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 .
DETAILED ACTION
2. This action is in response to the application filed September 24, 2024.
3. Claims 1-20 have been examined and are pending with this action.
4. The Information Disclosure Statements filed September 24, 2024 and June 2, 2025 have been considered.
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.
5. Claims 1-6 and 11-20 are rejected under 35 U.S.C. 103 as being unpatentable over Dolev et al. (US 2019/0089717 A1) in view of Chrapko et al. (US 11,900,479 B2)
INDEPENDENT:
As per claim 1, Dolev teaches a computer-implemented method, comprising:
receiving, with at least one processor, a first unique identifier from at least one remote system (see Dolev, [0013]: “If an entity is identified by an identifying entity then an embodiment may include at least one of: registering, enlisting and enrolling the entity with at least one of: a network, a platform, a server, a service and an application.”; and [0124]: “A token as referred to herein may be any value, code, key or data object or digital information. For example, a token may be a unique value or number generated for a user or for a device. A token sent from computing device 210 to server 211 as shown by arrow 510 may be a token stored or included in a smart mobile device, e.g., a token obtained during a prior one-time enrollment process of the client to server 211, for example, a token, code, key or other data object received by device 210 in an SMS message, in an email, or obtained from a human agent.”);
capturing, with at least one processor, a first image of an enrolling user (see Dolev, [0168]: “Entity details in a record or ledger may include a photo of a person, a photo of (possibly approved) official documents, a business license, a driving license, a passport, a serial number, a purchase document, contact information, an address, any biometric data (e.g., fingerprints or retinal scan), a phone number, an email address, a messenger addresses, a social network identity (e.g., details in Facebook, LinkedIn, Skype etc.), a credit history certificate and the like.”; [0049]: “The development (or training) phase involves creating a background model for capturing speaker-related information.”; [0188]: “Updating a record, ledger or entity details of an entity may be based on any input or event, for example, a registration procedure that may include physical verification, biometric check and the like, or an update of entity details may be based on a communication via one or more of the contact addresses in the entity details, possibly using secured communication channels and/or secret shares as described herein.”; and [0218]: “For example, a record (or identity record) may include any identity details or attributes as described (e.g., photo, contact information, biometric information, passwords, public-keys, credit history, credit numbers and the like).”); and
communicating, with at least one processor, first image data associated with the first image of the enrolling user to the at least one remote system, the first image data comprising the first unique identifier (see Dolev, [0203]: “In some embodiments, an automatic and/or semi-automatic contact, authorization and behavioral profile contact and identity record builder and verifier (e.g., included in identifying entity 830) may be an unsupervised (e.g., using capabilities such as face recognition in images) process or supervised, possibly presenting found photos or other-identifications details and their sources interacting with the owner or user of a rich-contacts data-base letting the owner or user choose the most probable details to be fused into a ledger, record or entity details as described herein. Any source may be accessed, e.g., by units in identifying entity 830 or nodes 810 and 820, that may use results of search engines such as google (images), Facebook, Linkedin, Skype presenting all relevant photos or other details to be selectively chosen for gathering reliable contact information. For example, identifying entity 830 may present to a user data found for the user, receive from the user an indication that the information is correct and/or that the information should be included in entity details for the user. After receiving a confirmation from a user that information found for the user is correct or approved, identifying entity 830 may include the information in entity details for the user and may distribute the entity details, e.g., by sending entity details to nodes 810 and 820. Accordingly, a distributed record may be established by updating a plurality of nodes.”),
wherein, in response to receiving the first image data, the at least one remote system records the first image data and the first unique identifier in a ledger (see Dolev, [0168]: “Entity details in a record or ledger may include a photo of a person, a photo of (possibly approved) official documents, a business license, a driving license, a passport, a serial number, a purchase document, contact information, an address, any biometric data (e.g., fingerprints or retinal scan), a phone number, an email address, a messenger addresses, a social network identity (e.g., details in Facebook, LinkedIn, Skype etc.), a credit history certificate and the like.”; and [0188]: “Updating a record, ledger or entity details of an entity may be based on any input or event, for example, a registration procedure that may include physical verification, biometric check and the like, or an update of entity details may be based on a communication via one or more of the contact addresses in the entity details, possibly using secured communication channels and/or secret shares as described herein.”).
