A physical anchoring and data monitoring method based on PUF tag

Abstract

The application discloses a kind of based on PUF label's real anchor and data supervision method, it is related to electronic tag anti-fake and real supervision field, including: generating PUF hardware fingerprint, with PUF label identification and real basic information are bound storage;Generate physical anchor check result;Generate data anchor check result, and with physical anchor check result fusion obtains final anchor check result;The state data of physical real object is acquired, is encrypted in combination with PUF hardware fingerprint and time stamp, generates encrypted state data and its integrity hash value;Related data is uploaded to block chain, is stored after integrity verification and generates chain voucher;Anchor check process is repeatedly executed, update final anchor check result, if abnormal, trigger early warning and record abnormal information to block chain;After authorization verification, sensitive data is destroyed and PUF label self-destruction is triggered, and anchor is removed.It realizes the anchor credible of physical real object whole life cycle supervision, data real and process traceable.

Description

Technical Field

[0001] This invention relates to the field of electronic tag anti-counterfeiting and physical object supervision, and more specifically to a method for physical object anchoring and data supervision based on PUF tags. Background Technology

[0002] In the fields of shipping trade, finished equipment circulation and high-value asset supervision, the identification and status tracking of physical objects are related to supply chain security and asset integrity. Traditional supervision methods usually rely on ordinary electronic tags to store physical identification information, and combine them with sensors to collect status data such as temperature and location and upload them to the supervision platform to achieve physical tracking in a visual way.

[0003] However, such solutions have a fundamental flaw at the physical anchoring level: the binding between electronic tags and physical objects is only a logical association at the identification information level, lacking a real-time physical verification mechanism for the adhesion status of the tag and the physical object. Attackers can remove the tag and replace it with other physical objects without triggering an alarm, or forge the identity of the physical object by copying the static identification information stored in the tag. Even if some solutions introduce physically unclonable functions to protect the tag itself from counterfeiting, it is limited to anti-cloning at the tag chip level and does not extend the PUF feature to the physical binding relationship between the tag and the physical object. This makes the anchoring relationship very easy to be destroyed by physical attacks, and regulators cannot distinguish between the two states: the tag is intact but has been damaged and the tag is normally anchored.

[0004] Regarding data trustworthiness, existing technologies lack an end-to-end encryption and integrity protection chain. When sensor-collected status data is transmitted to regulatory platforms or blockchains, it is usually in plaintext or simple checksum form. Intermediate nodes can easily tamper with key parameters such as temperature, humidity, and location and regenerate checksums, creating a regulatory blind spot where off-chain data is forged and on-chain records are invalid. Even with blockchain notarization, it can only guarantee that the data cannot be tampered with after it is uploaded to the chain, but it cannot constrain the authenticity and integrity of the data before it is uploaded to the chain. This makes the blockchain a tool for storing fake data and cannot solve the fundamental problem of data trustworthiness at the source.

[0005] Furthermore, the existing regulatory mechanisms lack dynamic adaptability and full lifecycle security protection. Anchoring verification is usually performed mechanically at a fixed frequency, which cannot dynamically adjust the verification intensity according to the stability of the physical object. This results in the consumption of a large amount of communication and computing resources even when the anchoring state is continuously stable, and the inability to detect risks in a timely manner when the anchoring relationship shows intermittent anomalies. At the same time, the anchoring removal process only relies on operator authorization verification and lacks a two-way security authentication mechanism that is bound to the PUF hardware fingerprint. This makes it possible for sensitive hardware that has been unanchored to be maliciously restored or re-bound, which fails to meet the closed-loop regulatory requirements for the entire lifecycle of physical objects from binding, monitoring to removal.

