DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claims 1-13, 16-17, and 19-23 are pending.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-13, 16-17, and 19-23 are rejected under 35 USC § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 (The Statutory Categories): Is the claim to a process, machine, manufacture or composition of matter? MPEP 2106.03.
Per Step 1, claims 1 and 11 are directed to a method (i.e., a process), claims 16 and 22 are directed to a device (i.e., a machine), and claims 17 and 23 to a non-transitory computer-readable storage medium (i.e., a machine or manufacture). Thus, the claims are directed to statutory categories of invention. However, the claims are rejected under 35 USC § 101 because they are directed to an abstract idea, a judicial exception, without reciting additional elements that integrate the judicial exception into a practical application.
The analysis proceeds to Step 2A Prong One.
Step 2A Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? MPEP 2106.04.
The abstract idea from claims 1, and 16-17 is:
performing a classification on a product information according to a field type of the product information, so as to obtain a numeric field and a text field;
encoding the text field to obtain an encoded field;
generating a field to be processed, according to a random number, the numeric field and the encoded field;
encrypting the field to be processed to obtain an initial anti-forgery field; and
generating a target anti-forgery information according to the initial anti-forgery field and the numeric field.
The abstract idea from claims 11, and 22-23 is :
acquiring, in response to a verification request for a product information being received, the product information and an anti-forgery information corresponding to the product information, wherein the anti-forgery information is generated using the method of claim 1 [encoding the text field to obtain an encoded field;
generating a field to be processed, according to a random number, the numeric field and the encoded field;
encrypting the field to be processed to obtain an initial anti-forgery field; and
generating a target anti-forgery information according to the initial anti-forgery field and the numeric field.];
obtaining an embedding position information of a numeric field according to the product information;
obtaining, from the anti-forgery information, the numeric field and an initial anti-forgery field according to the embedding position information of the numeric field;
decrypting the initial anti-forgery field to obtain a random number, the numeric field and an encoded field;
decoding the encoded field to obtain a text field; and
obtaining a verification result of the product information by comparing the product information with the numeric field and the text field.
The abstract idea steps italicized above recite anti-forgery information generation and verification based on product information, which constitutes a process that, under its broadest reasonable interpretation (BRI), covers commercial activity. This is further supported by [0026] of applicant’s specification as filed. If a claim limitation, under its BRI, covers commercial interactions, including contracts, legal obligations, advertising, marketing, sales activities or behaviors, and/or business relations, then it falls within the Certain Methods of Organizing Human Activity – Commercial or Legal Interactions grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Additionally and alternatively, the claim is directed to manipulation and transformation of information through encoding, encryption, decryption, and comparison operations, which constitutes a process that, under its BRI, covers mathematical concepts. This is further supported by [0027] of applicant’s specification as filed. If a claim limitation, under its BRI, covers mathematical concepts, including mathematical relationships, mathematical formulas or equations, mathematical calculations, then it falls within the Mathematical Concepts grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A, Prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application? MPEP §2106.04.
This judicial exception is not integrated into a practical application because the additional elements are merely instructions to apply the abstract idea to a computer, as described in MPEP §2106.05(f).
Claim 11 recites the following additional elements: querying an anti-forgery information database.
Claim 16 recites the following additional elements: An electronic device, comprising: a processor; and a memory for storing a program, wherein the program is configured to, when executed by the processor, cause the processor to implement the method of claim 1.
Claim 17 recites the following additional elements: A non-transitory computer-readable storage medium having executable instructions therein, wherein the instructions are configured to, when executed by a processor, cause the processor to implement the method of claim 1.
Claim 22 recites the following additional elements: An electronic device, comprising: a processor; and a memory for storing a program, wherein the program is configured to, when executed by the processor, cause the processor to implement the method of claim 11.
Claim 23 recites the following additional elements: A non-transitory computer-readable storage medium having executable instructions therein, wherein the instructions are configured to, when executed by a processor, cause the processor to implement the method of claim 11.
Examiner notes that claim 1 includes no additional elements.
These elements are merely instructions to apply the abstract idea to a computer, per MPEP §2106.05(f). Applicant has only described generic computing elements in their specification, as seen in [0170] – [0180] of applicant’s specification as filed, for example. Further, the combination of these elements is nothing more than a generic computing system.
Accordingly, these additional elements, alone and in combination, do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea.
Step 2B (The Inventive Concept): Does the claim recite additional elements that amount to significantly more than the judicial exception? MPEP §2106.05.