Dolev does not explicitly teach generating a first edge in a tree based on the first image data comprising the first unique identifier, the tree comprising a plurality of nodes and a plurality of edges, each node of the plurality of nodes connected to at least one other node of the plurality of nodes by a respective edge of the plurality of edges, the first edge connecting a first node of the plurality of nodes associated with a sponsoring user to a second node of the plurality of nodes associated with the enrolling user; and
determines a trust score for the second node based on a respective trust score of each of at least one node of the plurality of nodes connected to the second node by a respective edge of the plurality of edges, the at least one node of the plurality of nodes comprising the first node, the first node associated with a first trust score.
Chrapko teaches generating a first edge in a tree based on the first image data comprising the first unique identifier, the tree comprising a plurality of nodes and a plurality of edges, each node of the plurality of nodes connected to at least one other node of the plurality of nodes by a respective edge of the plurality of edges, the first edge connecting a first node of the plurality of nodes associated with a sponsoring user to a second node of the plurality of nodes associated with the enrolling user (see Chrapko, FIG. 10; col.19, lines 15-21: “In some embodiments, each of the nodes 1002, 1004, and 1006 may include images, text, or both, such as a profile picture associated with the entity depicted by the nodes. In some embodiments, the network graph 1000 may be generated for display in a scrollable display, wherein a user may scroll and zoom the network graph 1000 to see more and less nodes as desired.”; col.20, lines 44-47: “During this process, in some embodiments, a depth-first search may be performed of the node digraph or node tree. All affected ancestor nodes may then be identified and their paths recalculated.”; and col.23, lines 51-56: “As described above, in some embodiments, each network community is associated with its own connectivity graph, digraph, tree, or other suitable data structure. In other embodiments, a plurality of network communities may share one or more connectivity graphs (or other data structure).”); and
determines a trust score for the second node based on a respective trust score of each of at least one node of the plurality of nodes connected to the second node by a respective edge of the plurality of edges, the at least one node of the plurality of nodes comprising the first node, the first node associated with a first trust score (see Chrapko, Abstract: “A peer trust score targeted from a first entity to a second entity may also be calculated based on the above factors. In some embodiments, the peer trust score may be derived from the system trust score for the target entity and may take into account additional factors, including social network connections, group/demographic info, and location data. Finally, a contextual trust score may be calculated between the first and second entities based on a type of transaction or activity to be performed between the two entities.”; and col.2, lines 14-21: “As used herein, a “peer trust score” refers to a trust score calculated for a first entity in relation to a second entity. The peer trust score may take into account certain information that is specific to the first and second entity, such as specific transaction history between the first and second entity, number of common contacts/friends, etc. In some embodiments, the peer trust score may be derived from the system trust score and represent an update of the system trust score.”).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the system of Dolev in view of Chrapko by implementing generating a first edge in a tree based on the first image data comprising the first unique identifier, the tree comprising a plurality of nodes and a plurality of edges, each node of the plurality of nodes connected to at least one other node of the plurality of nodes by a respective edge of the plurality of edges, the first edge connecting a first node of the plurality of nodes associated with a sponsoring user to a second node of the plurality of nodes associated with the enrolling user; and determines a trust score for the second node based on a respective trust score of each of at least one node of the plurality of nodes connected to the second node by a respective edge of the plurality of edges, the at least one node of the plurality of nodes comprising the first node, the first node associated with a first trust score.
One would be motivated to do so because Chrapko teaches in the Abstract, “A system trust score may be calculated for an entity by combining a variety of factors, including verification data, a network connectivity score, publicly available information, and/or ratings data”, and Dolev further teaches in paragraphs [0161], “Accordingly, some embodiments of the invention may provide or enable security of a system… e.g., based on a security, trust or verification between entities 720 and/or 730 and entity 740, a security, identification or trust between identifying entity 710 and entity 740 may be achieved. For example, entities 720 and 730 may be known, trusted and/or identified employees in an organization, and the trust in these employees may be used to identify, and/or establish a trust of a new employee (or employee's device) 740.” & [0170]: “As shown, system 800 may include any (possibly large) number of entities (also referred to herein as nodes) that may each store, keep or otherwise include entity details of an entity and a trust level for each detail of the contact record for the entity. A trust level as referred to herein may be any value, score, or confidence level that reflects or indicates a level of trust in an identity of an entity.”.