[0006] Therefore, how to design a physical anchoring and data supervision method based on PUF tags to achieve reliable binding between physical objects and electronic tags, tamper-proof status data throughout the entire process, and efficient and controllable supervision is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0007] In view of this, the present invention provides a physical anchoring and data supervision method based on PUF tags, which aims to solve the problems of unreliable electronic tags and physical anchoring, easy tampering of status data, and lack of dynamic linkage and anti-attack capabilities in the supervision process in the prior art. By constructing a dual mechanism of physical anchoring and data anchoring and integrating PUF hardware fingerprints into edge computing and blockchain closed loop, it realizes full life cycle trusted supervision with unforgeable physical identity, untamperable status data, and real-time early warning of abnormal behavior.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] A method for physical anchoring and data monitoring based on PUF tags includes the following steps: S1. Generate a PUF hardware fingerprint, and bind and store the PUF hardware fingerprint with the PUF tag identifier and physical basic information to establish a reliable association between the edge computing unit and the PUF tag; S2. Generate physical anchoring verification results based on the tamper-proof status of the PUF tag; S3. Send a random challenge signal to the PUF tag to verify the response signal, generate a data anchoring verification result, and fuse it with the physical anchoring verification result to obtain the final anchoring verification result. S4. Obtain the physical object's status data, encrypt it using the PUF hardware fingerprint and timestamp, and generate encrypted status data and its integrity hash value. S5. Upload the encrypted state data, integrity hash value, final anchoring verification result, PUF hardware fingerprint, tag identifier, physical basic information, and timestamp to the blockchain, store them after integrity verification, and generate on-chain credentials. S6. Repeat S2 and S3 to update the final anchor verification result. If there is an error, trigger an alert and record the error information to the blockchain. S7. After authorization verification, destroy sensitive data and trigger PUF tag self-destruction to complete anchor release.

[0010] Preferably, S2 includes: Within the preset time window Internal acquisition of multiple sets of signals , For tamper prevention signal, This is the fit signal; Calculate the anti-tamper fluctuation coefficient Fitting the fluctuation coefficient ;in , Here, N represents the corresponding signal mean, and N is the number of sampling points. like , ,and , The physical anchoring verification result =1, otherwise 0; where , For fluctuation threshold, , This is the mean threshold.

[0011] Preferably, in step S3, the response signal verification includes: The edge computing unit generates a random challenge signal (Chal) and sends it to the PUF tag; The PUF tag's built-in PUF circuit generates a response signal Resp for the Chal operation and returns it; The edge computing unit utilizes its PUF hardware subunit to calculate the reference response Resp′ for the same Chal and to calculate the difference. , where j is the bit index of the response signal and L is the bit length; like , If the fault tolerance threshold is used, then the data anchoring verification result is... Otherwise, it is 0.

[0012] Preferably, in step S3, the final anchoring verification result is obtained. include: Obtain the historical final anchoring result sequence Calculate confidence level ; Calculate the current anchoring consistency coefficient ;like and ,but ;like but If so, historical backtracking verification is triggered to re-verify historical data; if ,but ; in, For the physical anchoring verification results, The data is used to anchor the verification result, where M is the total number of elements in the sequence. This is the confidence threshold.

[0013] Preferably, in step S4, the encrypted state data Represented as:

[0014] Integrity hash value Represented as:

[0015] in, For encryption functions, For hash functions, For PUF hardware fingerprinting, The root key is pre-placed in the secure storage area of ​​the edge computing unit. This indicates splicing / joining. For the collected physical state data, For collection timestamps.

[0016] Preferably, in step S5, the integrity verification includes: The blockchain smart contract processes the received encrypted state data Enc through... The hash function calculates a hash value, and the result is compared with the received integrity hash value. The data is compared; if they match, the data is written to the blockchain, and an on-chain certificate containing the transaction hash and block height is generated. Otherwise, the blockchain will be rejected and an alert will be triggered.

[0017] Preferably, in step S6, updating the final anchoring verification result includes: Set dynamic verification interval ,in, As the baseline verification interval, For adaptive coefficients, This represents the current confidence level. Execute S2 and S3 at each verification time to obtain the current final anchoring verification result. ; Update historical anchoring result sequence And slide to update the confidence level ρ; If the K consecutive verification results Ac=1 and the confidence level is... Then dynamically increase the verification interval to If Ac=0 occurs even once, the check interval will be immediately restored to the previous value. ;in Minimum verification interval The maximum verification interval, This is the confidence threshold for the steady state.