Step 2B involves evaluating the additional elements to determine whether they amount to significantly more than the judicial exception itself.
The examination process involves carrying over identification of the additional element(s) in the claim from Step 2A Prong Two and carrying over conclusions from Step 2A Prong Two on the considerations discussed in MPEP §2106.05(f).
The additional elements and their analysis are therefore carried over: applicant has merely recited elements that facilitates the tasks of the abstract idea, as described in MPEP §2106.05(f).
Further, the combination of these elements is nothing more than a generic computing system. When the claim elements above are considered, alone and in combination, they do not amount to significantly more.
Therefore, per Step 2B, the additional elements, alone and in combination, are not significantly more. The claims are not patent eligible.
Further, the analysis takes into consideration all dependent claims as well:
Regarding claims 2-10, 12-13, and 19-21, applicant further narrows the abstract idea with additional step(s). There are no further additional elements to consider, beyond those highlighted above. This further narrowing of the abstract idea, similar to above, is also not patent eligible.
Accordingly, claims 1-13, 16-17, and 19-23 are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-10, 16-17, and 19-21 are rejected under 35 U.S.C. § 103 as being unpatentable over Arya (US 20150039902) in view of von Mueller (US 20080091944).
Claims 1, 16, and 17
Arya discloses (claim 1 being representative):
(claim 1) A method of generating an anti-forgery information, comprising: {“Digest obfuscation may include translating bits of the hashed value into bit units according to a sparse bit selection pattern, and performing a cypher on the resultant bit units according to a digit cypher, using the bit units as indices into the digit cypher to generate a resultant obfuscated value.” [0009]. This is accomplished by means of methods and systems. [0055]}
(claim 16) An electronic device, comprising: a processor; and a memory for storing a program, wherein the program is configured to, when executed by the processor, cause the processor to implement the method of claim 1. {“The cryptographic computing device 116 may include a processor 118 that executes instructions stored on memory 120, including those of an obfuscation application 122.” [0013]}
(claim 17) A non-transitory computer-readable storage medium having executable instructions therein, wherein the instructions are configured to, when executed by a processor, cause the processor to implement the method of claim 1. {“ A computer-readable medium (also referred to as a processor-readable medium) includes any non-transitory (e.g., tangible) medium that participates in providing data (e.g., instructions) that may be read by a computer (e.g., by a processor of a computer). Such a medium may take many forms, including, but not limited to, non-volatile media and volatile media.” [0052]}
encoding the text field to obtain an encoded field; {The hashing module receives subscriber information and generates a digest (i.e., hash value). [0016], [0027]}
generating a field to be processed, according to a random number, the numeric field and the encoded field; {The system supports using a hash key and/or initialization vector determined by random number generation to generate the digest that is subsequently processed. The digest is generated based on the input information and a randomly generated value. [0016], [0027] – [0028]}
encrypting the field to be processed to obtain an initial anti-forgery field; and {The hashing module performs cryptographic hashing (i.e., encryption) processing on the input data to generate a digest, and the digest may be obfuscated to create a protected identifier. [0027], [0031] – [0032], [0040] – [0042]}
generating a target anti-forgery information according to the initial anti-forgery field and the numeric field. {The obfuscation application generates an obfuscated identifier from the digest through sparse bit selection and digit cipher processing. The final obfuscated identifier is generated from the encrypted digest and may be stored within records alongside other data fields. [0031] – [0032], [0037], [0042] – [0047]}
Arya does not disclose, however, von Mueller, in a similar field of endeavor directed to secure transactions and access authorization, teaches:
performing a classification on a product information according to a field type of the product information, so as to obtain a numeric field and a text field; {The system supports parsing token data into different field types, including numeric account information and other data fields such as expiration date, discretionary data, country code, and name. [0065] – [0074], [0113]}
Therefore, it would have been obvious to one of the ordinary skills in the art to modify the bit pattern selection and translation features of Arya to include the settlement of token access transactions features of von Mueller, to improve the organization and handling of different data types during encryption and decryption operations. (See [0113] of von Mueller).
