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Sands Capital Sponsors CAMLIS Conference

CAMLIS brings together leading practitioners and researchers from around the world to discuss applied and fundamental research on machine learning in information security.



October 2022

Over the past decade, breakthroughs in automation and analytics have enabled whole new generations of advanced systems such as electric vehicles, smart devices, global social applications, and massive cloud computing environments. Unfortunately, we are still learning how to detect and defend against abuses and misuses of, and attacks on, these complex systems.

Developing new machine learning for cybersecurity is critical to closing this gap and ensuring the security of the systems that we rely upon.

The importance of these efforts is why Sands Capital is proud to sponsor and host the Conference on Applied Machine Learning in Cybersecurity (CAMLIS) conference again this year. We believe that machine learning is critical to securing the infrastructure running our world and that innovation in this area creates opportunities at a global scale.

Cybersecurity Increasingly Affects Everyday Lives, Even During a Pandemic

The critical need for machine learning-based cybersecurity isn’t a topic most people think about daily. But its importance becomes evident when incidents and compromises are discovered.

Even during the height of the pandemic, cybersecurity was a common front-page story.

• In December 2020, SolarWinds, a U.S. information technology company, was hit by a cyberattack launched by foreign hackers that affected SolarWinds clients and was undetected for up to nine months. By deploying a malicious code that compromised a popular software application, the hackers were able to spy on private security companies and various departments of the U.S. government, including the Department of Homeland Security and the Department of the Treasury.

• In April 2021, hackers gained entry to a network owned by Colonial Pipeline, which operates the largest fuel pipeline in the United States. The attack led to fuel shortages across the East Coast and demonstrated how criminals looking to extort money from their cyber victims could put a major portion of the U.S. fuel supply at risk.

• In November 2021, the discovery of the Log4j vulnerability illustrated how the weakness of a single popular open-source software library can undermine the security of an untold number of systems ranging from routers deployed by a company 10 years ago to the doorbell camera shipped to your home yesterday.

These incidents were severe because they compromised infrastructure and undermined capabilities that were relied upon and trusted by a large number of parties. Before these incidents, most people were unaware of how vulnerable systems are to such attacks or the impact a compromise would have on businesses and our daily lives.

The Scale and Complexity of the Problem Demands Machine Learning

There are millions of digital cogs, subsystems, network connections, and lines of software within our society’s modern infrastructure. Understanding and actively monitoring all of them is not feasible. The scale and complexity of this problem is simply too large to solve using traditional approaches and manual effort.

Securing complex systems requires automation and the use of machine learning. Machine learning enables analytics that can identify normal, anomalous, and malicious activity. This is the type of information that system defenders need to detect attacks and prevent compromises. The need for machine learning-based cybersecurity exists today, and it gets larger every time new technologies are deployed.

That’s why researchers are actively developing machine learning techniques and algorithms for cybersecurity. It’s also why Sands Capital sponsors and hosts the CAMLIS conference.

CAMLIS brings together researchers from around the world to collaborate and share ideas on how machine learning can be used to solve real-world cybersecurity problems. The conference provides a forum for practitioners to discuss how they’re using advanced machine learning to detect cybersecurity problems and thwart attacks.

Cybersecurity Innovation Creates Opportunity

The innovation presented and discussed at CAMLIS offers true value for businesses, consumers, and investors. The systems we rely on every day are increasingly complex. Securing them is a daunting and complex task, but it’s essential. That’s why cybersecurity is not only a global problem but also a global opportunity.

Cybersecurity enables us to deploy technology at scale and to rely upon it. Although many people view cybersecurity as onerous or costly, advances in cybersecurity have enabled new revenue opportunities from entirely new industries, including smartphones, cloud computing, and ecommerce.

The CAMLIS conference focuses on cybersecurity innovations that we believe are critical today and for the next generation of industries.


The views expressed are the opinion of Sands Capital and are not intended as a forecast, a guarantee of future results, investment recommendations, or an offer to buy or sell any securities. The views expressed were current as of the date indicated and are subject to change. This material may contain forward-looking statements, which are subject to uncertainty and contingencies outside of Sands Capital’s control. Readers should not place undue reliance upon these forward-looking statements. There is no guarantee that Sands Capital will meet its stated goals.

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