As per claim 19, Dolev and Chrapko teach a system, comprising: at least one processor configured to:
receive a first unique identifier from at least one remote system;
capture a first image of an enrolling user; and
communicate first image data associated with the first image of the enrolling user to the at least one remote system, the first image data comprising the first unique identifier,
wherein, in response to receiving the first image data, the at least one remote system is configured to record the first image data and the first unique identifier in a ledger;
generate a first edge in a tree based on the first image data comprising the first unique identifier, the tree comprising a plurality of nodes and a plurality of edges, each node of the plurality of nodes connected to at least one other node of the plurality of nodes by a respective edge of the plurality of edges, the first edge connecting a first node of the plurality of nodes associated with a sponsoring user to a second node of the plurality of nodes associated with the enrolling user; and
determine a trust score for the second node based on a respective trust score of each of at least one node of the plurality of nodes connected to the second node by a respective edge of the plurality of edges, the at least one node of the plurality of nodes comprising the first node, the first node associated with a first trust score.
As per claim 20, Dolev and Chrapko teach a computer program product, the computer program product comprising at least one non-transitory computer-readable medium including one or more instructions that, when executed by at least one processor, cause the at least one processor to:
receive a first unique identifier from at least one remote system;
capture a first image of an enrolling user; and
communicate first image data associated with the first image of the enrolling user to the at least one remote system, the first image data comprising the first unique identifier,
wherein, in response to receiving the first image data, the at least one remote system records the first image data and the first unique identifier in a ledger;
generates a first edge in a tree based on the first image data comprising the first unique identifier, the tree comprising a plurality of nodes and a plurality of edges, each node of the plurality of nodes connected to at least one other node of the plurality of nodes by a respective edge of the plurality of edges, the first edge connecting a first node of the plurality of nodes associated with a sponsoring user to a second node of the plurality of nodes associated with the enrolling user; and
determines a trust score for the second node based on a respective trust score of each of at least one node of the plurality of nodes connected to the second node by a respective edge of the plurality of edges, the at least one node of the plurality of nodes comprising the first node, the first node associated with a first trust score.
DEPENDENT:
As per claim 2, which depend on claim 1, Dolev further teaches wherein receiving the first unique identifier comprises receiving the first unique identifier via a secure mobile application of a sponsor device, and wherein communicating the first image data comprises communicating the first image data from the secure mobile application of the sponsor device (see Dolev, [0038]: “Executable code 125 may be any executable code, e.g., an application, a program, a process, task or script. Executable code 125 may be executed by controller 105 possibly under control of operating system 115. For example, executable code 125 may be an application that secures a communication channel and/or authenticates a remote device as further described herein. Embedded in memory 120, executable code 125 may be firmware as known in the art.”; and [0083]: “channels that may be secured are between hub 323 and device (or application) 310, between, or connecting, hub 323 and one or more of edge devices 324, between one or more of servers 330 and device (or application) 310, and between servers 330 and hub 323.”; and [0087]: “Each of the channels may be secured by the application that is used to send data over it, for example, only the owner of device 310 can send push notification to SEU 211 or channels may be secured by a cloud service (e.g. as provided by Apple or Google).”).
As per claim 3, which depend on claim 2, Dolev further teaches wherein the sponsor device logs into the secure mobile application via a strong authentication technique (see Dolev, [0061]: “An authentication may be based on one or more secret values 128. For example, to authenticate the washing machine in the above example, an SEU in device 310 may, using one or more secret values 128 as an encryption key, encrypt a message (for which a respective specific response is expected) and send the encrypted message to the washing machine (e.g., to an SEU in the washing machine), if a response from the washing machine is as expected, then the SEU in device 310 may determine or conclude that the SEU in the washing machine knows, includes or has the secret and is therefore authenticated, e.g., since the SEU in the washing machine successfully decrypted the message, generated an expected response, and encrypted the response. An authentication of a device may be explicit, e.g., as described herein or it may be implicit, e.g., successful exchange of data that is encrypted using a secret value 128 may authenticate a device, e.g., the washing machine may be authenticated by a smartphone if it sends expected data or messages or correctly responds to messages.”; and [0114]: “Accordingly, using an overlay technique or security as described herein, some embodiments of the invention may provide security that is stronger than the (currently) strongest authentication and security among the physical and logical channels used for sending the secret shares, as information on all channels should be revealed to expose a (possibly encrypted) secret shared or other information.”).
