IP Library › Granted Patent US 11,210,512
Granted Patent B2
US 11,210,512 · App. 16/257,606 · Granted Dec 28, 2021

Fingerprinting of physical objects

Inventors: Joseph Ligman (Wilton, CT); Venkat K. Balagurusamy (Suffern, NY)
Assignee: International Business Machines Corporation
G06K9/00577H04L9/0637H04L9/0643G06K2009/00583
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Quick Facts
Patent No.
US 11,210,512
App. No.
16/257,606
Granted
Dec 28, 2021
Kind
B2
Abstract

An example operation may include one or more of scanning, by a mobile node, a physical object to generate a scan data, extracting, by the mobile node, a set of features from the scan data, generating, by the mobile node, a feature vector based on the set of the features, applying, by the mobile node, a cryptographic hash function to the feature vector to produce a hash value, encrypting, by the mobile node, the set of the features with the hash value, and executing a smart contract to store the encrypted set of the features on a blockchain.

Claims (51)

1. A mobile node in a blockchain network, the mobile node comprising:

a memory storing one or more instructions; and

a processor that when executing the one or more instructions is configured to:

cause the mobile node to scan a physical object to generate a scan data;

extract a set of features from the scan data;

generate a feature vector including a set of linear equations based on the set of the features;

create an encrypted fingerprint of the physical object based on a cryptographic hash of the set of linear equations;

and

store the encrypted fingerprint in a blockchain of the blockchain network based on a smart contract.

2. The system of claim 1 , wherein the processor is further configured to:

acquire the scan data through a lens adapter attached to the mobile node.

3. The system of claim 2 , wherein the processor is further configured to:

extract a set of unique characteristics from an image of the physical object magnified by the lens adapter.

4. The system of claim 3 , wherein the processor is further configured to:

generate the feature vector based on the set of the unique characteristics.

5. The system of claim 1 , wherein, when the processor is configured to create the encrypted fingerprint, the processor is further configured to:

apply the cryptographic hash using a cryptographic hash function.

6. The system of claim 5 , wherein the cryptographic hash function is any of:

MD4, MD5, SHA1, or SHA2.

7. A method, comprising:

scanning, by a mobile node, of a blockchain network, a physical object to generate a scan data;

extracting, by the mobile node, a set of features from the scan data;

generating, by the mobile node, a feature vector including a set of linear equations based on the set of the features;

creating, by the mobile node, an encrypted fingerprint of the physical object based on a cryptographic hash of the set of linear equations;

and

storing, by the mobile node, the encrypted fingerprint in a blockchain of the blockchain network based on a smart contract.

8. The method of claim 7 , further comprising:

acquiring the scan data through a lens adapter attached to the mobile node.

9. The method of claim 8 , further comprising:

extracting a set of unique characteristics from an image of the physical object magnified by the lens adapter.

10. The method of claim 9 , further comprising:

generating the feature vector based on the set of the unique characteristics.

11. The method of claim 7 , wherein the creating the encrypted fingerprint further comprises:

applying the cryptographic hash using a cryptographic hash function.

12. The method of claim 7 , wherein the cryptographic hash function is any of:

MD4, MD5, SHA1, or SHA2.

13. A non-transitory computer readable medium comprising one or more instructions that when executed by a processor of a mobile node of a blockchain network cause the processor to perform:

scanning of a blockchain network, a physical object to generate a scan data;

extracting a set of features from the scan data;

generating a feature vector including a set of linear equations based on the set of the features;

creating an encrypted fingerprint of the physical object based on a cryptographic hash of the set of linear equations;

and

storing the encrypted fingerprint in a blockchain of the blockchain network based on a smart contract.

14. The non-transitory computer readable medium of claim 13 , wherein the one or more instructions further cause the processor to perform:

acquiring the scan data through a lens adapter attached to a mobile node.

15. The non-transitory computer readable medium of claim 14 , wherein the one or more instructions further cause the processor to perform:

extracting a set of unique characteristics from an image of the physical object magnified by the lens adapter.

16. The non-transitory computer readable medium of claim 15 , wherein the one or more instructions further cause the processor to perform:

generating the feature vector based on the set of the unique characteristics.

17. The non-transitory computer readable medium of claim 13 , wherein the creating the encrypted fingerprint further comprises:

applying the cryptographic hash using a cryptographic hash function.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 25, 2019
From: LIGMAN, JOSEPH; BALAGURUSAMY, VENKAT K.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 048136/0860 →
Continuity (1)
Related Publication 20200242354A1 · Jul 30, 2020