iOS 18 introduces homomorphic encryption for some Siri features, allowing on-device processing of encrypted audio requests without decrypting them first. This enhances privacy by preventing Apple from accessing the raw audio data. Specifically, it uses a fully homomorphic encryption scheme to transform audio into a numerical representation amenable to encrypted computations. These computations generate an encrypted Siri response, which is then sent to Apple servers for decryption and delivery back to the user. While promising improved privacy, the post raises concerns about potential performance impacts and the specific details of the implementation, which Apple hasn't fully disclosed.
The blog post "Homomorphic Encryption in iOS 18" by Bastian Bohm details the introduction of homomorphic encryption capabilities within Apple's iOS 18 operating system, specifically focusing on the newly available APIs for performing calculations on encrypted data without requiring decryption. The author expresses excitement about this development, highlighting the potential for enhanced privacy and security in various applications.
The post begins by explaining the concept of homomorphic encryption, emphasizing its ability to process encrypted information directly, thus preserving the confidentiality of sensitive data. It distinguishes between Fully Homomorphic Encryption (FHE), which supports arbitrary computations, and Partially Homomorphic Encryption (PHE), which is limited to specific operations like addition or multiplication. The post clarifies that iOS 18 implements PHE, specifically focusing on additive homomorphic encryption.
The core of the post revolves around the newly introduced SecKeyEncryptedData class and its associated methods. The author provides a concise code example demonstrating how to create encrypted integers using this class and how to perform homomorphic addition on these encrypted values. The resulting sum remains encrypted, and only the holder of the decryption key can reveal its true value. The author meticulously breaks down the code snippet, explaining the role of each function and parameter. For instance, the post elucidates the process of generating a public key specifically designated for encrypted data operations and how this key is subsequently used to encrypt integer values. It also explains the significance of the perform method in executing homomorphic operations on these encrypted integers.
Furthermore, the post discusses the underlying cryptographic scheme employed by Apple, revealing that it leverages a variant of the Paillier cryptosystem. This choice is deemed suitable for integer additions and is acknowledged for its established security properties. The post also touches upon the practical limitations of PHE, specifically noting the inability to perform other operations like multiplication or comparison directly on the encrypted data without decryption.
Finally, the author speculates on the potential applications of this technology within the Apple ecosystem. The example given is privacy-preserving data collection, suggesting how homomorphic encryption could enable the aggregation of user statistics without compromising individual data privacy. This could be useful for applications like collecting usage metrics or accumulating health data while ensuring that the individual contributions remain confidential. The author concludes with an optimistic outlook on the future implications of homomorphic encryption within the iOS environment and expresses anticipation for further advancements in this field.
Summary of Comments ( 121 )
https://news.ycombinator.com/item?id=42666959
Hacker News users discussed the practical implications and limitations of homomorphic encryption in iOS 18. Several commenters expressed skepticism about Apple's actual implementation and its effectiveness, questioning whether it's fully homomorphic encryption or a more limited form. Performance overhead and restricted use cases were also highlighted as potential drawbacks. Some pointed out that the touted benefits, like encrypted search and image classification, might be achievable with existing techniques, raising doubts about the necessity of homomorphic encryption for these tasks. A few users noted the potential security benefits, particularly regarding protecting user data from cloud providers, but the overall sentiment leaned towards cautious optimism pending further details and independent analysis. Some commenters linked to additional resources explaining the complexities and current state of homomorphic encryption research.
The Hacker News post titled "Homomorphic encryption in iOS 18" spawned a modest discussion with a handful of comments focusing on the practicalities and limitations of the technology, rather than the announcement itself. No one expressed outright excitement or skepticism about the announcement, instead offering pragmatic observations.
One commenter pointed out that the homomorphic encryption being utilized is limited to integer addition and multiplication, and thus isn't fully homomorphic encryption (FHE) in the broader, more powerful sense. They clarified that true FHE allows arbitrary computation on encrypted data, which is not what Apple is implementing. This comment served as an important clarification to distinguish the specific type of homomorphic encryption being employed.
Another user expanded on this by mentioning that the specific technique used is called "additive homomorphic encryption" and likely leverages the Paillier cryptosystem. This added technical depth to the discussion, providing a potential underlying mechanism for Apple's implementation. They then speculated about its use case, suggesting it could be applied to scenarios like federated learning or aggregated metrics collection.
A subsequent comment explored the performance limitations of homomorphic encryption. The commenter noted the significant computational overhead associated with these techniques, which makes them unsuitable for many real-time or performance-sensitive applications. This comment highlighted the trade-offs involved in using homomorphic encryption, emphasizing that while it offers enhanced privacy, it comes at the cost of performance.
Finally, one commenter linked to a related project called "Concrete," further adding context to the types of operations and optimizations possible within the homomorphic encryption space. This provides an avenue for those interested in learning more about practical implementations and advancements in the field.
Overall, the comments section offers a concise and informed discussion focusing on the technical nuances of Apple's implementation rather than broad speculation or hype. They provide valuable context and clarification regarding the specific type of homomorphic encryption being used and its inherent limitations.