IP Library Granted Patent US 12,387,002
Granted Patent B2
US 12,387,002 · App. 17/315,309 · Granted Aug 12, 2025

Secure in-memory units for transmitting and receiving encoded vectors for external secure similarity searches

Inventors: Mark Wright (Cupertino, CA); Avidan Akerib (Tel Aviv, IL)
Assignee: GSI Technology Inc.
G06F21/6254G06F18/214G06F18/22G06F21/602G06F21/72G06F21/79G06N3/04G06V10/764
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Quick Facts
Patent No.
US 12,387,002
App. No.
17/315,309
Filed
May 9, 2021
Granted
Aug 12, 2025
Kind
B2
Art Unit
2496
USPC
726/26
Abstract

A system including a secure, in-memory unit implemented on an associative processing unit (APU), for creating encrypted vectors. The in-memory unit includes a data store and an encryptor. The data store stores data and the encryptor encrypts the data into an encrypted vector. Optionally, the unit includes a neural proxy hash encoder that encodes the data into an encoded vector, and, in this embodiment, the encryptor encrypts the encoded vector into an encrypted encoded vector. The neural proxy hash encoder includes a trained neural network which includes a plurality of layers that encode the data into feature sets. The trained neural network encodes image files, audio files, or large data sets. The APU is implemented on SRAM, non-volatile, or non-destructive memory.

Claims (12)

1. A system comprising:

a secure in-memory unit implemented on an associative processing unit (APU), said APU implemented in a memory array having columns, for creating encrypted vectors for secure data transfer to an external similarity searcher, said unit to implement:

an in-memory secure data store to store raw data to be kept secure in said columns;

an in-memory neural proxy hash encoder comprising a trained neural network trained to encode data into binary encoded feature sets having a non-recoverable representation of said raw data, said encoder operative in user-selected ones of said columns to encode user selected ones of said raw data into a binary encoded feature set stored in portions of said columns; and

an in-memory encryptor operative in said portions of said columns to encrypt said binary encoded feature set into an encrypted vector for said secure data transfer.

2. The system of claim 1 said trained neural network to encode at least one of: image files, audio files, and large data sets.

3. The system of claim 1 wherein said APU is implemented on one of: SRAM, non-volatile, and non-destructive memory.

4. A system comprising:

a secure, in-memory unit implemented on an associative processing unit (APU), said APU implemented in a memory array having columns, for securely receiving and decrypting data to be kept secure during a similarity search, said unit to implement:

an in-memory decryptor to decrypt a received encrypted data vector into a secure encoded data vector formed of a binary encoded feature set generated by an external neural proxy hash encoder, wherein said encoded feature set is a non-recoverable representation of user selected raw data to be kept secure; and

an in-memory encoded vector data store to store said secure encoded data vector in said columns among a plurality of previously decrypted secure encoded data vectors, said secure encoded vector to act as a query vector to said similarity search through said previously decrypted secure encoded data vectors.

5. The system of claim 4 wherein said APU is implemented on one of: SRAM, non-volatile, and non-destructive memory.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 24, 2021
From: WRIGHT, MARK; AKERIB, AVIDAN
To: GSI TECHNOLOGY INC.
Reel/Frame 056647/0374 →
Continuity (3)
Provisional Application 63184824 · May 6, 2021
Provisional Application 63026155 · May 18, 2020
Related Publication 20210357515A1 · Nov 18, 2021
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