[0018] Preferably, in step S7, destroying sensitive data and triggering PUF tag self-destruction includes: The monitoring terminal initiated an anchor release request, which included a PUF-based hardware fingerprint. Generated temporary session token ,in To request a timestamp, It is a random number; The edge computing unit verifies the validity of the token. After successful verification, it performs a secure erasure operation to delete the locally stored PUF hardware fingerprint, tag identification, physical basic information, and root key. Send a self-destruct command containing a self-destruct verification code to the PUF tag. ,in This is the timestamp for the self-destruct instruction; after receiving the self-destruct verification code, the PUF tag will disconnect its internal storage unit from the external pins once the verification is successful.

[0019] As can be seen from the above technical solution, compared with the prior art, the technical solution of the present invention has the following beneficial effects: 1. This method employs a dual verification mechanism of physical and data anchoring. At the physical level, it uses the fluctuation coefficient and mean threshold of the anti-tamper signal to monitor the adhesion status between the tag and the object in real time. At the data level, it uses the challenge-response mechanism of the PUF circuit to dynamically verify the legitimacy of the tag. The two are then combined to form the final anchoring verification result. Historical confidence is also introduced to comprehensively judge the anchoring result. This mechanism ensures that any act of removing the tag, replacing the tag, or forging the identity will be captured in real time and trigger an early warning, ensuring that the anchoring relationship between the tag and the object is tamper-proof and tamper-proof.

[0020] 2. Using the PUF hardware fingerprint as the core root of trust, encrypted state data is generated by binding the root key with the PUF fingerprint during the data encryption process. Before the data is uploaded to the blockchain, an integrity verification value is generated through hash calculation. During the blockchain storage process, a smart contract performs a second verification on the encrypted data and the hash value. This closed-loop mechanism ensures that the state data is protected by hardware-level encryption and hash verification throughout the entire process from sensor collection and edge computing processing to blockchain storage. Any tampering with the original data will result in the integrity verification failing and the data being rejected from being uploaded to the blockchain, thus effectively solving the problems of off-chain forgery and invalid on-chain data.

[0021] 3. Through a dynamic verification interval mechanism, the verification frequency is adaptively adjusted based on historical anchoring confidence: when the anchoring state is stable for a long period of time, the verification interval is automatically extended to reduce system power consumption and communication load; when an anomaly occurs, high-frequency verification is immediately restored to capture subsequent risks, achieving a dynamic balance between resource consumption and monitoring timeliness; and in the anchoring release process, a temporary session token generated based on PUF hardware fingerprint and a self-destruct verification code are used for bidirectional verification to ensure that the anchoring release command must be jointly confirmed by the edge computing unit holding a valid PUF fingerprint and the tag before it can be executed, effectively preventing malicious release or misoperation that could cause the anchoring relationship to fail. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0023] Figure 1 A flowchart of a physical anchoring and data monitoring method based on PUF tags provided in this embodiment of the invention; Figure 2 A schematic diagram of the physical anchoring and data monitoring process based on PUF tags in a container transportation scenario provided by an embodiment of the present invention; Figure 3 This is a schematic diagram showing the installation location of the PUF tag and the edge computing unit provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the PUF tag structure provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the container transportation supervision system provided in an embodiment of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] like Figure 1 As shown, this embodiment provides a method for physical anchoring and data monitoring based on PUF tags, including the following steps: S1. Generate a PUF hardware fingerprint, and bind and store the PUF hardware fingerprint with the PUF tag identifier and physical basic information to establish a reliable association between the edge computing unit and the PUF tag; S2. Generate physical anchoring verification results based on the tamper-proof status of the PUF tag; S3. Send a random challenge signal to the PUF tag to verify the response signal, generate a data anchoring verification result, and fuse it with the physical anchoring verification result to obtain the final anchoring verification result. S4. Obtain the physical object's status data, encrypt it using the PUF hardware fingerprint and timestamp, and generate encrypted status data and its integrity hash value. S5. Upload the encrypted state data, integrity hash value, final anchoring verification result, PUF hardware fingerprint, tag identifier, physical basic information, and timestamp to the blockchain, store them after integrity verification, and generate on-chain credentials. S6. Repeat S2 and S3 to update the final anchor verification result. If there is an error, trigger an alert and record the error information to the blockchain. S7. After authorization verification, destroy sensitive data and trigger PUF tag self-destruction to complete anchor release.