As per claim 4, which depend on claim 3, Dolev further teaches wherein the strong authentication technique comprises at least one of two-factor authentication (2FA), Fast IDentity Online (FIDO), or any combination thereof (see Dolev, [0120]: “the O(n) secured links may be secured by user passwords, data encryption, two-step-verification and/or various other techniques supported by servers and/or applications. By overlaying a set of secured layers as described, some embodiments of the invention may achieve a security between any two devices, namely, O(n̂2) secure overlay channels.”; and [0201]: “For example, automatic, multi-factor identification and rich-contact details construction may be achieved by search engine fusion results (including indications concerning access patterns that can be extracted from public data and/or the personal behavioral patterns and preferences that servers store) in public and private directories, social networks, government, and commercial entities is a proposed software application. A contact list or rich-contact details as described herein may facilitate the use of secret sharing and overlay security to establish multi-channel, multi-factor, identification, authentication, and secrecy as described herein.”).
As per claim 5, which depend on claim 1, Dolev teaches further comprising: communicating, with at least one processor, a request for the first unique identifier to the at least one remote system before receiving the first unique identifier (see Dolev, [0004]: “Specifically, a registration authority (RA) accepts requests for digital certificates and authenticates entities.”; and [0172]: “identifying entity 830 may be a bank that wants to validate or verify the identity of target entity that may be a user, e.g., prior to completing a transaction of money to a bank account of a user based on data in a transaction request, the bank (the identifying entity) may want to verify or ascertain that the user indicated in the transaction data (the target entity) is indeed the user who owns the indicated account.”).
As per claim 6, which depend on claim 1, Dolev further teaches wherein the first image data comprises a checksum value associated with the first image (see Dolev, [0209]: “Privacy protection may be achieved by some embodiments by sending secret shared data with integrity checksum to a user. For example, a user or client that would like to identify herself/himself may present a random string (for certain fields that should be revealed) that when used in a particular fashion, say twice (e.g. concatenated) reveals the needed information and the fitting signature.”).
As per claim 11, which depend on claim 1, Dolev further teaches further comprising: communicating, with at least one processor, second image data associated with a second image of a government identification document of the enrolling user (see Dolev, [0203]: “In some embodiments, an automatic and/or semi-automatic contact, authorization and behavioral profile contact and identity record builder and verifier (e.g., included in identifying entity 830) may be an unsupervised (e.g., using capabilities such as face recognition in images) process or supervised, possibly presenting found photos or other-identifications details and their sources interacting with the owner or user of a rich-contacts data-base letting the owner or user choose the most probable details to be fused into a ledger, record or entity details as described herein. Any source may be accessed, e.g., by units in identifying entity 830 or nodes 810 and 820, that may use results of search engines such as google (images), Facebook, Linkedin, Skype presenting all relevant photos or other details to be selectively chosen for gathering reliable contact information.”).
As per claim 12, which depend on claim 11, Dolev further teaches wherein the first image comprises a first representation of a face of the enrolling user and the second image comprises a second representation of the face of the enrolling user, wherein the at least one remote system compares the first image to the second image to determine the first representation matches the second representation (see Dolev, [0198]: “For example, if the person is found by one of nodes 810 or 820 (entity details that match those received from identifying entity 830 were found in a database of identity details in node 810), then that node may inform identifying entity 830 that the person was found and may send additional details for the person it found in its storage or additional details the node obtained using the details it received from identifying entity 830.”; and Claim 11 rejection above).
