In the present, confidential computing - the ability to protect data and applications in use by running them inside secured enclaves may come across as the latest tech-industry buzzword that only the top embedded experts are aware of. However, this is only half true. In reality, confidential computing is already at forefront of numerous groundbreaking use cases. However, the concept isn't as well-known because of an absence of understanding of the concept, what it does and how it functions. The organizations need to adopt a different approach in today's environment where rising security concerns and high-visibility threats collide with the "go faster" push to cloud and DevOps. Enter AWS Nitro Security, where it helps businesses run more efficiently and makes work possible that previously seemed impossible. It has the potential to give security teams the ability to tackle issues that businesses didn't believe were possible. What is confidential computing?It is best to focus on the data in order to protect it in a data-driven world. On a basic level data is able to exist in three different states. When it's being stored, it's "at rest" and when it's being processed and used, it's "in use" while travelling across networks, it's "in the process of moving." Nowadays, the best security practices employ encryption to secure information when it's not in use or traveling across networks. That data, however, is still vulnerable to unauthorized access and tampering during processing or running. It is essential to safeguard the data throughout its use for security throughout the data's entire existence. Confidential computing secures data as well as the programs that process those data by running it in secure enclaves that isolate both code and data from unauthorized access - even when the infrastructure for computing has been compromised. Hardware-backed, hardware-backed techniques are utilized to offer greater security and protection for execution of code as well as data protection in Confidential Computing environments (TEE). What Can I Do With Confidential Computing? Many creative uses for secure computing have already demonstrated its potential. As security and privacy issues, it is difficult to help in sharing sensitive data in real-time , while still meeting strict compliance regulations. Technology is already helping accelerate the introduction of new medicines at a lower cost. Consilient uses the technology to combat fraud in the financial sector by utilizing machine learning and an confidential cloud software model which permits AI training without centralizing data. This means that financial institutions and government agencies can more accurately identify malicious activity, which lowers false-positive rate and increases the efficiency of risk management for legitimate companies. Then, there's the UC San Francisco Center for Digital Health Innovation's efforts to accelerate the development and validation of clinical algorithm. In healthcare, securing the approval of regulators for clinical artificial intelligence (AI) algorithms requires diverse and detailed clinical information - it's the only way to build an algorithm that is unbiased, efficient and reliable. algorithm models. Businesses can utilize untrusted infrastructure, such as cloud services or other hosted environments that have high-level encryption on the hardware to run sensitive data and applications. This significantly improves control over the security and privacy of the applications and data inside and outside of their security perimeter and can prevent networks from becoming compromised. It's simple: companies should encrypt their information and take care of their keys or somebody else could. What is the best time to start Confidential Computing? As the above example from UCSF illustrates, the quick answer to this question is "now." But aside from using it to secure AI in healthcare there are many other practical use cases. This includes protecting in-use data to support machines learning models, as well as securing blockchain , and providing anonymous and secure analytics across a variety of data sets. One trend that just about every business wants to address is using the mountains of data they collect. Most people think that data siloed can only be valuable when it is integrated with other data. In addition most data is classified as confidential, which means that there must be safeguards implemented.
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February 2023
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