Papers for

security hardware designers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Conditional imaging preserves privacy while enabling later image recovery

Conditional Imaging for Privacy-Preserving Visual Sensing

Abstract: Conventional visual sensing faces a fundamental dilemma: information that should remain private today may need to be recovered tomorrow. This challenge is becoming increasingly important as cameras become pervasive in our daily surroundings. Existing safeguards either protect visual content only after an image is formed or suppress information during capture in ways that prevent its later recovery. Here, we show through an information-theoretic analysis that privacy and recoverability cannot be achieved simultaneously in static optical systems. Information preserved in a measurement for later reconstruction also remains available to an observer of that measurement, limiting the privacy such systems can provide. To overcome this limitation, we introduce conditional imaging, an imaging approach that changes the optical state for every captured frame. The measurement alone conceals the scene, while knowledge of the corresponding physical system state enables its reconstruction. We analyze how the optical parameters determine the information that can be recovered and use this analysis to guide the design of a camera prototype. We evaluate the system on a captured dataset of human faces using increasingly powerful attempts to recover the scene, from direct visualization and computational inversion to learned reconstruction and identity recognition. Our experiments show that conditional imaging preserves identity in authorized reconstructions while withholding visual information from observers without access to the system state. By making the physical state of the camera part of the information needed for reconstruction, conditional imaging enables visual information to be protected at the point of capture while remaining recoverable for future authorized use.

Tue 20 OctComputer Vision and Pattern Recognition
The gist
Traditional cameras either protect privacy by hiding details when taking a picture, or let you recover lost details later, but not both. The authors show it’s impossible for normal cameras to keep information private and also allow perfect recovery. They introduce a new way called conditional imaging that changes the camera’s settings for every photo, so without extra secret knowledge, the image looks unclear. But with the secret info about the camera’s state, you can reconstruct the private image later. This approach was tested on human faces, showing it keeps identities private from casual viewers while allowing authorized users to see the images clearly.
Open → 2610.28835v1

Fpga speeds up client-side homomorphic encryption encoding and encryption

A Combined Streaming FPGA Architecture for Client-Side CKKS Encoding and Encryption

Abstract: Homomorphic encryption allows a computing service to process encrypted data, but the client must first encode and encrypt its inputs. Sharing hardware between floating-point encoding and modular encryption reduces area but requires those transform roles to execute at different times. We present a streaming FPGA architecture for CKKS encoding and encryption that computes the shared floating-point encoding transform once and performs the integer transforms for six residue moduli in parallel. Dedicated transform pipelines exchange intermediate results on chip rather than through off-chip memory. DSP Builder generates the transform RTL, and Altera HLS IP Gen compiler compiles the surrounding SYCL pipeline into IP integrated with DMA and control logic in an accelerator functional unit. At polynomial degree N = 8192, the Altera Agilex 7 implementation delivers 5,143 complete ciphertexts per second at 471 MHz. One SEAL-Embedded CPU worker on the same workstation delivers 113 ciphertexts per second for real-valued inputs using all 4,096 slots. Measurements cover prepared-input computation through complete ciphertext construction, including FPGA submission and output delivery.

Mon 19 OctCryptography and SecurityHardware Architecture
The gist
Homomorphic encryption lets you perform calculations on data while keeping it secret, but preparing the data first takes time. The authors created a special FPGA design that shares hardware efficiently to speed up this preparation step called CKKS encoding and encryption. Their design processes parts both sequentially and in parallel on the chip, avoiding slow memory use. This makes encrypting millions of data points faster than typical CPU software solutions.
Open → 2610.27204v1