Claims 2 and 19
The combination of Arya and von Mueller teaches the limitations set forth above. Von Mueller further teaches:
obtaining a field length of the product information according to the numeric field and the encoded field; {The system supports determining the size of the data to be encrypted and generating an encryption block having a corresponding length for use with selected portions of the account data. [0319] – [0329], [0336] – [0337]}
obtaining a target random field from the random number according to the field length and a field length threshold; and {The system supports generating a transaction stream cipher field (Ki) from the counter value (MSC/MKC), expanding an encrypted block into a predetermined number of digits, and selecting a portion of the resulting field of use. [0316] – [0329]}
generating the field to be processed according to the target random field, the numeric field and the encoded field. {The system supports combining the generated stream cipher block Ki with selected account data fields to generate the processed field used for encryption/decryption. [0309] – [0313], [0330]}
The motivation and rationale to include the additional features of von Mueller is the same as set forth previously.
Claims 3 and 20
The combination of Arya and von Mueller teaches the limitations set forth above. Von Mueller further teaches:
determining a length of the numeric field according to the numeric field; {The system supports identifying specific account data fields (e.g., PAN digits, expiration month, service year), each having a defined length. [0309] – [0313], [0330]}
determining a length of the encoded field according to the encoded field; and {The system supports generating encrypted fields having defined lengths, including a 20 digit block Ke and a 19 digit stream cipher block Ki. [0316] – [0329]}
obtaining the field length of the product information according to the length of the numeric field and the length of the encoded field. {The system supports constructing encryption/decryption fields based on the lengths of the account data fields and generated encryption blocks. [0309] – [0313], [0316] – [0330]}
The motivation and rationale to include the additional features of von Mueller is the same as set forth previously.
Claims 4 and 21
The combination of Arya and von Mueller teaches the limitations set forth above. Von Mueller further teaches:
determining a target number of bytes according to the field length and the field length threshold; and {Data is converted into an 8-byte binary value and encrypted data is expanded into a specified number of digits for subsequent processing. [0336]}
obtaining, based on a field query strategy, the target random field from the random number according to the target number of bytes. {The system supports generating the stream cipher field Ki by expanding encrypted block Kd into a 20 digit value and then selecting a subset of digits by dropping the leftmost digit to obtain the 19 digit target field. [0316] – [0329]}
The motivation and rationale to include the additional features of von Mueller is the same as set forth previously.
Claim 5
The combination of Arya and von Mueller teaches the limitations set forth above. Von Mueller further teaches:
determining a query start position and a query direction based on the field query strategy; {The system supports selecting digits from the generated 20 digit field Ke by dropping the leftmost digit to form Ki (i.e., determining a starting position and retrieval direction within the generated field. [0328] – [0329]}
determining a query end position according to the query start position, the query direction and the target number of bytes; and {The system supports retaining the remaining digits of Ke after removal of the leftmost digit to produce the 19 digit field Ki. [0328] – [0329]}
retrieving the target random field from the random number according to the query start position and the query end position. {The system supports obtaining the stream cipher field Ki by selecting a subset of digits from the generated field Ke and subsequently using Ki during encryption and decryption processing. [0309], [0329] – [0330]}
The motivation and rationale to include the additional features of von Mueller is the same as set forth previously.
Claim 6
The combination of Arya and von Mueller teaches the limitations set forth above. Arya further discloses:
generating an information code according to the numeric field and the encoded field; {The hashing module generates a digest and the digit cipher module generates an obfuscated identifier from the encoded information. [0027], [0031] – [0032], [0040] – [0042]}
determining an embedding position information of the target random field; and {The sparse bit selection pattern specifies output bit unit locations for selected bits. [0019], [0023], [0035]}
embedding the target random field into the information code according to the embedding position information, so as to generate the field to be processed. {The sparse bit selection module inserts selected bits into designated output bit unit locations to form the translated digest. [0023], [0031], [0035] – [0036]}
Claim 7
The combination of Arya and von Mueller teaches the limitations set forth above. Arya further discloses:
determining a target key according to the random number by querying an anti- forgery information database; and {The system supports obtaining hash keys from a key server and generating initialization vectors according to random number generation. [0013], [0016], [0027] – [0028]}
encrypting the field to be processed by using the target key, so as to obtain the initial anti-forgery field. {The hashing module uses the hash key to generate a digest from the input information. [0016], [0027] – [0028]}
Claim 8
The combination of Arya and von Mueller teaches the limitations set forth above. Arya further discloses:
determining a target encryption algorithm according to a type of the target key; {The hashing module may implement “hashing algorithm algorithms”, and different keys are used with the selected algorithm. [0027] – [0028]}
and encrypting the field to be processed by using the target key based on the target encryption algorithm, so as to obtain the initial anti-forgery field. {The hashing module uses a selected cryptographic hashing algorithm together with a hash key to generate the digest. [0016], [0027] – [0028], [0040]}
Claim 9
