Deploying applications on cloud servers is increasingly popular due to their cost-efficiency and ease of management. However, these servers are controlled by companies that users may hesitate to trust with sensitive data. To keep sensitive data safe, Confidential Computing Environments (CCEs) use a mix of secure hardware and software to protect data from the cloud platform's operating system and other untrusted software. While companies like Intel, ARM, and AMD have improved the hardware for these systems, the associated software remains insufficient to protect modern cloud applications completely. This project aims to solve this problem by designing better software, studying security weaknesses, and creating new ways to block attacks from malicious software. A central idea in our project is to "hide" real data by mixing it with extra, meaningless (“noise”) data to confuse attackers. The research will test these solutions in different cloud setups for popular applications like AI training, recommendation systems, and data analysis tools. Securing cloud applications is a key challenge for computing, and our work, if successful, will positively impact the security of cloud computing platforms. Confidential Computing Environments (CCEs) leverage a combination of trusted hardware and software to protect application data confidentiality and control-flow integrity from untrusted operating systems (OSes) and hypervisors in public cloud settings. While the hardware component has