[0026] It ensures that the binding relationship between the tag and the physical object is unforgeable and tamper-proof through a dual verification mechanism of physical anchoring and data anchoring; by embedding PUF hardware fingerprints into the entire process of data encryption and integrity verification, and relying on blockchain for secondary verification, it makes the status data tamper-proof at every stage from collection and encryption to storage; at the same time, it balances the timeliness of supervision and resource consumption through a dynamic verification interval mechanism, and uses tokens and verification codes based on PUF fingerprints to achieve two-way security authentication for anchoring and de-anchoring, thus constructing a full life-cycle physical object supervision system with reliable anchoring relationship, complete data chain, and efficient and controllable supervision.

[0027] The following provides a further detailed explanation of each step in the above technical solution; In this embodiment, S1, a PUF hardware fingerprint is generated, and the PUF hardware fingerprint is bound and stored with the PUF tag identifier and physical basic information to establish a reliable association between the edge computing unit and the PUF tag. The PUF hardware fingerprint is generated by a PUF hardware subunit built into the edge computing unit based on a physically unclonable function. The PUF hardware subunit uses a ring oscillator PUF or a static random access memory PUF, and the generated fingerprint is unique and unclonable. The binding storage here refers to storing the PUF hardware fingerprint, PUF tag identifier and physical basic information together in the secure storage area of ​​the edge computing unit, and at the same time writing the PUF hardware fingerprint and physical basic information into the secure storage area of ​​the PUF tag.

[0028] During the power-on initialization process of the edge computing unit, the PUF hardware subunit utilizes inherent process deviations in chip manufacturing, such as differences in ring oscillator frequency or the initial power-on state of SRAM, to generate a unique hardware fingerprint. This fingerprint is fixed and cannot be copied after the chip leaves the factory. Even if an attacker obtains the complete chip circuit diagram, they cannot clone the same fingerprint value, thus providing a hardware-level root of trust for all subsequent secure operations. When binding storage, the edge computing unit and the PUF tag exchange and verify fingerprint information through a secure channel to ensure that the fingerprint data stored by both parties is consistent and has not been tampered with. If a fingerprint mismatch is found during the binding process, the initialization is immediately stopped and an anomaly is reported, preventing unauthorized device access from the source. Once the binding relationship is established in this initialization phase, all subsequent data encryption and anchoring verification are based on it, forming a unique correspondence of one item, one chip, and one tag. Compared with the traditional solution that relies solely on software-level binding, this step incorporates the hardware's unclonable characteristics into the initial association process, preventing attackers from forging legitimate devices through software tampering or copying, thus enhancing the system's ability to resist identity forgery attacks.

[0029] In this embodiment, S2, physical anchoring verification results are generated based on the tamper-proof status of the PUF tag; including: Within the preset time window Internal acquisition of multiple sets of signals , For tamper prevention signal, This is the fit signal; Calculate the anti-tamper fluctuation coefficient Fitting the fluctuation coefficient ;in , Here, N represents the corresponding signal mean, and N is the number of sampling points. like , ,and , The physical anchoring verification result =1, otherwise 0; where , For fluctuation threshold, , This is the mean threshold.

