud
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As one of the most trusted cloud platform providers, Google is committed to providing our clients secure and reliable environments for their workloads. Google believes the future of computing will increasingly shift to private, encrypted services where users can be confident that their data is not being exposed to cloud providers or their own insiders. Confidential Computing helps make this future possible by keeping data encrypted in memory, and elsewhere outside the CPU, while it is being processed.
Since our first Confidential Computing offering in 2018, Google has been a pioneer in making the technology widely available through our cloud, while also constantly adding new features that allow a wide range of organizations to benefit from it.
Expanding the Confidential Computing portfolio
Today at the RSA Conference 2023, we are announcing several exciting updates to our Confidential Computing portfolio.
We are expanding our portfolio with the next generation of our Confidential Computing VM instances that utilize AMD Infinity Guard technology, specifically AMD SEV-SNP (Secure Encrypted Virtualization-Secure Nested Paging). SEV-SNP adds additional new hardware-based security protections such as strong memory integrity protection and hardware rooted attestation. Confidential VMs on general purpose N2D VMs with SEV-SNP enabled are now in Private Preview. Learn more in our deep dive here.
“Advanced, hardware-based security features – such as AMD Infinity Guard built into AMD EPYC processors – are a crucial part of cloud offerings and the further expansion of cloud computing,” said Ram Peddibhotla, corporate vice president, Cloud Business, AMD. “Our work with Google Cloud delivers on the leadership security features our joint customers demand with nearly effortless implementation and minimal performance impact as more mission critical and business critical workloads move to the cloud.”
Google is committed to ensuring Confidential Computing technology is as secure as possible before releasing products to customers. We constantly evaluate various attack vectors to make certain that Google Cloud Confidential Computing environments are protected against a wide range of attacks.
Throughout last year, Google and Intel collaborated on a research project to identify potential security vulnerabilities in Intel’s new Confidential Computing technology, Trust Domain Extensions (TDX). We’ve recently released the full report and made it available in our blog here.
“We want to make it such that people don’t worry about the security and trustworthiness of their data,” said Anil Rao, vice president and general manager of systems architecture and engineering in the Office of the CTO at Intel. “Organizations use confidential computing to control their data and provide access to trusted parties in a manner that is verifiable, revocable and time sensitive – we have an obligation to make sure the technology is secure. Our early effort with Google solidifies our commitment to perform thorough analysis to address all potential vulnerabilities.”
Confidential Space is now in general availability. Confidential Space builds on Confidential Computing and provides a secure enclave, also known as a Trusted Execution Environment (TEE). Google Cloud customers can leverage the TEE for various privacy-focused use cases such as joint data analysis and machine learning (ML) model training, with trust guarantees that data can stay protected — including hardened protection against cloud service provider access.
Confidential Space allows for new privacy-preserving technologies to take shape, and one such technology is The Privacy Sandbox. This is a crucial step forward as Privacy Sandbox for the Web will phase out third-party cookies and limit covert tracking. By supporting a choice of trusted execution environments, including Confidential Space, the Privacy Sandbox will provide ad-techs with safer alternatives to existing technology, so they can continue building digital businesses while keeping user data private.
“Trusted Execution Environments (TEEs) are already in use across industries such as digital advertising to enable privacy preserving analytics, and we are excited to leverage Google Cloud’s built-in TEE called Confidential Space,” said Gaurav Bhaya, vice president and general manager, Google Ads Measurement.
Building on our history of innovation with Confidential Computing
Google has worked diligently with internal and external partners to validate, audit and publish the security assessment of the hardware, firmware, and software that underpins Confidential Computing.
Last year, a joint security effort between Google Project Zero, Google Cloud, and AMD led to more secure technology for the entire industry, regardless of what service provider you choose for your Confidential Computing deployment. You can learn more in our full report here.
Since then, we have continued to expand the portfolio of Confidential Computing products and services, including Confidential Virtual Machines (CVMs), Confidential GKE, Confidential Dataproc, and Confidential Space. These offerings give our customers more choice in their deployments.
