A SYSTEM AND METHOD FOR THE VERIFICATION OF DIGITAL CERTIFICATES

Abstract

ABSTRACT A SYSTEM AND METHOD FOR THE VERIFICATION OF DIGITAL CERTIFICATES The present disclosure provides a system (100) and method (200) for verifying the authenticity of digital certificates, comprising a certificate digitization module (102) for converting physical certificates into digital form through imaging techniques. A hash generation module (104) computes a cryptographic hash value of the digital certificate using a secure hash technique. The cryptographic hash value is stored on a decentralized blockchain ledger (106), which ensures immutability through a consensus mechanism. A digital signature module (108) generates a digital signature using a private key, while a timestamping module (110) records the issuance time of the certificate. A verification module (112) compares the hash of a certificate under verification with the stored hash, validating the certificate's authenticity by checking the integrity of the digital signature and the accuracy of the timestamp. The system provides a secure, immutable, and decentralized method for verifying certificates, protecting against forgery, and ensuring trustworthiness.

Specification

Description:FIELD
The present disclosure relates to the digital security domain. More particularly, focusing on digital verification of the certificates.
DEFINITION
As used in the present disclosure, the following terms are generally intended to have the meaning as set forth below, except to the extent that the context in which they are used indicates otherwise.
1. Elliptic Curve Digital Signature Technique (ECDSA): The term "Elliptic Curve Digital Signature Technique (ECDSA)", refers to a cryptographic technique used to ensure the authenticity and integrity of messages or transactions. ECDSA is based on Elliptic Curve Cryptography (ECC) and provides a method for signing digital messages and verifying the signatures. It is widely used in secure communication protocols like TLS and blockchain technologies for validating transactions.
2. Proof-of-Stake (PoS): The term "Proof-of-Stake (PoS) ", refers to a consensus mechanism used in blockchain networks where validators are chosen to confirm transactions and produce new blocks based on the amount of cryptocurrency they hold and are willing to "stake" as collateral. PoS is considered more energy-efficient compared to Proof-of-Work (PoW), as it does not require solving complex computational problems.
3. YOLOv9 Technique: The term "YOLOv9 Technique " refers to a specific version of the "You Only Look Once" (YOLO) family of real-time object detection techniques. YOLOv9 is an advanced deep-learning model used to identify and localize objects within images or video frames. It builds on previous YOLO versions with enhancements in speed and accuracy for applications like autonomous driving, surveillance, and robotics.
4. Elliptic Curve Cryptography (ECC) Technique: The term "Elliptic Curve Cryptography (ECC) Technique" refers to a method of public key cryptography based on the mathematics of elliptic curves. ECC offers a high level of security with smaller key sizes compared to other techniques like RSA. This makes ECC more efficient and faster for encryption, digital signatures, and key exchange, making it suitable for use in mobile devices, SSL/TLS protocols, and blockchain technologies.
5. Quick Response (QR) Code: The term "Quick Response (QR) Code " refers to a two-dimensional barcode that stores information as a series of black and white squares arranged in a grid. QR codes can be scanned by a smartphone or other device to quickly access data, such as URLs, text, or payment information. QR codes are widely used in marketing, payments, and product tracking due to their convenience and ability to store more data than traditional barcodes.
The above definitions are in addition to those expressed in the art.
BACKGROUND
The background information herein below relates to the present disclosure but is not necessarily prior art.
In today's digital landscape, certificates, whether academic, professional, or otherwise, serve as critical credentials that validate an individual's qualifications or accomplishments. However, with the rise of digital documentation, there has also been a corresponding increase in fraudulent activities, including the creation of counterfeit certificates. Traditional methods of verifying the authenticity of these certificates, such as physical inspection or reliance on centralized databases, are often insufficient to counteract sophisticated forgery techniques.
While some solutions incorporate basic cryptographic approaches to secure digital certificates, these methods often face challenges related to scalability, tamper-proofing, and ease of verification. Additionally, with the increase in the volume of digital certificates issued globally, there is a need for a more efficient and scalable solution that can provide secure, real-time verification without compromising the integrity of the data or the privacy of the users.
