Can Confidential Computing Stop the Next Crypto Heist?

Can Confidential Computing Stop the Next Crypto Heist?
Published on

Confidential computing stops crypto heists it protects cryptocurrencies and their users from cyberattacks

Cryptocurrencies are digital assets that use cryptography to secure transactions and control the creation of new units. They are decentralized, meaning that they operate without the need for intermediaries such as banks or governments. However, this also means they are vulnerable to cyberattacks, such as hacking, phishing, or ransomware. In recent years, there have been several incidents of crypto heists, where hackers have stolen millions of dollar worth of cryptocurrencies from exchanges, wallets, or users. For example, in 2014, Mt. Gox, the largest bitcoin exchange, lost 850,000 bitcoins (worth about US$450 million then) due to a security breach. In 2018, Coincheck, a Japanese exchange, was hacked and lost 523 million NEM coins (worth about US$530 million then). In 2021, Poly Network, a cross-chain platform, was exploited and lost US$610 million worth of various cryptocurrencies.

These crypto heists pose a severe threat to the security and trust of the cryptocurrency ecosystem. They also raise the question of how to protect cryptocurrencies and their users from such attacks. One possible solution is confidential computing. Confidential computing stops crypto heists, a cloud computing technology that protects data during processing. Confidential computing technology isolates sensitive data in a secure CPU enclave during processing. The contents of the enclave, the data being processed, and the techniques used to process it are accessible only to authorized programming code. They are invisible and unknowable to anyone, including the cloud provider. Confidential computing uses embedded encryption keys and attestation mechanisms to ensure that only authorized code can access the data and that the code has not been tampered with. If any unauthorized or malicious code attempts to access the data or the keys, the enclave denies access and cancels the computation.

However, confidential computing is not a silver bullet that can stop all crypto heists. Confidential computing relies on hardware-based trusted execution environments (TEEs) and secure enclaves within CPUs. While TEEs are designed to be tamper-resistant and isolated from other system components, they are not immune to vulnerabilities or attacks. These flaws, dubbed Foreshadow and Plundervolt, allowed attackers to bypass SGX's security mechanisms and access data inside enclaves. Moreover, confidential computing does not protect data at rest (in storage) or in transit (over networks), which are also potential targets for crypto heists. Therefore, confidential computing should be used with other security measures, such as rest and transit encryption, multi-factor authentication, firewalls, and backups.

Confidential computing is a promising technology that can protect cryptocurrencies and their users from cyberattacks by encrypting data during processing. However, confidential computing is not a foolproof solution to stop all crypto heists. It has its limitations and challenges, and other security practices should complement it. Therefore, confidential computing is not a definitive answer to whether it can stop the next crypto heist but rather a part of it.

Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

                                                                                                       _____________                                             

Disclaimer: Analytics Insight does not provide financial advice or guidance. Also note that the cryptocurrencies mentioned/listed on the website could potentially be scams, i.e. designed to induce you to invest financial resources that may be lost forever and not be recoverable once investments are made. You are responsible for conducting your own research (DYOR) before making any investments. Read more here.

Related Stories

No stories found.
logo
Analytics Insight
www.analyticsinsight.net