Patent 11387982

Prior art

Earlier patents, publications, and products that may anticipate or render the claims unpatentable.

Active provider: Google · gemini-2.5-flash

Prior art

Earlier patents, publications, and products that may anticipate or render the claims unpatentable.

✓ Generated

The initial search for "US patent 11387982 USPTO" confirms that the patent exists and provides links to the USPTO search tools. The provided patent text is authoritative, so I will proceed using the citation information directly from it, and supplement with searches for specific descriptions if needed.

Here's an analysis of the most relevant prior art for US11387982, based on the citations provided within the patent text and considering potential anticipation under 35 U.S.C. § 102.

US11387982: Method for authenticating a hash of a data packet from collected context data based on a hash distance generation step, first authentication device, second authentication device, and authentication system

The independent claims of US11387982 are:

  • Claim 1 (Method): Requires collecting context data (specifically a captured image as a fixed-length string of bits), constituting a data packet, generating a hash using a predetermined hash type algorithm, sending the hash, generating a hash distance between the generated hash and a reference hash, and authenticating based on this distance. The hash is a byte stream generated from the fixed-length string of bits.
  • Claim 8 (First Authentication Device): Configured to perform the collection, data packet constitution, hash generation, and sending steps of Claim 1.
  • Claim 9 (Second Authentication Device): Configured to receive the hash, generate the hash distance, and authenticate based on the hash distance.
  • Claim 10 (Authentication System): Combines the first and second authentication devices and their respective functionalities as described above.

The distinguishing features of US11387982, particularly as articulated in its summary and problem statement, include:

  • Reduced bandwidth: Transmitting a hash (few kbytes) instead of raw video/image data (several Mb).
  • Data privacy: The hash obfuscates original context data, unlike plain text transmission.
  • Resilience to small changes: Using hash distance (e.g., LSH) allows authentication even with slight variations in collected context data.

The patent specifically criticizes EP 2 924 603 A2 in its "State of the Art" section, making it a highly relevant piece of prior art.

