FEATURE : CYBERSECURITY
Where might HE be used ?
HE ’ s groundbreaking capability has significant implications for data privacy and security across both the public and private sector , where data theft is still a huge problem , simply because it isn ’ t encrypted during processing .
HE can play a role in securing any sensitive data that needs to be analysed without exposing the actual information .
Take the financial sector , for example . Here , FHE can secure data while complex analyses like fraud detection , credit scoring , and risk assessment are performed . This allows banks to analyse encrypted financial records , ensuring client confidentiality and data integrity , and opens the door to personalised financial services , while adhering to privacy regulations . FHE also facilitates secure data sharing between institutions for anti-fraud purposes , without exposing individual customer data .
For Apple , one of their notable FHE applications is the Live Caller ID Lookup feature in iOS 18 , used to protect your privacy when identifying callers and blocking spam . Basically , it sends an encrypted request to a server to find out who is calling you . The server then processes this encrypted request and sends back an encrypted answer without ever seeing your actual phone number . To make this possible , Apple uses a technique called Private Information Retrieval ( PIR ), which lets you look up private information ( like phone numbers ) without the server knowing what you ’ re looking for . Instead of sending the whole database to your phone ( which is only practical for small databases ), Apple ’ s FHE implementation only sends a small part of the database that rarely changes , making it highly efficient for handling large databases that are updated frequently .
The future of HE
Apple ’ s embrace of FHE will no doubt impact public understanding and perception of this powerful cryptographic technology , in turn helping to promote a more privacy-focused mindset going forwards . But there is still work to be done to make FHE faster and more efficient and broaden its use even more so .
At Zama , for example – where we ’ re using an extension of TFHE as the underlying FHE scheme – we ’ ve reduced the time needed for a key operation from 20 milliseconds to just 3 milliseconds on CPUs and expect to further improve this by 5 to 10 times with new cryptography breakthroughs we ’ re working on . Moving to GPUs and FPGAs should enhance performance by another 5 to 10 times , giving us a potential 100-fold increase in efficiency compared to when we started .
While these improvements are already significant and benefit blockchain and AI applications , we ’ re still working towards achieving an even greater 100-fold performance boost . Once hardware acceleration is addressed , FHE ’ s technical challenges are effectively addressed ; a situation we expect to see by 2026 , seeing FHE widely deployable across various platforms . p
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