As per claim 13, which depend on claim 1, Dolev teaches further comprising: communicating, from a relying party system, a request for the trust score associated with the enrolling user to the at least one remote system (see Dolev, [0170]: “A trust level as referred to herein may be any value, score, or confidence level that reflects or indicates a level of trust in an identity of an entity. For example, a scale of one to ten (1-10) may be used where a trust level of one (1) may indicate lack of trust while a trust level of ten (10) may indicate, represent or reflect that an identity of an entity is verified, authenticated or determined with a high level of confidence or trust.”; [0172]: “identifying entity 830 may be a bank that wants to validate or verify the identity of target entity that may be a user, e.g., prior to completing a transaction of money to a bank account of a user based on data in a transaction request, the bank (the identifying entity) may want to verify or ascertain that the user indicated in the transaction data (the target entity) is indeed the user who owns the indicated account.”; and [0174]: “For the sake of clarity, only a single trust level per node is shown; however, any number of trust levels, scores or values may be associated, by each node, with an entity. For example, each element or entry in entity details 811 may be associated or assigned with a trust level, and trust level 812 may be calculated based on a set of trust levels.”).
As per claim 14, which depend on claim 13, further teaches wherein the request comprises the first unique identifier see Dolev, ([0004]: “Specifically, a registration authority (RA) accepts requests for digital certificates and authenticates entities.”; and [0172]: “identifying entity 830 may be a bank that wants to validate or verify the identity of target entity that may be a user, e.g., prior to completing a transaction of money to a bank account of a user based on data in a transaction request, the bank (the identifying entity) may want to verify or ascertain that the user indicated in the transaction data (the target entity) is indeed the user who owns the indicated account.”).
As per claim 15, which depend on claim 13, Dolev further teaches wherein the relying party system creates an account for the enrolling user with the relying party system based on the trust score (see Dolev, [0010]: “An embodiment may receive from a registering entity, entity details related to the registering entity; may provide the entity details to at least one of first system and second systems; and may associate the registering entity with a trust level based on at least one trust level received from at least one of the first and second systems”; and [0013]: “f an entity is identified by an identifying entity then an embodiment may include at least one of: registering, enlisting and enrolling the entity with at least one of: a network, a platform, a server, a service and an application.”; and [0146]: “Identifying an entity (e.g., a person or device) may be performed as part of an enrollment or registration procedure, e.g., as part of an enrollment to a service, organization or platform. For example, an identifying entity may be a server, platform, service and/or application of an organization and the identifying entity may identify, authenticate or verify a new employee, device or any entity that needs to be identified, e.g., prior to being granted access to resources of the organization.”).
As per claim 16, which depend on claim 1, Dolev further teaches wherein the ledger comprises an encrypted distributed ledger (see Dolev, [0166]: “an embodiment may include or enable establishing trust concerning an identity of an entity by the implementation of a distributed ledger or record of entity details, possibly based on block-chain and/or distributed-ledger technology, either with or without using consensus. In some embodiments, a trust in an identity of an entity may be based on an accumulation of trust in one or more nodes (or entities) that may collaborate to create a distributed ledger.”).
As per claim 17, which depend on claim 1, Dolev does not explicitly teach wherein the at least one remote system identifies at least one subset of the plurality of nodes of the tree based on network analysis.
Chrapko teach wherein the at least one remote system identifies at least one subset of the plurality of nodes of the tree based on network analysis (see Chrapko, FIG. 10; col.11, lines 26-30: “For a peer trust score, such as peer trust score 304, the network connectivity component may take into account number of mutual friends, degree of separation, and number of paths from a first entity to the target entity.”; and col.20, lines 44-47: “in some embodiments, a depth-first search may be performed of the node digraph or node tree. All affected ancestor nodes may then be identified and their paths recalculated.”).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the system of Dolev in view of Chrapko so that at least one remote system identifies at least one subset of the plurality of nodes of the tree based on network analysis. One would be motivated to do so because Dolev teaches in paragraph [0090], “Accordingly, authenticity or trust level of the new device N may be yielded from, based on, or a function of, the authenticity of each of the already trusted or authenticated devices that directly communicate with the new device and the corresponding authenticity or trust level of the direct channel used by device A when directly communicating with device N.”.