Moreover, existing methods may not adequately address the issue of visual tampering, where legitimate certificates are altered post-issuance, leading to fraud. The need for a system that can not only ensure data integrity but also analyse visual elements of certificates is becoming increasingly important.
Therefore, there is a need for a system and method for the verification of digital certificates that alleviates the aforementioned drawbacks.
OBJECTS
Some of the objects of the present disclosure, which at least one embodiment herein satisfies, are as follows:
It is an object of the present disclosure to ameliorate one or more problems of the prior art or to at least provide a useful alternative.
An object of the present disclosure is to provide a system for the verification of digital certificates.
Another object of the present disclosure is to provide a system that verifies, is secure, efficient, and scalable.
Still another object of the present disclosure is to provide a system that simplifies the verification of digital certificates in a way that is resistant to tampering and forgery.
Yet another object of the present disclosure is to provide a system that provides a solution that enhances transparency and trust among stakeholders, including certificate holders, employers, and institutions.
Still another object of the present disclosure is to provide a system that improves the overall accuracy, speed, and security of certificate verification processes.
Yet another object of the present disclosure is to provide a system that promotes the use of secure digital certificates, reducing reliance on paper-based credentials.
Still another object of the present disclosure is to provide a system that reduces the time and cost of manual verification by automating the process.
Yet another object of the present disclosure is to provide a method for verification of digital certificates.
Other objects and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.
SUMMARY
The present disclosure provides a system for verifying the authenticity of digital certificates, comprising: a certificate digitization module, a hash generation module, a blockchain network, a digital signature module, a timestamping generation module, and a verification module.
The certificate digitization module is configured to receive a physical certificate on a scanning device and further configured to scan and convert the physical certificate into a digital certificate by means of imaging techniques.
The hash generation module is configured to compute a cryptographic hash value corresponding to the digital certificate by means of a secure hash technique.
The blockchain network implementing a decentralised blockchain ledger, wherein said decentralised blockchain ledger is configured to:
- receive and store the cryptographic hash value of the digital certificate; and
- secure the stored hash with a consensus technique ensuring immutability.
The digital signature module is configured to generate a digital signature by means of a private key to sign the cryptographic hash value of the digital certificate.
The timestamping generation module is configured to generate a timestamp to indicate the precise issuance time of the digital certificate; and
The verification module is configured to:
- compare the calculated hash of a certificate under verification with the stored on the blockchain network; and
- validate the authenticity of the certificate by checking the integrity of the digital signature and the validity of the timestamp.
In an embodiment, further comprises an object detection module fine-tuned with a YOLOV9 technique, wherein the object detection module is configured to detect specific visual elements of certificates including seals, logos, and signatures to identify forgery attempts based on discrepancies in the detected objects.
In an embodiment, wherein the digital signature module is configured to use an elliptic curve digital signature technique (ECDSA) to sign the certificate's cryptographic hash, providing enhanced security and reduced computational overhead compared to traditional RSA techniques.
In an embodiment, wherein the generation module utilizes a trusted third-party timestamping service, thereby ensuring the certificate's issuance time is probably linked to a trusted external authority, enhancing legal compliance and accountability.
In an embodiment, wherein the blockchain network is configured to use a proof-of-stake (PoS) consensus technique to minimize energy consumption while maintaining the integrity and security of the certificate verification process.
In an embodiment, the system (100) further comprises a quick response (QR) code generation module configured to:
- generate a QR code for each verified certificate, and
- embed the certificate's hash, digital signature, and timestamp within the QR code, allowing for instant verification of the certificate's authenticity by scanning the QR code.
In an embodiment, the QR code is configured to be scanned using a mobile or web-based application, which retrieves the certificate's corresponding hash, digital signature, and timestamp from the blockchain for real-time verification of authenticity.