[0030] In actual deployment, anti-tamper signals This can be achieved through a microswitch or conductive circuit inside the label. When the label is peeled off the object's surface, the switch state or circuit continuity changes; adhesion signal. The contact pressure between the label and the object surface can be detected by capacitive or piezoresistive sensors. When the label is loosened or partially peeled off, the adhesion signal fluctuates accordingly. By collecting multiple sets of signals within a preset time window ΔT and calculating the fluctuation coefficient, false alarms caused by environmental vibration or instantaneous interference can be effectively filtered out, while accurately identifying continuous physical tampering behavior. This physical anchoring verification mechanism elevates the static determination of whether disassembly has occurred to a dynamic analysis based on temporal fluctuations, enabling the system to distinguish between instantaneous interference and continuous tampering, thus reducing the false alarm rate. At the same time, by setting fluctuation thresholds and mean thresholds, the sensitivity can be flexibly adjusted according to the material and pasting conditions of different physical surfaces, making it suitable for various scenarios such as container metal walls, bulk cargo storage wooden structures, and finished equipment plastic shells.

[0031] In this embodiment, S3, a random challenge signal is sent to the PUF tag to verify the response signal, a data anchoring verification result is generated, and the result is fused with the physical anchoring verification result to obtain the final anchoring verification result. The response signal verification includes: The edge computing unit generates a random challenge signal (Chal) and sends it to the PUF tag; The PUF tag's built-in PUF circuit generates a response signal Resp for the Chal operation and returns it; The edge computing unit utilizes its PUF hardware subunit to calculate the reference response Resp′ for the same Chal and to calculate the difference. , where j is the bit index of the response signal and L is the bit length; like , If the fault tolerance threshold is used, then the data anchoring verification result is... Otherwise, it is 0.

[0032] Furthermore, the final anchoring verification result is obtained. include: Obtain the historical final anchoring result sequence Calculate confidence level ; Calculate the current anchoring consistency coefficient ;like and ,but ;like but If so, historical backtracking verification is triggered to re-verify historical data; if ,but ; in, For the physical anchoring verification results, The data is used to anchor the verification result, where M is the total number of elements in the sequence. This is the confidence threshold.

[0033] During the response signal verification process, the random challenge signal Chal generated by the edge computing unit has a sufficient bit length to ensure its unpredictability. A new challenge is generated for each verification, ensuring that even if an attacker intercepts a response, they cannot replay it to pass subsequent verifications; Dissimilarity The calculation uses a bit-by-bit comparison method, which can tolerate minor response deviations caused by physical factors such as ambient temperature and voltage fluctuations. This is achieved by setting a fault tolerance threshold. A balance must be struck between security and stability to avoid legitimate labels being misjudged as illegitimate due to the inherent instability of PUF; The introduction of historical anchoring result sequences and confidence levels ensures that the final anchoring result Ac depends not only on the current physical and data anchoring status but also on its long-term historical performance; when But confidence level When the data falls below a threshold, a historical backtracking verification is triggered. The system automatically retrieves the most recent M historical data for integrity verification. If any unmarked anomalies are found in the historical data, the specific time point of the anomaly is traced and a warning is issued, forming an active defense against potential progressive tampering.

[0034] In this embodiment, S4, the physical object's status data is obtained, and encrypted by combining the PUF hardware fingerprint and timestamp to generate encrypted status data and its integrity hash value. Among them, encrypted status data Represented as:

[0035] Integrity hash value Represented as:

[0036] in, For encryption functions, For hash functions, For PUF hardware fingerprinting, The root key is pre-placed in the secure storage area of ​​the edge computing unit. This indicates splicing / joining. For the collected physical state data, For collection timestamps.

[0037] During the encryption process, the state data (State) and... timestamp After mixing and splicing, AES-256 encryption is applied, ensuring that even if different physical objects collect the same state data at the same time, their individual characteristics will be distinguished. The resulting encryption is completely different, eliminating the possibility of inferring the original data by comparing the ciphertext; root key Pre-installed in the chip's secure storage area and unreadable, it only participates in encryption operations, ensuring that even if an attacker gains physical control of the chip; integrity hash value. The calculation results are uploaded along with the encrypted data, enabling blockchain smart contracts to verify whether the data has been tampered with during transmission without decryption; because There is a one-to-one correspondence between the data and the encrypted data. Any modification to Enc will result in inconsistent hash values ​​and be rejected by on-chain verification. This ensures that the authenticity is screened before the data enters on-chain storage, avoiding the problems of off-chain forgery and on-chain invalidity.