The combination of Arya and von Mueller teaches the limitations set forth above. Arya further discloses:
determining an embedding position information of the numeric field; and {The sparse bit selection pattern specifies output locations for insertion of selected data bits. [0019], [0023]}
embedding the numeric field into the initial anti-forgery field according to the embedding position information, so as to generate the target anti-forgery information. {The sparse bit selection module maps selected data bits into designated output positions to generate the translated digest and resulting obfuscated identifier. [0023], [0031] – [0032]}
Claim 10
The combination of Arya and von Mueller teaches the limitations set forth above. Arya further discloses:
embedding the numeric field into the initial anti-forgery field according to the embedding position information, so as to obtain a target anti-forgery field; {The sparse bit selection module maps selected data bits into designated output positions to generate the translated digest and resulting obfuscated identifier. [0023], [0031] – [0032]}
determining a display type of the target anti-forgery field according to the product information; and {The system supports generating output values according to selected outputs formats such as hexadecimal, base-64, etc. [0018] – [0020], [0031] – [0032]}
processing the target anti-forgery field based on the display type, so as to obtain the target anti-forgery information. {The digit cipher module converts translated digest values according to the selected representation format. [0018], [0032], [0037]}
Claims 11-13, and 22-23 are rejected under 35 U.S.C. § 103 as being unpatentable over the combination of Arya and von Mueller in further view of Dameri (US 20110276502).
Claims 11, 22, and 23
The combination of Arya and von Mueller teaches the limitations set forth above. Von Mueller further teaches (claim 11 being representative):
obtaining, by querying an anti-forgery information database, an embedding position information of a numeric field according to the product information; {“ Thus, encryption module 132 creates track data character strings. Encryption module 132 is further configured to parse this track data to select appropriate portions of this data for encryption.” [0113 ]. “the card BIN number is used to access the encryption parameters and keys.” [0116]}
decrypting the initial anti-forgery field to obtain a random number, the numeric field and an encoded field; {The decryption process retrieves keys, generate decryption block Ki, and reconstructs the cleartext data from the encrypted field. [0316], [0330 ]}
The motivation and rationale to include the additional features of von Mueller is the same as set forth previously.
While the combination of Arya and von Mueller teaches the limitations set forth above, it does not explicitly teach, however, Dameri, in a similar field of endeavor directed to checking the authenticity of a product, teaches:
(claim 11) A method of verifying a product, comprising: {“a computerized system is provided for verifying the authenticity of products”. [0010]}
(claim 22) An electronic device, comprising: a processor; and a memory for storing a program, wherein the program is configured to, when executed by the processor, cause the processor to implement the method of claim 11. {“central processing apparatus 2 schematically includes first and second processing units 6, 8. As it will be readily apparent to a person skilled in the art, each of the first and second processing units 6, 8 includes hardware and/or software elements configured to perform the required functions; in particular, both the first and second processing units 6, 8 may be implemented by the computing core 3 (e.g. running special adapted computer program products and dedicated software instructions stored on machine readable media). [0022]}
(claim 23) A non-transitory computer-readable storage medium having executable instructions therein, wherein the instructions are configured to, when executed by a processor, cause the processor to implement the method of claim 11. {“central processing apparatus 2 schematically includes first and second processing units 6, 8. As it will be readily apparent to a person skilled in the art, each of the first and second processing units 6, 8 includes hardware and/or software elements configured to perform the required functions; in particular, both the first and second processing units 6, 8 may be implemented by the computing core 3 (e.g. running special adapted computer program products and dedicated software instructions stored on machine readable media). [0022]}
acquiring, in response to a verification request for a product information being received, the product information and an anti-forgery information corresponding to the product information, wherein the anti-forgery information is generated using the method of claim 1; {The system receives an authenticity verification request and retrieves the corresponding product information and stored univocal sign information from the centralized database. [0070], [0086] – [0090] }
obtaining, from the anti-forgery information, the numeric field and an initial anti-forgery field according to the embedding position information of the numeric field; {The system extracts the digital part of the univocal sign, which includes a serial number and random security number, from the received authentication information. [0031], [0046], [0089] – [0090 ]}
decoding the encoded field to obtain a text field; and {The system automatically decodes the digital part of the univocal sign from a received image. [0089 ]}
obtaining a verification result of the product information by comparing the product information with the numeric field and the text field. {The system compares information derived from the received univocal sign against information stored in the database and generates an authenticity verification result. The positive response includes the stored product information for verification by the consumer. [0087], [0090] – [0093], [0100] }
Therefore, it would have been obvious to one of the ordinary skills in the art to modify the combination of Arya and von Mueller to include the product verification features of Dameri, to improve the security of the anti-forgery information and prevent unauthorized access, reproduction, or prediction of authentication data. (See [0067] of Dameri).