In an embodiment, the blockchain network is configured to store multiple versions of a certificate's cryptographic hash corresponding to any revisions or updates, ensuring that the history of changes to a certificate can be tracked and verified over time.
In an embodiment, the object detection module is further configured to implement machine learning techniques to adaptively improve its ability to detect anomalies or fraudulent modifications in certificate elements based on training data, enhancing the system's ability to detect emerging forgery techniques.
In an embodiment, the verification module further comprises an artificial intelligence (AI) based anomaly detection submodule configured to analyse digital certificates for subtle signs of forgery, including manipulated fonts, altered content, or irregular patterns that may indicate document tampering.
The present disclosure provides a method for verifying the authenticity of digital certificates, comprising:
• converting a physical certificate into a digital format by a certificate digitization module ;
• computing a cryptographic hash of the digital certificate by a hash generation module;
• signing, by a digital signature module, the cryptographic hash using a digital signature technique to generate a digital signature;
• generating, by a timestamping generation module, a timestamp indicating the exact time of certificate issuance;
• registering the cryptographic hash, digital signature, and timestamp on a blockchain network to ensure immutability;
• verifying a certificate by a verification module, said verifying comprises:
• comparing a recalculated hash of the presented certificate with the hash stored on the blockchain network;
• validating the integrity of the digital signature; and
• ensuring the certificate's issuance time corresponds to the stored timestamp.
In an embodiment, the method further comprises the step of utilizing an object detection technique to automatically identify key visual elements of the certificate, including seals, signatures, and watermarks, and cross-referencing the detected elements with the stored data to detect potential forgeries.
In an embodiment, the method includes the digital signature generated using an elliptic curve cryptography (ECC) technique, providing increased efficiency and security in the signing process.
In an embodiment, the method further comprises the step of generating a quick response (QR) code that encodes the certificate's hash, digital signature, and timestamp, allowing instant verification by scanning the QR code.
In an embodiment, the method includes the blockchain network operating using a proof-of-stake consensus technique, ensuring energy-efficient and secure storage of certification data.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWING
A system and method for verification of digital certificates, of the present disclosure will now be described with the help of the accompanying drawing in which:
Figure 1 illustrates a block diagram of a system for verification of digital certificates, in accordance with an embodiment of the present disclosure;
Figures 2A and 2B illustrate a flowchart of a method for verification of digital certificates, in accordance with an embodiment of the present disclosure; and
Figure 3 illustrates screenshots of an exemplary verification method, in accordance with the present disclosure.
LIST OF REFERENCE NUMERALS
100 System
101 The scanning device
102 Certificate digitization module
104 Hash generation module
106 Blockchain network
108 Digital signature module
110 Timestamp generation module.
112 Verification module
114 Object detection module.
116 Quick response (QR) code generation module
200-210 Method and method steps
DETAILED DESCRIPTION
The present disclosure relates to the field of digital security and certificate verification. More specifically, it focuses on systems and methods for authenticating digital certificates using cryptographic techniques, blockchain technology, and machine learning to enhance security and trust in various digital environments.
Embodiments, of the present disclosure, will now be described with reference to the accompanying drawing.
Embodiments are provided so as to thoroughly and fully convey the scope of the present disclosure to the person skilled in the art. Numerous details are set forth, relating to specific components, and methods, to provide a complete understanding of embodiments of the present disclosure. It will be apparent to the person skilled in the art that the details provided in the embodiments should not be construed to limit the scope of the present disclosure. In some embodiments, well known processes, well known apparatus structures, and well known techniques are not described in detail.
The terminology used, in the present disclosure, is only for the purpose of explaining a particular embodiment and such terminology shall not be considered to limit the scope of the present disclosure. As used in the present disclosure, the forms "a," "an," and "the" may be intended to include the plural forms as well, unless the context clearly suggests otherwise. The terms "including," and "having," are open ended transitional phrases and therefore specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not forbid the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. The particular order of steps disclosed in the method and process of the present disclosure is not to be construed as necessarily requiring their performance as described or illustrated. It is also to be understood that additional or alternative steps may be employed.
