According to the current state of affairs, confidential computing - the ability to secure the data and programs that are used by running them within secured enclaves may appear as the next tech-industry buzzword that only the top embedded experts know about. But this is only half the truth. In reality, the concept of confidential computing is already at the forefront of several new applications. However, the concept isn't yet prevalent due to an absence of knowledge about what it is and how it works, and how it works. Organizations need a new strategy in the current environment, with increasing security risks and high-visibility attacks collide with the "go faster" shift to cloud computing and DevOps. Enter confidential cloud, where security helps businesses run more efficiently and makes work that was previously thought to be impossible. It is able to give security teams the ability to solve problems that businesses didn't believe could be solved. Confidential Computing What is it? The best way to protect your data in a constantly changing world is to rely on an approach that is focused on the data. On a basic level data is able to exist in three different states. When it's being stored in one of these states, it's "at in rest"; when it's being processed, it's "in use" while traveling across the network or network, it's "in transit." Today's security best practices rely on encryption to safeguard data when it's at rest or in transit across networks. The data remains vulnerable to intrusion and manipulation while it's being processed or in the course of running. Therefore, protecting the data while in use is essential for complete protection throughout the entire lifecycle of the data. Confidential computing safeguards data as well as the applications that process the data by running them within secure enclaves which isolate code and data from unauthorised access, even if the compute infrastructure has been compromised. AWS Nitro Enclaves Confidential computing accomplishes this through hardware-based trusted execution environments (TEE) which utilize hardware-backed techniques for increased guarantees of security during code execution and data security within that environment. What is the best way to use Confidential Computing?Confidential computing is already demonstrating its capabilities in a variety of new applications. Leidos utilizes it to build an internet of secure computing environments that expedite clinical drug trials. Leidos cannot communicate important data in real-time due to security and privacy issues. However, it is able to comply with strict compliance regulations. This technology has already helped speed up the release of new medicines available for sale at a lower cost. In addition, Consilient uses the technology to fight financial fraud with machine learning and a secure computing model that allows AI training without centralizing data. Practically this means that governments, organizations and financial institutions are able to detect fraudulent activity more precisely and efficiently, which reduces false-positive rates and improving risk management for legitimate businesses. The UC San Francisco Center for Digital Health Innovation is a collaborative effort to accelerate the development and validation of algorithms for clinical use. To get regulatory approval for clinical AI (AI) in healthcare, you must have an abundance of clinical data. It is the sole way to develop, optimize, and validate objective algorithms. Enterprises can utilize untrusted infrastructure, such as cloud services or other hosted environments to save sensitive information and applications. This vastly improves control over the security and security of applications and data within and outside their established security perimeters and prevents networks from becoming insecure. In the end, organizations need to encrypt their data and maintain their keys or they will be hacked by someone else. When is the best time to start Confidential Computing? As the example above from UCSF indicates, the short answer to this question is "now." However aside from using it to safeguard the healthcare AI market, there are already many other possible uses. It is a good idea to protect the data used in machine learning models, securing blockchains and providing safe and confidential analysis of multiple sets of data. Every business is eager to take on one of the macro trends: the use of the data that it has amassed. The majority of people think that data siloed is only valuable when it is integrated with data from other companies. At the same time, a lot of data is confidential, meaning that there must be safeguards in place. This creates a tradeoff between usability and security. Businesses must be in a position to gain access to and use data to work with others, unlock insights, and keep it secure. It's not an easy order with so many moving parts in play however Azure confidential computing makes it a reality. The bottom line: data is the new gold, however, how do organizations mine it? In the end, as confidential computing as a technology is more widely used and the rate of innovation increases, organizations will come up with innovative and effective methods to put their data to use, eventually making it more valuable.
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