[0038] In embodiment S5, the encrypted state data, integrity hash value, final anchoring verification result, PUF hardware fingerprint, tag identifier, physical basic information, and timestamp are uploaded to the blockchain. After integrity verification, they are stored and an on-chain credential is generated. Integrity verification includes: The blockchain smart contract processes the received encrypted state data Enc through... The hash function calculates a hash value, and the result is compared with the received integrity hash value. The data is compared; if they match, the data is written to the blockchain, and an on-chain certificate containing the transaction hash and block height is generated. Otherwise, the blockchain will be rejected and an alert will be triggered.

[0039] In this step, when performing integrity verification, the blockchain smart contract not only compares the consistency of hash values ​​but also verifies whether the format of the uploaded data conforms to the predefined on-chain specifications, including the length of each field, data type, and the reasonableness of the timestamp. If the hash comparison passes but the format is abnormal, the contract also refuses to upload the data to the chain and records the detailed information of the request for subsequent analysis to determine if there are any potential attack attempts. On-chain credentials. Including transaction hashes and block heights, this allows regulatory terminals to quickly locate and verify the storage location of data via blockchain explorers, facilitating post-event auditing and accountability.

[0040] In this embodiment, S6 repeats S2 and S3 to update the final anchor verification result. If an anomaly is detected, an alert is triggered and the anomaly information is recorded to the blockchain. Updating the final anchor verification result includes: Set dynamic verification interval ,in, As the baseline verification interval, For adaptive coefficients, This represents the current confidence level. Execute S2 and S3 at each verification time to obtain the current final anchoring verification result. ; Update historical anchoring result sequence And slide to update the confidence level ρ; If the K consecutive verification results Ac=1 and the confidence level is... Then dynamically increase the verification interval to If Ac=0 occurs even once, the check interval will be immediately restored to the previous value. ;in Minimum verification interval The maximum verification interval, The confidence threshold for the steady state; The dynamic verification interval mechanism introduces confidence levels. As a feedback parameter, the system can adaptively adjust the verification frequency according to the stability of the anchoring state. When the anchoring state is stable for a long time and the confidence level is high, the verification interval gradually increases, effectively reducing the power consumption and communication load of the edge computing unit. Once an anomaly occurs, the verification interval immediately returns to the minimum interval to ensure that subsequent abnormal states can be captured in a timely manner.

[0041] Furthermore, if an anomaly is detected, an alert will be triggered and the anomaly information will be recorded to the blockchain. Specifically, this includes: When the final anchoring verification result Ac=0, it is determined to be an abnormal state; the abnormal information includes the abnormal type, the timestamp of the abnormal occurrence, the current physical anchoring verification result, the current data anchoring verification result, the current confidence level, and the hash value of the sequence of the most recent W historical anchoring results; The abnormal information is signed by the edge computing unit and uploaded to the blockchain, where it is stored by a smart contract and triggers an alarm on the monitoring terminal.

[0042] In this embodiment, S7, after authorization verification, sensitive data is destroyed and PUF tag self-destruction is triggered, completing the anchor release; wherein, destroying sensitive data and triggering PUF tag self-destruction includes: The monitoring terminal initiated an anchor release request, which included a PUF-based hardware fingerprint. Generated temporary session token ,in To request a timestamp, It is a random number; The edge computing unit verifies the validity of the token. After successful verification, it performs a secure erasure operation to delete the locally stored PUF hardware fingerprint, tag identification, physical basic information, and root key. Send a self-destruct command containing a self-destruct verification code to the PUF tag. ,in This is the timestamp for the self-destruct instruction; after receiving the self-destruct verification code, the PUF tag will disconnect its internal storage unit from the external pins once the verification is successful.