Most Relevant Prior Art for US11387982

  1. EP2924603A2
    • Full Citation: EP2924603A2 - Fmr Llc, "Method and system for user authentication based on biometrics, clothes wearing and surrounding scene"
    • Publication/Filing Date: Publication date: 2015-09-30; Priority date: 2014-03-25.
    • Brief Description: This patent describes a user authentication technique where a client sends a captured video signal (including physical user characteristics and environmental objects) to a server. The server analyzes the video signal to determine values associated with visual and audio elements, calculates a total score, and compares it to a predetermined reference score for authorization. The present patent US11387982 explicitly identifies this prior art and highlights its drawbacks: requiring significant bandwidth due to transmitting the full video signal (several Mb) and disclosing private user environment data in plain text.
    • Potential Anticipation (35 U.S.C. § 102): EP2924603A2 anticipates the general concept of collecting context data (video signal including user characteristics and environment), sending it to a server, and authenticating based on a comparison to a reference. However, it does not anticipate the specific claimed features of US11387982, particularly:
      • Generating a hash from the collected context data. EP2924603A2 transmits the raw video signal.
      • Generating a hash distance between the generated hash and a predetermined reference hash. EP2924603A2 calculates a "total score" from direct analysis of the video signal, not a hash distance.
      • The "wherein" clauses of Claim 1 (context data as captured image represented as fixed-length string of bits for constituting a data packet, and hash as a byte stream generated from said string of bits).
        Therefore, it does not anticipate Claim 1, 8, or 10, as it lacks the core hashing and hash distance comparison steps.
  1. US20150096023A1
    • Full Citation: US20150096023A1 - Fireeye, Inc., "Fuzzy hash of behavioral results"
    • Publication/Filing Date: Publication date: 2015-04-02; Priority date: 2013-09-30.
    • Brief Description: This application describes systems and methods for determining the similarity between behavioral results (e.g., from malware analysis) using fuzzy hashing. Fuzzy hashes allow for similarity detection even if the underlying data has slight variations, which is a core concept for the hash distance in US11387982. The application relates to generating a fuzzy hash and comparing it to a reference fuzzy hash.
    • Potential Anticipation (35 U.S.C. § 102): This patent application is highly relevant because it describes the use of "fuzzy hashing" for similarity detection, which is directly analogous to the "hash distance generation step" and the use of algorithms like LSH (Locality Sensitive Hash) mentioned in US11387982. It covers:
      • Generating a hash (fuzzy hash).
      • Comparing hashes to determine similarity (hash distance).
        However, its context is "behavioral results" (e.g., malware), not general "context data elements" like images of a user or a TV set. It also does not explicitly describe the "collecting... at least one context data element" and "constituting a data packet" in the manner of US11387982, nor the specific "wherein" clauses of Claim 1 (captured image as fixed-length string of bits, hash as byte stream from said string of bits). While it anticipates the technique of fuzzy hashing and similarity comparison for authentication, it does not fully disclose the application to diverse context data elements as defined in US11387982's Claim 1.
        Therefore, it does not anticipate Claim 1, 8, or 10 as it lacks the specific context data collection and packet constitution. However, it directly anticipates the technical principle of "generating a hash distance" and using fuzzy/LSH type algorithms (as detailed in dependent Claim 2).
  1. US9594906B1
    • Full Citation: US9594906B1 - Juniper Networks, Inc., "Confirming a malware infection on a client device using a remote access connection tool to identify a malicious file based on fuzzy hashes"
    • Publication/Filing Date: Publication date: 2017-03-14; Priority date: 2015-03-31.
    • Brief Description: This patent describes confirming malware infections by calculating fuzzy hashes of files on a client device and comparing them to fuzzy hashes of known malicious files. This is another example of applying fuzzy hashing for similarity detection in a security context.
    • Potential Anticipation (35 U.S.C. § 102): Similar to US20150096023A1, this patent utilizes fuzzy hashes for comparison and detection of similar (malicious) files. It reinforces the concept of generating hashes that are resilient to small changes and comparing them. However, its specific application is malware detection from files, not context data elements like images or environmental data for general authentication. It lacks the steps of collecting context data from the environment, constituting a data packet from it, and specifically using captured images as fixed-length strings of bits.
      Thus, it does not anticipate Claim 1, 8, or 10 for similar reasons as US20150096023A1, but it is highly relevant to the "hash distance generation step" and the underlying technology described in dependent Claim 2.
  1. US20140108800A1
    • Full Citation: US20140108800A1 - David Lawrence, "System and method for improved geothentication based on a hash function"
    • Publication/Filing Date: Publication date: 2014-04-17; Priority date: 2012-10-16.
    • Brief Description: This application describes a "geothentication" method where a hash function is applied to geolocation data to improve security and privacy for location-based authentication.
    • Potential Anticipation (35 U.S.C. § 102): This prior art describes collecting "context data" (geolocation data), applying a hash function, and using the hash for authentication. This broadly covers some elements of Claim 1, namely "collecting... at least one context data element," "generating a hash... and the data packet, as input," and "sending the generated hash." However, it does not disclose:
      • Generating a hash distance between the generated hash and a predetermined reference hash. Instead, it uses a hash for direct authentication.
      • Authenticating based on the hash distance.
      • The specific "wherein" clauses of Claim 1 (captured image as fixed-length string of bits, hash as byte stream from said string of bits). While geolocation data is a "context data element", it's not a "captured image represented as a string of bits with a fixed length".
        Therefore, it does not anticipate Claim 1, 8, or 10 because it lacks the crucial "hash distance" generation and authentication step, and the specific nature of the context data element.
  1. US9514753B2
    • Full Citation: US9514753B2 - Google Inc., "Speaker identification using hash-based indexing"
    • Publication/Filing Date: Publication date: 2016-12-06; Priority date: 2013-11-04.