Currently, our Confidential Computing services are widely available across 80% of Google Cloud regions and growing, and we recently added support for Compute-Optimized C2D VMs for Confidential GKE.
Organizations are now leveraging Confidential Computing for joint data analysis and machine learning (ML) model training with trust guarantees that the data they own stays protected and across various other industries by organizations, including AstraZeneca, Bullish, HashiCorp, Matrixx Software, MonetaGo and Yellowdog.
Confidential Computing has also proven to be a helpful additional control for organizations implementing digital sovereignty strategies, providing an encryption capability, and protection for data-in-use where encryption keys are not accessible by the cloud provider.
We can’t wait to see the possibilities this technology will open up for your organization. Check out our Confidential Computing page to learn more.
New ML-Powered API Abuse Detection
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API security incidents are increasingly common and disruptive. With the growth of API traffic, enterprises across the world are also experiencing an uptick in malicious API attacks, making API security a heightened priority. According to our latest API Security Research Report, 50% of organizations surveyed have experienced an API security incident in the past 12 months and of those, 77% delayed the rollout of a new service or application.
At the RSA Conference 2023 today, we’re making it faster and easier to help detect API abuse incidents with the introduction of Advanced API Security Machine Learning powered abuse-detection dashboards. Our newly introduced Machine Learning models are trained to detect business logic attacks.
These types of attacks are notoriously hard to identify, and target APIs tied to intellectual property, business processes, or sensitive information, such as user data, listing of goods, or crediting accounts. These APIs must be accessible to provide business value, but have also become targets for attackers.
API security incidents can have a considerable impact on an organization’s operations and its bottom line. In June 2022, Imperva released a report titled Quantifying the Cost of API Insecurity, which estimates that lack of secure APIs could result in an average annual API-related total global cyber loss of between $41 billion to $75 billion annually. Furthermore, according to IBM’s 2022 Cost of a Data Breach Report, the average cost of a data breach is $4.35 million. It’s vital that organizations detect and mitigate API abuse incidents early to prevent prolonged fiscal and reputational damage to the business.
However, business logic attacks are harder to detect using static security policies, which allows attackers to manipulate legitimate functionality to achieve a malicious goal without triggering any static security alerts. For example, if a malicious actor gains control of a server and makes subtle changes, the shift in activity patterns of the server is generally undetectable to most monitoring tools. However, in this scenario, the Advanced API Security’s ML-powered API abuse detection model can help differentiate between legitimate and deviant traffic and immediately notify key stakeholders to act quickly and minimize blast radius of the problem.
The ML models that power API abuse detection have been trained and used by Google’s internal teams to help protect our public-facing APIs. The models rely on years of learning and best practices and are now available to all Apigee Advanced API Security customers.
Another challenge in detecting API abuse incidents is the volume of alerts. To reduce the risk of missing key security incidents, many static rules that detect less sophisticated attacks are incredibly sensitive: They generate a high volume of alerts. This makes finding the critical incidents within API traffic and acting to resolve them like “finding a needle in a haystack” for many IT teams. Apigee Advanced Security’s ML-powered dashboards more accurately identify critical API abuses and find similar patterns within the large number of bot alerts to help reduce the time to find and act on most important incidents.
With the help of Apigee Advanced API Security’s ML-powered abuse detection dashboards, customers can uncover critical API abuse incidents, including business logic attacks, scraping, and anomalies, faster. Critical threats are surfaced with clear and concise descriptions to capture the essence of the attack along with the most important characteristics such as the source of the attack, the number of API calls, and the duration of the attack, to help resolve the incident more rapidly.
Machine Learning powered abuse-detection dashboards are available in Advanced API Security, a feature of Apigee API management that enables you to more easily detect API security misconfigurations, bad bots, and malicious activities.
To get started with Advanced API Security’s ML-powered dashboards, start your free Apigee trial now.
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Hear from SAP customers who have deployed on Google Cloud and the game changing results they are realizing.
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