When an element is referred to as being "engaged to," "connected to," or "coupled to" another element, it may be directly engaged, connected, or coupled to the other element. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed elements.
Referring to Figure 1, the present disclosure provides a system (100) for verifying the authenticity of digital certificates, comprising: a certificate digitization module (102), a hash generation module (104), a blockchain network (106), a digital signature module (108), a timestamping generation module (110), and a verification module (112).
The certificate digitization module (102) is configured to receive a physical certificate on a scanning device (101) and further configured to scan and convert the physical certificate into a digital certificate by means of imaging techniques.
The hash generation module (104) is configured to compute a cryptographic hash value corresponding to the digital certificate by means of a secure hash technique.
The blockchain network (106) implements a decentralised blockchain ledger, wherein the decentralised blockchain ledger is configured to:
- receive and store the cryptographic hash value of the digital certificate; and
- secure the stored hash with a consensus technique ensuring immutability.
The digital signature module (108) is configured to generate a digital signature by means of a private key to sign the cryptographic hash value of the digital certificate;
The timestamping generation module (110) is configured to generate a timestamp to indicate the precise issuance time of the digital certificate; and
The verification module (112) is configured to:
- compare the calculated hash of a certificate under verification with the stored on the blockchain network (106); and
- validate the authenticity of the certificate by checking the integrity of the digital signature and the validity of the timestamp.
In an embodiment, further comprises an object detection module (114) fine-tuned with a YOLOV9 technique, wherein the object detection module (114) is configured to detect specific visual elements of certificates including seals, logos, and signatures to identify forgery attempts based on discrepancies in the detected objects.
In an embodiment, wherein the digital signature module (108) is configured to use an elliptic curve digital signature technique (ECDSA) to sign the certificate's cryptographic hash, providing enhanced security and reduced computational overhead compared to traditional RSA techniques.
In an embodiment, wherein the generation module (110) utilizes a trusted third-party timestamping service, thereby ensuring the certificate's issuance time is probably linked to a trusted external authority, enhancing legal compliance and accountability.
In an embodiment, wherein the blockchain network (106) is configured to use a proof-of-stake (PoS) consensus technique to minimize energy consumption while maintaining the integrity and security of the certificate verification process.
In an embodiment, the system (100) further comprises a quick response (QR) code generation module (116) configured to:
- generate a QR code for each verified certificate, and
- embed the certificate's hash, digital signature, and timestamp within the QR code, allowing for instant verification of the certificate's authenticity by scanning the QR code.
In an embodiment, the QR code is configured to be scanned using a mobile or web-based application, which retrieves the certificate's corresponding hash, digital signature, and timestamp from the blockchain for real-time verification of authenticity.
In an embodiment, the blockchain network (106) is configured to store multiple versions of a certificate's cryptographic hash corresponding to any revisions or updates, ensuring that the history of changes to a certificate can be tracked and verified over time.
In an embodiment, the object detection module (114) is further configured to implement machine learning techniques to adaptively improve its ability to detect anomalies or fraudulent modifications in certificate elements based on training data, enhancing the system's ability to detect emerging forgery techniques.
In an embodiment, the verification module (114) further comprises an artificial intelligence (AI) based anomaly detection submodule configured to analyse digital certificates for subtle signs of forgery, including manipulated fonts, altered content, or irregular patterns that may indicate document tampering.
In an embodiment, the system (100) can include one or more processors and may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processors are configured to fetch and execute computer-readable instructions stored in a memory of the system 100. The memory may store one or more computer-readable instructions or routines, which may be fetched and executed for executing the instructions. The memory may include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like. The functions of one or more processor(s) may be provided through the use of dedicated hardware as well as hardware capable of executing machine-readable instructions. In other examples, one or more processors may be implemented by electronic circuitry or printed circuit board. One or more processors may be configured to execute functions of various modules of the system (100).
In an alternative aspect, the memory may be an external data storage device coupled to the system (100) directly or through one or more offline/online data servers.