    • Brief Description: This patent describes methods for identifying speakers using hash-based indexing. Audio data is converted into features, hashed, and then compared to indexed hashes for identification. This involves generating hashes from biometric (voice) data and comparing them.
    • Potential Anticipation (35 U.S.C. § 102): This patent involves collecting biometric "context data" (speaker's voice), processing it (feature extraction), hashing it, and comparing the hash for identification. This is broadly similar to elements of Claim 1. However, it focuses on "speaker identification" using "hash-based indexing" which implies direct matching rather than a flexible "hash distance" for authentication that allows for slight changes in the environment, as emphasized in US11387982. Also, the context data is audio, not specifically a "captured image represented as a string of bits with a fixed length," and it doesn't explicitly describe constituting a "data packet" in the same way. The comparison for identification might be a form of "hash distance" but it's not explicitly framed as "authenticating based on the generated hash distance" allowing for "more or less small changes" as described in US11387982.
      Therefore, it does not anticipate Claim 1, 8, or 10 due to the lack of explicit hash distance for flexible authentication and the specific nature of the "captured image" context data.
  1. US20170109514A1
    • Full Citation: US20170109514A1 - Sri International, "Continuous authentication of mobile device users"
    • Publication/Filing Date: Publication date: 2017-04-20; Priority date: 2014-12-18.
    • Brief Description: This application details systems and methods for continuous authentication of mobile device users based on various user and device characteristics (context data) collected over time.
    • Potential Anticipation (35 U.S.C. § 102): This patent involves collecting "context data" (user and device characteristics) for authentication. While it broadly falls under the umbrella of context-based authentication, it does not explicitly describe the crucial steps of:
      • Generating a hash from the collected context data.
      • Generating a hash distance between the generated hash and a reference hash.
      • Authenticating based on the hash distance.
      • The specific "wherein" clauses of Claim 1 concerning a captured image and its representation.
        Thus, it does not anticipate Claim 1, 8, or 10 as it lacks the core hashing and hash distance comparison elements.
  1. US20080181403A1
    • Full Citation: US20080181403A1 - Yu Sakamoto, "Authenticating system, authenticating method, and authenticating program"
    • Publication/Filing Date: Publication date: 2008-07-31; Priority date: 2007-01-25.
    • Brief Description: This patent describes an authentication system that includes receiving authentication information, generating authentication data, comparing it with registered authentication data, and authenticating. The authentication information could be user inputs or environmental data.
    • Potential Anticipation (35 U.S.C. § 102): This patent broadly covers authentication using various types of data and comparison. However, it does not specify the use of hashing the collected context data to form a data packet, generating a hash distance for authentication, nor the specific "wherein" clauses of Claim 1. The comparison is generally between "authentication data" and "registered authentication data," which is less specific than the "hash distance" concept of US11387982.
      Therefore, it does not anticipate Claim 1, 8, or 10.
  1. US20040221153A1
    • Full Citation: US20040221153A1 - [[Samsung Electronics Co.](/litigations/by-defendant/Samsung%20Electronics%20Co.), Ltd.](/litigations/by-plaintiff/Samsung%20Electronics%20Co.%2C%20Ltd.), "Apparatus and method of enciphering data packet of variable width"
    • Publication/Filing Date: Publication date: 2004-11-04; Priority date: 2003-02-06.
    • Brief Description: This application focuses on methods and apparatus for enciphering data packets, particularly those with variable widths. While it deals with data packets and security, it is primarily concerned with encryption techniques for data transmission.
    • Potential Anticipation (35 U.S.C. § 102): This patent is concerned with ciphering data packets, which is an optional step mentioned in US11387982 (e.g., Claim 6 and its description). It does not, however, disclose the core elements of US11387982's independent claims, such as collecting context data, generating a hash from it, creating a hash distance, and authenticating based on that distance. It would not anticipate the independent claims (1, 8, 9, 10), but could be considered relevant to the dependent claim involving ciphering (Claim 6).
  1. US20060020796A1
    • Full Citation: US20060020796A1 - Microsoft Corporation, "Human input security codes"
    • Publication/Filing Date: Publication date: 2006-01-26; Priority date: 2003-03-27.
    • Brief Description: This application describes generating human input security codes (e.g., CAPTCHAs) to distinguish humans from automated processes. It involves presenting challenges and verifying human responses.
    • Potential Anticipation (35 U.S.C. § 102): This patent focuses on human interaction and CAPTCHA-like mechanisms for security. It is not related to collecting environmental or contextual data for authentication using hash distances. It does not anticipate any claims of US11387982.
  1. WO2016083216A1
    • Full Citation: WO2016083216A1 - Gemalto Sa, "Method for accessing media data and corresponding device and system"
    • Publication/Filing Date: Publication date: 2016-06-02; Priority date: 2014-11-28.
    • Brief Description: This application describes methods for accessing media data, possibly with authentication mechanisms. The title is quite broad, and without further details, its direct relevance to hash distance authentication from context data is not immediately clear.
    • Potential Anticipation (35 U.S.C. § 102): Without more specific details about the authentication method in WO2016083216A1, it's difficult to assess precise anticipation. However, based on the title, it likely covers general access control for media, rather than the specific hash distance authentication mechanism for context data as claimed in US11387982. It is unlikely to anticipate Claim 1, 8, 9, or 10.
  1. US20160323243A1
    • Full Citation: US20160323243A1 - Cirius Messaging Inc., "Data leak protection system and processing methods thereof"
    • Publication/Filing Date: Publication date: 2016-11-03; Priority date: 2015-05-01.
    • Brief Description: This application describes systems and methods for data leak protection, often involving scanning and identifying sensitive information within data streams or files.
    • Potential Anticipation (35 U.S.C. § 102): This patent is focused on data leak protection, which might involve hashing for content identification or integrity, but it does not describe an authentication method based on collecting environmental context data, generating a hash distance from it, and using that distance for authentication. It does not anticipate any claims of US11387982.