As per claim 18, which depend on claim 1, Dolev further teaches wherein, in response to receiving negative event data associated with at least one negative event associated with a third node of the tree, the at least one remote adjusts a third trust score associated with the third node based on the negative event data and adjusts the trust score for each node of the plurality of nodes connected to the third node by one of the plurality of edges, wherein the negative event data comprises at least one of complaint data associated with a complaint, an indication associated with a fraudulent transaction, or any combination thereof (see Dolev, [0160]: “It is possible that a network of trust will be constructed and updated with every new identification, possibly with feedbacks concerning false identifications. Such a network of trust can have independent applications, such as credit ranking.”; [0179]: “Accordingly, a record or ledger for an entity may be created or updated by any number of nodes.”; and [0213]: “In some embodiments, nodes in a system (e.g., nodes 810 and 820) may use consensus to establish common identity storage (e.g., removing obsolete information) and combined trust, upon a read/search/write event and/or periodically. In some embodiments, nodes (e.g., nodes 810 and 820) may periodically perform search for their identity to avoid identity theft, and may have (periodically, e.g., daily, monthly) search, read, write or update identity details or records.”).
6. Claim 7-9 are rejected under 35 U.S.C. 103 as being unpatentable over Dolev et al. (US 2019/0089717 A1) and Chrapko et al. (US 11,900,479 B2), and still further in view of Rhoads US 2004/0022444 A1)
As per claim 7, which depend on claim 1, Dolev and Chrapko do not explicitly teach wherein the first image data comprises the first unique identifier embedded in the first image.
Rhoads teaches the first image data comprises the first unique identifier embedded in the first image (see Rhoads, [0818]: “A session may be tracked and associated with session related metadata by a session identifier encoded in the image, the image file, or its metadata. For example, the session identifier may be a number or message embedded steganographically in the image or metadata associated with the image.”).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the system of Dolev and Chrapko in view of Rhoads so that the first image data comprises the first unique identifier embedded in the first image.
One would be motivated to do so because Rhoads teaches in the Abstract, “physical attributes of the object are utilized as a key for accessing information included in a digital watermark for the object.”.
As per claim 8, which depend on claim 7, Dolev and Chrapko do not explicitly teach further comprising: embedding, by at least one processor, the first unique identifier in the first image by inserting the first unique identifier in metadata of the first image.
Rhoads teaches embedding, by at least one processor, the first unique identifier in the first image by inserting the first unique identifier in metadata of the first image (see Rhoads, [0818]: “A session may be tracked and associated with session related metadata by a session identifier encoded in the image, the image file, or its metadata. For example, the session identifier may be a number or message embedded steganographically in the image or metadata associated with the image.”).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the system of Dolev and Chrapko in view of Rhoads by implementing embedding, by at least one processor, the first unique identifier in the first image by inserting the first unique identifier in metadata of the first image.
One would be motivated to do so because Rhoads teaches in the Abstract, “physical attributes of the object are utilized as a key for accessing information included in a digital watermark for the object.”.
As per claim 9, which depend on claim 7, Dolev and Chrapko do not explicitly teach further comprising: embedding, with at least one processor, the first unique identifier in the first image by steganography.
Rhoads teaches embedding, with at least one processor, the first unique identifier in the first image by steganography (see Rhoads, [0818]: “A session may be tracked and associated with session related metadata by a session identifier encoded in the image, the image file, or its metadata. For example, the session identifier may be a number or message embedded steganographically in the image or metadata associated with the image.”).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the system of Dolev and Chrapko in view of Rhoads by implementing embedding, with at least one processor, the first unique identifier in the first image by steganography.
One would be motivated to do so because Rhoads teaches in the Abstract, “physical attributes of the object are utilized as a key for accessing information included in a digital watermark for the object.”.
Claim Objections
7. Claim 10 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is an examiner' s statement of reasons for allowance:
The prior art of record does not disclose, teach, or suggest neither singly nor in combination the claimed limitation of “wherein embedding the first unique identifier in the first image by steganography comprises adjusting at least one bit of a plurality of pixel values of the first image based on the first unique identifier” as recited in dependent claim 10.
Conclusion
8. For the reasons above, claims 1-9 and 11-20 have been rejected, claim 10 has been objected to, and claims 1-20 remain pending.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL Y WON whose telephone number is (571)272-3993. The examiner can normally be reached on Wk.1: M-F: 8-5 PST & Wk.2: M-Th: 8-7 PST.
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/Michael Won/Primary Examiner, Art Unit 2443