In an embodiment, the system (100) further comprises a network interface to receive real-time data inputs from external sources such as databases, APIs, and sensors, which are used by the system (100). The network interface may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, transceivers, storage devices, and the like. The network interface may facilitate communication of the system (100) with various devices coupled to the system (100). The network interface may also provide a communication pathway for one or more components of the system 100. Examples of such components include, but are not limited to, processing module(s) and data storage.
The module(s) of the system (100) may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing module(s). In the examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the module(s) may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the module(s) may include a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the module(s). In such examples, the system (100) may include the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system (100) and the processing resource. In other examples, the module(s) may be implemented by electronic circuitry.
Figures 2A and 2B illustrate a flowchart that includes the steps involved in a method (200) for verification of digital certificates, in accordance with an embodiment of the present disclosure. The order in which method (200) is described is not intended to be construed as a limitation, and any number of the described method (200) steps may be combined in any order to implement method (200), or an alternative method. Furthermore, method (200) may be implemented by processing resource or electronic device(s) through any suitable hardware, non-transitory machine-readable medium/instructions, or a combination thereof. The method (200) comprises the following steps:
At step (202), the method (200) includes converting a physical certificate into a digital format by a certificate digitization module (102).
At step (204), the method (200) includes computing a cryptographic hash of the digital certificate by a hash generation module (104).
At step (206), the method (200) includes signing, by a digital signature module (108), the cryptographic hash using a digital signature technique to generate a digital signature.
At step (208), the method (200) includes generating, by a timestamping generation module (110), a timestamp indicating the exact time of certificate issuance.
At step (210), the method (200) includes registering the cryptographic hash, digital signature, and timestamp on a blockchain network (106) to ensure immutability.
At step (212), the method (200) includes verifying a certificate by a verification module (112), the verifying comprises:
At step (214), the method (200) includes comparing a recalculated hash of the presented certificate with the hash stored on the blockchain network (106).
At step (216), the method (200) includes validating the integrity of the digital signature.
At step (218), the method (200) includes ensuring the certificate's issuance time corresponds to the stored timestamp.
Figure 3 depicts an interface for a certificate verification system, likely designed to detect fraudulent certifications using blockchain technology. It includes various modules such as a certificate registration form, certificate authenticity check, and a "fake certification detection" system. The blockchain's cryptographic hash is visible, ensuring the integrity of the certificates. The interface also displays a QR code that presumably links to a detailed record of the certificate on the blockchain. There are multiple user prompts, including options for adding certificates, verifying them against the blockchain, and using an admin interface. The focus seems to be on using secure, decentralized techniques to ensure that certificates are genuine, providing a tamper-proof mechanism to detect and prevent forgery.
In an embodiment, the method (200) further comprises the step of utilizing an object detection technique to automatically identify key visual elements of the certificate, including seals, signatures, and watermarks, and cross-referencing the detected elements with the stored data to detect potential forgeries.
In an embodiment, the method (200) includes the digital signature generated using an elliptic curve cryptography (ECC) technique, providing increased efficiency and security in the signing process.
In an embodiment, the method (200) further comprises the step of generating a quick response (QR) code that encodes the certificate's hash, digital signature, and timestamp, allowing instant verification by scanning the QR code.
In an embodiment, the method (200) includes the blockchain network (106) operating using a proof-of-stake consensus technique, ensuring energy-efficient and secure storage of certification data.
Alternative Embodiments:
In another embodiment, the system (100) may utilize different types of blockchain networks, such as public, private, or consortium blockchains, depending on the use case. For example, a consortium blockchain could be employed for academic institutions where only authorized entities can validate and verify certificates, while a public blockchain might be used for a more open and decentralized approach.
In an alternative configuration, the digital signature module (102) may incorporate various cryptographic techniques beyond asymmetric cryptography, such as elliptic curve cryptography (ECC), lattice-based cryptography, or post-quantum cryptographic techniques. This ensures the system is adaptable to future cryptographic standards, particularly for use in environments that require quantum-resistant security.