Claim 12
The combination of Arya, von Mueller, and Dameri teaches the limitations set forth above. Von Mueller further teaches:
obtaining, by querying the anti-forgery information database, the random number and a target key according to the product information; and {The system supports retrieving transaction values and decryption keys based on token information such as the BIN number, and using the retrieved keys to decrypt encrypted token data and recover the underlying data fields. [0116], [0316] – [0329]}
decrypting the initial anti-forgery field by using the target key, so as to obtain the random number, the numeric field and the encoded field. {The system supports employing a TDES counter mode decryption algorithm selected for use with the retrieved DMK and TMK keys and applying that algorithm to decrypt encrypted data and recover cleartext information. [0316] – [0329], [0330]}
The motivation and rationale to include the additional features of von Mueller is the same as set forth previously.
Claim 13
The combination of Arya, von Mueller, and Dameri teaches the limitations set forth above. Von Mueller further teaches:
determining a target encryption algorithm according to a type of the target key; and {The system supports generating a counter mode TDES stream cipher decryption block using the retrieved keys. [0316] – [0329]}
decrypting the initial anti-forgery field by using the target key based on the target encryption algorithm, so as to obtain the random number, the numeric field and the encoded field. {The system supports performing decryption operations using the retrieved DMK/TMK keys under the TDES counter mode algorithm to construct the original cleartext data. [0316] – [0330]}
The motivation and rationale to include the additional features of von Mueller is the same as set forth previously.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure (additional pertinent references can be found on attached form PTO-892):
US 20080307503 A1, which teaches: A system and method for law enforcement query entry that enables universal platform access without requiring specialized platform software by utilizing a keystroke efficient lexicon for data entry that is converted to standardized search commands by a back end server and by displaying search results in accordance with user, platform, network, and data security constraints.
US 20180330386 A1, which teaches: Methods and apparatuses are provided for a proof of ownership device and methods for using the same. In one embodiment, a proof of ownership device includes a transceiver configured to wirelessly communicate with an authentication server, a memory configured to store information about an authentic product made by a manufacturer, a battery configured to provide power to the proof of ownership device, and a controller configured to pair the proof of ownership device to the authentic product and control a status update of the authentic product.
US 20180349567 A1, which teaches: According to the present invention, a location of forged or falsified content can be indicated and identified with integrity verification of an electronic document file, whereby forgery or falsification can be effectively prevented.
“Efficient detection of counterfeit products in large-scale RFID systems using batch authentication protocols” (NPL attached), which teaches: RFID technology facilitates processing of product information, making it a promising technology for anti-counterfeiting. However, in large-scale RFID applications, such as supply chain, retail industry, pharmaceutical industry, total tag estimation and tag authentication are two major research issues. Though there are per-tag authentication protocols and probabilistic approaches for total tag estimation in RFID systems, the RFID authentication protocols are mainly per-tag-based where the reader authenticates one tag at each time. For a batch of tags, current RFID systems have to identify them and then authenticate each tag sequentially, one at a time. This increases the protocol execution time due to the large volume of authentication data. In this paper, we propose to detect counterfeit tags in large-scale system using efficient batch authentication protocol. We propose FSA-based protocol, FTest, to meet the requirements of prompt and reliable batch authentication in large-scale RFID applications. FTest can determine the validity of a batch of tags with minimal execution time which is a major goal of large-scale RFID systems. FTest can reduce protocol execution time by ensuring that the percentage of potential counterfeit products is under the user-defined threshold. The experimental result demonstrates that FTest performs significantly better than the existing counterfeit detection approaches, for example, existing authentication techniques.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CARLOS F MONTALVO whose telephone number is (703)756-5863. The examiner can normally be reached Monday - Friday 8:00AM - 5:30PM; First Fridays OOO.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sarah Monfeldt can be reached at 571-270-1833. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/C.F.M./Examiner, Art Unit 3629 /SARAH M MONFELDT/Supervisory Patent Examiner, Art Unit 3629
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