Summary of Most Relevant Prior Art and Anticipation:

The most relevant prior art appears to be EP2924603A2, US20150096023A1, and US9594906B1.

  • EP2924603A2 is the closest in problem domain (context/environment authentication) and explicitly discussed as prior art in US11387982. It teaches collecting context data (video) and authenticating based on a score derived from it. However, it specifically lacks the crucial hashing and hash-distance comparison steps, which are the inventive core of US11387982. Therefore, it does not anticipate Claim 1, 8, or 10.
  • US20150096023A1 and US9594906B1 are highly relevant to the technical mechanism of fuzzy hashing/LSH and similarity comparison (hash distance). They clearly demonstrate the generation of hashes and their comparison for similarity detection. While they describe the technique underlying the "hash distance generation step" (Claim 1 and 9, and thus 10), and especially the LSH type algorithm of Claim 2, they apply this technique in different contexts (malware analysis) and do not disclose the specific collection of diverse context data elements, constituting a data packet from them (especially images as fixed-length strings of bits), and then applying the hash distance to authenticate the context as defined in US11387982. Thus, they do not anticipate the full scope of Claim 1, 8, or 10, but they demonstrate that the "generating a hash distance" and comparing it to a threshold (which is key to Claim 2) was known in the art for various forms of similarity detection.

Therefore, while these references teach individual components or similar concepts, none of them fully disclose every element of independent claims 1, 8, or 10 of US11387982 in a single piece of prior art, specifically the combination of (1) collecting diverse context data elements (including images as fixed-length strings of bits), (2) forming a data packet from them, (3) generating a hash from that packet, and (4) performing authentication based on a hash distance between the generated hash and a reference hash to allow for small changes. The specific "wherein" clauses of Claim 1 are particularly important in distinguishing US11387982 from prior art that uses hashing for different data types or purposes.

Full list of relevant prior art for US11387982:

  1. US20040221153A1

    • Full Citation: US20040221153A1 - Samsung Electronics Co., Ltd., "Apparatus and method of enciphering data packet of variable width"
    • Publication/Filing Date: Publication: 2004-11-04; Priority: 2003-02-06
    • Brief Description: Describes methods and apparatus for enciphering data packets, including those with variable widths, primarily focusing on encryption techniques for data transmission.
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate independent claims 1, 8, 9, or 10 due to lacking the core hash generation, hash distance comparison, and context-based authentication steps. It is relevant to the optional step of ciphering data packets, as described in dependent Claim 6 of US11387982.

  2. US20060020796A1

    • Full Citation: US20060020796A1 - Microsoft Corporation, "Human input security codes"
    • Publication/Filing Date: Publication: 2006-01-26; Priority: 2003-03-27
    • Brief Description: Describes generating human input security codes (e.g., CAPTCHAs) for distinguishing humans from automated processes, involving challenges and verification of human responses.
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate any claims of US11387982 as it focuses on human interaction/CAPTCHA, not hash distance authentication from collected context data.

  3. US20080181403A1

    • Full Citation: US20080181403A1 - Yu Sakamoto, "Authenticating system, authenticating method, and authenticating program"
    • Publication/Filing Date: Publication: 2008-07-31; Priority: 2007-01-25
    • Brief Description: Describes an authentication system that receives authentication information, generates authentication data, compares it with registered authentication data, and authenticates. Authentication information can include user inputs or environmental data.
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate independent claims 1, 8, 9, or 10. While it broadly discusses authentication and comparison, it lacks the specificity of generating a hash from a data packet of collected context data, using a hash distance (as opposed to a general comparison) for authentication, and the specific "wherein" clauses of Claim 1.

  4. US20140108800A1

    • Full Citation: US20140108800A1 - David Lawrence, "System and method for improved geothentication based on a hash function"
    • Publication/Filing Date: Publication: 2014-04-17; Priority: 2012-10-16
    • Brief Description: Describes a "geothentication" method where a hash function is applied to geolocation data to enhance security and privacy for location-based authentication.
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate independent claims 1, 8, 9, or 10. While it involves hashing context data (geolocation), it does not disclose the generation of a hash distance between a generated hash and a reference hash for authentication, nor the specific "wherein" clauses of Claim 1 regarding a captured image as context data.