Instead of a centralized timestamping service (103), the system can use a distributed and decentralized timestamping mechanism where multiple independent nodes contribute to consensus on the timestamp, making it even harder to falsify the issuance time of certificates.
In another embodiment, the system (100) can be configured to work with existing, non-blockchain-based certificate systems. By providing an API or middleware, the blockchain-backed verification system can integrate with legacy systems, ensuring backward compatibility while enhancing security and verification capabilities.
In a further embodiment, the digital signature module (102) could implement multi-factor authentication (MFA) for certificate issuers. This would require issuers to use a combination of biometric verification, hardware tokens, or one-time passwords (OTPs) in addition to cryptographic signatures, adding an extra layer of security to the certificate issuance process.
Another embodiment could involve a mobile application that allows for offline verification. The mobile app could store a lightweight copy of the blockchain or essential certificate hashes locally, enabling verification in environments with limited internet connectivity. Once the device reconnects to the internet, it synchronizes with the blockchain for updated verification status.
In an alternative embodiment, the object detection module (104) could include natural language processing (NLP) techniques to verify not just the visual features of a certificate but also its textual content. For instance, discrepancies in text formatting, terminology, or issuer details can be flagged as potential indicators of forgery.
In another embodiment, the system (100) may be configured to verify multiple certificates simultaneously. This is particularly useful for employers or institutions that need to verify a batch of certificates at once, optimizing the process by conducting parallel checks and providing a consolidated report.
An alternative embodiment may integrate geo-location services with the user interface (105). This would allow verification requests to be geo-tagged, providing stakeholders with information about the location where a certificate was verified, thereby adding another layer of security to the process.
In this embodiment, biometric data (e.g., fingerprint or facial recognition) could be linked to certificates during issuance. This ensures that the certificate is not just authenticated by the blockchain but also linked directly to the individual it was
In an embodiment, the system (100) could allow third-party service providers or external verification authorities to plug into the blockchain network (101) via a standardized API. This would enable additional levels of trust by allowing external entities to cross-check and independently verify the certificates without compromising security or data privacy.
In another embodiment, the system (100) may include a module for revoking or updating certificates. If a certificate is found to be compromised, it can be marked as invalid on the blockchain. Similarly, if a certificate needs updating (e.g., change of legal name), a new certificate can be issued while maintaining a record of the previous one.
In a further embodiment, the object detection module (104) may incorporate artificial intelligence techniques such as deep learning to detect advanced forgery attempts. The system could learn from patterns in known forgery cases and continuously update its detection techniques to respond to new and evolving fraud techniques.
In this embodiment, the system (100) can be configured to operate in a hybrid architecture, where the blockchain is used for secure and immutable record-keeping, while other certificate-related data (e.g., verification logs or analytics) is stored in a scalable cloud environment. This ensures flexibility and performance optimization for high-volume verification tasks.
In a further embodiment, the system (100) could integrate with self-sovereign identity (SSI) frameworks, allowing certificate holders to control their credentials directly. Holders could grant or revoke access to their certificates without requiring intermediaries, enhancing privacy and personal control over digital identity.
In an operative configuration, the system (100) for verifying the authenticity of digital certificates operates by first storing digital certificates and their corresponding hash values on a blockchain network (101), ensuring that records are maintained in a tamper-proof and decentralized manner. The digital signature module (102) utilizes asymmetric cryptography to authenticate the identity of certificate issuers, safeguarding against unauthorized access and forgery. Upon issuance, a timestamping service (103) records the exact time of certificate generation, providing non-repudiation and preserving the chronological order of certificate issuance. The object detection module (104), equipped with a machine learning model such as YOLOV9, analyzes visual features of the certificates to detect anomalies, such as alterations to seals or signatures, enhancing the detection of counterfeit certificates. Verification requests are initiated through a user interface (105), where stakeholders can submit certificates for validation, review verification results, and access detailed analytics on verification attempts. The system (100) may also generate unique QR codes (106) for each certificate to enable instant mobile verification.
