TH58552B - Systems and methods for encoding randomly distributed characteristics in objects. - Google Patents

Abstract

DC60 (08/06/60) System and method described. It is aimed directly at encoding the characteristics that are distributed. Randomly in the object The randomly distributed trait in the authentication object was determined, the randomly distributed trait data was compressed and encoded with a trademark, a trademark label was created and merged. Authentication objects and data encoded data may be encoded by determining function, density, relative probability. With the authentication object Vectors associated with randomly distributed features have been Determined on the basis At least some Of the probability density function Vector has been Encrypted using an arithmetic encryption algorithm. The systems and methods described It is aimed directly at encoding the characteristics that are distributed. Randomly in the object The randomly distributed trait in the authentication object was determined, the randomly distributed characteristic data was compressed and encoded with a trademark. The trademark label was created and merged. Authentication objects and data to be encrypted The data may be encrypted by considering the probability density function relative to the Authentication object Vectors relative to randomly distributed features have been determined on at least some basis. Of the probability density function The vectors have been encoded. By using an arithmetic encryption algorithm

Claims (2)

Disclaimer (ALL) which will not appear on the announcement page: 8 June 2017 1. Methods include determining (410) randomly distributed characteristics in the authentication object (100). Compression (415) The data exhibits a randomly distributed identity. Where is the compression It consists of (505) the probability density function involved in the authentication object. (authentication object) where the function Probability density function represents probability, which is one unit of A randomly distributed trait is found in a particular region of the authentication object. (authentication object) Determining (510) Point-to-point vectors (point-to-point vector) involves The end of the randomly distributed identity basis. At least in the upper part Probability density function and encoding (515) point-to-point vectors. (point-to-point vector) by using an algorithm Arithmetic coding algorithm, which is basically a vector coding using The arithmetic coding algorithm, including determining (520) paths for connecting a part of a point-to-point quadrant. (point-to-point vector) within the data volume. Constant, which is where the path connects points of a point-to-point vector (point-to-point vector), return (525) route as such compressed data, encryption (420), compressed data with a private key and creation (425). ) Trademark labeling including authentication objects and information Is encrypted -------------------------------------------------- -------------------------------------------------- --------------------- what is claimed; 1. A method consists of determining the characteristics that are randomly distributed in the object. Randomly distributed characterization compression. Encoding compressed data with symbolism and trademark labeling which included Objects and data that are encrypted 2. Method, as described in claim 1, where data compression includes determining the function, density, probability associated with the object. Consideration of vectors relative to randomly distributed features based on at least some of the density, probability, and vector coding functions using an arithmetic encoding algorithm. 3. Method, as discussed in claim 2, where vector coding using an arithmetic cipher algorithm includes determining the path for connecting vector parts within a constant volume of data. As explained in claim 2, where randomly distributed characteristics are fibers. That are randomly positioned in the object 5. Method as described in claim 4 where the probability density function is expressed. Probability that a particular area of fiber is illuminated by a light source. 6. Method, as described in claim 4, where the probability density function was Definition based on At least some 7. Method, as described in Proposition 4, where each vector represents the end point of two fibers 8. Method, as described in Proposition 1, where data is encrypted with a section key. Person 9. Method as described in Clause 1, where the trademark label is in support of Formatted Authentication And where the object is Authentication object Actual Authentication is included in the Authentication Section 1 0. Method, as described in claim 1, where the encrypted information is included on the label. Barcode 1 Trademark 1. The method as described in Claim No. 1 also includes: Considering the character information including the character string. Hashing of text data with algorithms Encrypting compressed data using hashed text data and incorporating text into trademark labels 1 2. Method as described in Clause 11, where the algorithm is. Free hashing algorithms Cryptographic Threats 1 3. Method, as described in Claim 11, where an algorithm is a SHAI 1 cryptographic algorithm 4. One or more computer-readable memory containing a word set. Order that can It can be executed by the processor to perform the methods described in Clause 1 1 5. The system consists of the published sections that have been formatted to determine the characteristics that are randomly distributed in the object. Prove yourself And to compress randomly distributed characteristic data. Also published section It is further formatted to encode the compressed data with symbols. And to create a machine pattern Trade marks that include a authentication object. 1 6. System, as outlined in Claim 15, where the published section is still formatted for Consider the probability density function relative to the authentication object to determine the vectors relative to the randomly distributed attribute on the basis. At least some of the probability density functions. And to encode parts of the vector as a path by Applied the Arithmetic Coding Algorithm 1 7. The system, as discussed in claim 15, where the publication continues to be formatted for entry. Data Code Compressed with Private Keys 1 8. System, as described in claim 15, where the publication continues to be formatted to include Barcodes containing information encoded on the trademark label 1. 9. System, as outlined in Claim 15, where the publication is continued to be formatted for. Consider the character data including the string of the alphabet. And to hash the text data with the algorithm 2 0. The system, as described in the claim 19, where the publication is still formatted for access. The secret code, compressed data using hashed character data. And to include text information in the label Trademark 2 1. The system, as outlined in Claim No. 15, is also included. A formatted assertion to decode randomly distributed characteristic information. On the trademark label And to prove the identity of the trademark label by comparing the Data encoded versus real randomly distributed traits considered by object jets. Truthful Proof 2 2. A trademark label contains an authentication object that combines randomly distributed characteristics and an encrypted sermon relative to the authentication object. The sermons are also encrypted. Symbol pattern And includes the compressed data showing the randomly distributed characteristics in the opt. Authentication Jake Where the trademark label proved itself By comparing the compressed information in the substance Encrypted sermons With data showing the randomly distributed traits obtained from the analysis. Authentication Objects 2 3. Trademark label, as described in Claim 22, as stated in the Sermon. Encoded, compressed by Consideration of the probability density function in relation to the authentication object. Consideration of vectors relative to randomly distributed features based on at least some of the density, probability, and vector coding functions. Using an arithmetic encryption algorithm 2 4. The trademark label, as described in Claim 22, where the encrypted information is It has been included in the barcode trademark label 2. 5. Trademark label, as described in Claim No. 22, where the encrypted sermon. It is encrypted using a private key. 2. 6. The trademark label, as described in Claim 22, also includes one. The character data that includes the character string Where the compressed data is encrypted using the text. 2. 7. The trademark label, as described in Clause 26, where the compressed data is encrypted. Encrypted by Algorithm hashing of character data and encryption of compressed data using hashed text data 2 8. Tools consists of tools for compressing randomly distributed characteristics. Tools for encoding data with logos and tools for creating trademark labels that combine authentication objects and encrypted data 2 9. The tools, as described in Claim 28, are continued. Go too A tool for combining fibers in a unique authentication object that has Randomly distributed 3 0. The tools, as outlined in the claim 28, are also included. A tool for pondering the probability density function in relation to the authentication object. A tool for determining vectors relative to a randomly distributed attribute on at least some of the bases. Of probability density functions and tools for entering vectors using algorithms. Arithmetic Coding 3 1. The method, as outlined in the claim, holds the 28th, also continues. A tool for determining the character information that includes a string of characters. A tool for hashing text with algorithms. Tool for encoding compressed data using hashed text data and a tool for inclusion of text into trademark labels 3. 2. The tools, as outlined in Claim 28, are also included. A tool for authenticating trademark labels by comparing entered information. Code and data associated with randomly distributed traits in the authentication object.