  5. US20150096023A1

    • Full Citation: US20150096023A1 - Fireeye, Inc., "Fuzzy hash of behavioral results"
    • Publication/Filing Date: Publication: 2015-04-02; Priority: 2013-09-30
    • Brief Description: Describes systems and methods for determining similarity between behavioral results (e.g., from malware analysis) using fuzzy hashing. This allows for similarity detection even with slight data variations.
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate independent claims 1, 8, or 10, as it applies fuzzy hashing to "behavioral results" (e.g., malware) and lacks the specific context data collection (e.g., captured image as fixed-length string of bits) and explicit authentication of a context based on the hash distance. However, it is highly relevant to the "generating a hash distance" step and the use of fuzzy hash type algorithms, directly anticipating the technical principle of dependent Claim 2.

  6. US9514753B2

    • Full Citation: US9514753B2 - Google Inc., "Speaker identification using hash-based indexing"
    • Publication/Filing Date: Publication: 2016-12-06; Priority: 2013-11-04
    • Brief Description: Describes methods for identifying speakers using hash-based indexing, where audio data is processed, hashed, and compared to indexed hashes for identification.
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate independent claims 1, 8, or 10. While it involves hashing biometric (audio) context data, it focuses on "speaker identification" using "hash-based indexing" which implies direct matching rather than a flexible "hash distance" for authentication that accounts for slight environmental changes, and it does not use a "captured image represented as a fixed-length string of bits" as the context data.

  7. EP2924603A2

    • Full Citation: EP2924603A2 - Fmr Llc, "Method and system for user authentication based on biometrics, clothes wearing and surrounding scene"
    • Publication/Filing Date: Publication: 2015-09-30; Priority: 2014-03-25
    • Brief Description: Describes a user authentication technique where a client sends a captured video signal (including user characteristics and environmental objects) to a server. The server analyzes the video signal to determine values, calculates a total score, and compares it to a reference score for authorization. US11387982 explicitly states this as prior art and describes its shortcomings (bandwidth, privacy).
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate independent claims 1, 8, or 10. While it relates to collecting context data and authenticating, it directly transmits the raw video signal and calculates a score from that raw data, rather than generating a hash, a hash distance between hashes, and authenticating based on that hash distance as claimed by US11387982.

  8. WO2016083216A1

    • Full Citation: WO2016083216A1 - Gemalto Sa, "Method for accessing media data and corresponding device and system"
    • Publication/Filing Date: Publication: 2016-06-02; Priority: 2014-11-28
    • Brief Description: Describes methods for accessing media data, potentially including authentication mechanisms. The title is general, suggesting access control for media rather than a specific context-based hash distance authentication.
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate any claims of US11387982, as it does not disclose the specific steps of collecting context data for authentication, generating a hash from it, and using a hash distance for authentication.

  9. US20170109514A1

    • Full Citation: US20170109514A1 - Sri International, "Continuous authentication of mobile device users"
    • Publication/Filing Date: Publication: 2017-04-20; Priority: 2014-12-18
    • Brief Description: Describes systems and methods for continuous authentication of mobile device users based on various user and device characteristics (context data) collected over time.
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate independent claims 1, 8, or 10. While it involves collecting context data for authentication, it does not explicitly disclose generating a hash from this data, computing a hash distance between generated and reference hashes, or authenticating based on that distance, nor the specific "wherein" clauses of Claim 1.

  10. US9594906B1

    • Full Citation: US9594906B1 - Juniper Networks, Inc., "Confirming a malware infection on a client device using a remote access connection tool to identify a malicious file based on fuzzy hashes"
    • Publication/Filing Date: Publication: 2017-03-14; Priority: 2015-03-31
    • Brief Description: Describes confirming malware infections by calculating fuzzy hashes of files on a client device and comparing them to fuzzy hashes of known malicious files.
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate independent claims 1, 8, or 10. Similar to US20150096023A1, it uses fuzzy hashing for similarity detection, but in the context of malware files, not general context data (e.g., captured images) for user/environment authentication. It directly anticipates the technical principle of generating a hash distance (Claim 1, 9) and using fuzzy hash type algorithms for similarity (Claim 2).

  11. US20160323243A1

    • Full Citation: US20160323243A1 - Cirius Messaging Inc., "Data leak protection system and processing methods thereof"
    • Publication/Filing Date: Publication: 2016-11-03; Priority: 2015-05-01
    • Brief Description: Describes systems and methods for data leak protection, often involving scanning and identifying sensitive information within data streams or files.
    • Potential Anticipation (35 U.S.C. § 102): Does not anticipate any claims of US11387982. It focuses on data leak protection, which is a different inventive concept from context-based authentication via hash distance.

Generated 5/29/2026, 5:39:32 PM