Advantageously, the system (100) offers a highly secure, decentralized solution for verifying the authenticity of digital certificates, minimizing the risk of forgery and unauthorized alterations. By leveraging blockchain technology (101), the system ensures immutable storage of certificates, which enhances transparency and trust among stakeholders, including certificate holders, issuers, and verifiers. The integration of a digital signature module (102) further strengthens the system's security by allowing for the cryptographic verification of certificate issuers, while the timestamping service (103) provides a reliable audit trail that ensures certificates are issued and recorded in a verifiable chronological sequence. The object detection module (104), utilizing advanced machine learning models, automates the process of identifying visual discrepancies on certificates, significantly improving the accuracy and efficiency of the verification process. The QR code generator (106) makes the system more accessible, allowing for quick and convenient certificate validation through mobile devices, further promoting ease of use. Additionally, the user interface (105) offers real-time analytics and reporting, enabling stakeholders to monitor verification activity and make informed decisions with greater confidence.
The functions described herein may be implemented in hardware, executed by a processor, firmware, or any combination thereof. Other examples and implementations are within the scope and spirit of the disclosure and appended claims. The present disclosure can be implemented by a processor, hardware, firmware, hardwiring, or combinations of any of these. Features implementing functions may also be physically located at various positions, including being distributed such that portions of functions are implemented at different physical locations.
The foregoing description of the embodiments has been provided for purposes of illustration and is not intended to limit the scope of the present disclosure. Individual components of a particular embodiment are generally not limited to that particular embodiment, but, are interchangeable. Such variations are not to be regarded as a departure from the present disclosure, and all such modifications are considered to be within the scope of the present disclosure.
TECHNICAL ADVANCEMENTS
The present disclosure described hereinabove has several technical advantages including, but not limited to, a system and method for the verification of digital certificates, which;
• verifies, is secure, efficient, and scalable;
• simplifies the verification of digital certificates in a way that is resistant to tampering and forgery;
• provides a solution that enhances transparency and trust among stakeholders, including certificate holders, employers, and institutions;
• improves the overall accuracy, speed, and security of certificate verification processes;
• promotes the use of secure digital certificates, reducing reliance on paper-based credentials; and
• reduces the time and cost of manual verification by automating the process.
The foregoing disclosure has been described with reference to the accompanying embodiments which do not limit the scope and ambit of the disclosure. The description provided is purely by way of example and illustration.
The embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
The foregoing description of the specific embodiments so fully reveals the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.
Any discussion of devices, articles or the like that has been included in this specification is solely for the purpose of providing a context for the disclosure. It is not to be taken as an admission that any or all of these matters form a part of the prior art base or were common general knowledge in the field relevant to the disclosure as it existed anywhere before the priority date of this application.
While considerable emphasis has been placed herein on the components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation. , Claims:WE CLAIM:
1. A system (100) for the verification of digital certificates, comprising:
• a certificate digitization module (102) configured to receive a physical certificate on a scanning device (101), and further configured to scan and convert the physical certificate into a digital certificate by means of imaging techniques;
• a hash generation module (104) configured to compute a cryptographic hash value corresponding to the digital certificate by means of a secure hash technique;
• a blockchain network (106) implementing a decentralised blockchain ledger, wherein said decentralised blockchain ledger is configured to:
- receive and store the cryptographic hash value of the digital certificate; and
- secure the stored hash with a consensus technique ensuring immutability;
• a digital signature module (108) configured to generate a digital signature by means of a private key to sign the cryptographic hash value of the digital certificate;
• a timestamping generation module (110) configured to generate a timestamp to indicate the precise issuance time of the digital certificate; and
• a verification module (112) configured to:
- compare the calculated hash of a certificate under verification with the stored on the blockchain network (106); and
- validate the authenticity of the certificate by checking the integrity of the digital signature and the validity of the timestamp.
2. The system (100) as claimed in claim 1, further comprises an object detection module (114) fine-tuned with a YOLOV9 technique, wherein said object detection module (114) is configured to detect specific visual elements of certificates including seals, logos, and signatures to identify forgery attempts based on discrepancies in the detected objects.
3. The system (100) as claimed in claim 1, wherein said digital signature module (108) is configured to use an elliptic curve digital signature technique (ECDSA) to sign the certificate's cryptographic hash, providing enhanced security and reduced computational overhead compared to traditional RSA techniques.
4. The system (100) as claimed in claim 1, wherein said generation module (110) utilizes a trusted third-party timestamping service, thereby ensuring the certificate's issuance time is probably linked to a trusted external authority, enhancing legal compliance and accountability.
5. The system (100) as claimed in claim 1, wherein said blockchain network (106) is configured to use a proof-of-stake (PoS) consensus technique to minimize energy consumption while maintaining the integrity and security of the certificate verification process.
6. The system (100) as claimed in claim 1, further comprises a quick response (QR) code generation module (116) configured to:
- generate a QR code for each verified certificate, and
- embed the certificate's hash, digital signature, and timestamp within said QR code, allowing for instant verification of the certificate's authenticity by scanning said QR code.
7. The system (100) as claimed in claim 1, wherein said QR code is configured to be scanned using a mobile or web-based application, which retrieves the certificate's corresponding hash, digital signature, and timestamp from the blockchain for real-time verification of authenticity.
8. The system (100) as claimed in claim 1, wherein said blockchain network (106) is configured to store multiple versions of a certificate's cryptographic hash corresponding to any revisions or updates, ensuring that the history of changes to a certificate can be tracked and verified over time.
9. The system (100) as claimed in claim 2, wherein said object detection module (114) is further configured to implement machine learning techniques to adaptively improve its ability to detect anomalies or fraudulent modifications in certificate elements based on training data, enhancing the system's ability to detect emerging forgery techniques.
10. The system (100) as claimed in claim 1, wherein said verification module (114) further comprises an artificial intelligence (AI) based anomaly detection submodule configured to analyze digital certificates for subtle signs of forgery, including manipulated fonts, altered content, or irregular patterns that may indicate document tampering.
11. A method (200) for the verification of digital certificates, comprising:
• converting a physical certificate into a digital format by a certificate digitization module (102);
• computing a cryptographic hash of the digital certificate by a hash generation module (104);
• signing, by a digital signature module (108), the cryptographic hash using a digital signature technique to generate a digital signature;
• generating, by a timestamping generation module (110), a timestamp indicating the exact time of certificate issuance;
• registering the cryptographic hash, digital signature, and timestamp on a blockchain network (106) to ensure immutability; and
• verifying a certificate by a verification module (112), said verifying comprises:
- comparing a recalculated hash of the presented certificate with the hash stored on the blockchain network (106),
- validating the integrity of the digital signature, and
- ensuring the certificate's issuance time corresponds to the stored timestamp;

12. The method (200) as claimed in claim 11, further comprises the step of utilizing an object detection technique to automatically identify key visual elements of the certificate, including seals, signatures, and watermarks, and cross-referencing the detected elements with the stored data to detect potential forgeries.
13. The method (200) as claimed in claim 11, wherein said digital signature is generated using an elliptic curve cryptography (ECC) technique, provides increased efficiency and security in the signing process.
14. The method (200) as claimed in claim 11, further comprises the step of generating a quick response (QR) code that encodes the certificate's hash, digital signature, and timestamp, allowing instant verification by scanning the QR code.
15. The method as claimed in claim 11, wherein said blockchain network (106) operates using a proof-of-stake consensus technique, ensuring energy-efficient and secure storage of certification data.

Dated this 11th day of November, 2024

_______________________________
MOHAN RAJKUMAR DEWAN, IN/PA - 25
OF R. K. DEWAN & CO.
AUTHORIZED AGENT OF APPLICANT

TO,
THE CONTROLLER OF PATENTS
THE PATENT OFFICE, CHENNAI

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