[0043] The design of the temporary session token introduces a timestamp. and random numbers This achieves dual replay protection against release requests; when verifying a token, the edge computing unit first calculates the local expected value and compares it with the received token, then checks... Whether it is within the allowed time window, and The erase operation can only be performed after all three criteria—whether the device has been used or not—have been verified. This mechanism ensures that even if an attacker intercepts historical removal requests, they cannot successfully initiate an illegal removal after the device has expired or been reused.

[0044] The verification process for the self-destructing CAPTCHA is similar to that of token verification, but it is completed independently by the PUF tag, which pre-stores the CAPTCHA code. Extract after receiving the self-destruct command The fingerprint is compared with the locally stored fingerprint verification code. If they match and the comparison is within the time window, the tag will self-destruct. The self-destruction operation is achieved by melting the physical connection between the internal storage unit and the external pin, making the tag permanently invalid and unrecoverable. This eliminates the possibility of the tag being recycled and reused, ensuring the irreversibility of the anchor release.

[0045] like Figure 2 As shown, the following describes the specific implementation steps of the PUF tag-based physical anchoring and data monitoring method in this embodiment, taking into account the specific scenario of container transportation: 1) Binding initialization; Before a container leaves the factory or is loaded, regulatory personnel enter basic information such as the container number, specifications, load capacity, logistics company, and destination through a monitoring terminal. After the edge computing unit is powered on, its built-in RO-PUF hardware subunit generates a unique 64-bit hardware fingerprint. Based on this hardware fingerprint, a root key is derived, and the hardware fingerprint, root key, container basic information, and PUF tag identifier are associated and stored in the secure storage area of ​​the edge computing unit and the PUF tag through a secure channel, forming a unique binding relationship of one container, one chip, and one tag, ensuring that the container has an unforgeable identity throughout its entire life cycle. 2) Physical anchoring verification; like Figure 3 As shown, the PUF tag is fixed to the inner wall of the container away from the door by an anti-tear adhesive to avoid being easily touched or damaged during transportation; the edge computing unit is installed at the bottom of the container and is connected to the PUF tag, related sensors and door magnetic switch via wired or wireless means; the container also integrates a GPS positioning module and a door magnetic switch sensor, and the edge computing unit is responsible for periodically collecting anti-tamper signals, adhesion signals, GPS data and door magnetic status; Specifically, the edge computing unit collects anti-tamper signal and fit signal every 5 minutes, calculates the fluctuation coefficient and average value within a 10-second time window, and determines that the physical anchoring is normal when the fluctuation coefficient is lower than the threshold and the average value is higher than the threshold; otherwise, it triggers an early warning. This mechanism effectively distinguishes between instantaneous signal fluctuations caused by bumps during transportation and malicious disassembly behavior. 3) Data anchoring verification; like Figure 4As shown, the PUF tag integrates a PUF circuit, an anti-tamper detection unit, a secure storage area, and a communication module. The tag's built-in PUF circuit generates a response signal and returns it. The edge computing unit randomly generates a 128-bit challenge signal and sends it to the PUF tag. Based on the challenge-response relationship pre-paired with the PUF tag, the edge computing unit uses its own PUF hardware subunit to calculate a reference response and compares the difference bit by bit. If the difference is less than a preset fault tolerance threshold, the data anchoring passes. At the same time, it records the historical anchoring result sequence and calculates the confidence level. When the confidence level is lower than the threshold, it automatically backtracks and verifies the historical data to ensure that even if signal interference or intermittent attacks occur during transportation, anomalies can be detected and recorded in a timely manner.

[0046] 4) Encryption of container status data collection; The sensor module collects the internal temperature, humidity, GPS latitude and longitude coordinates, and door magnetic switch status every 3 minutes. The edge computing unit mixes the collected status data with the hardware fingerprint and the collection timestamp, and uses the root key derived from the hardware fingerprint to perform AES-256 encryption to generate encrypted data. It also calculates the SHA-256 integrity hash value. If the anchoring verification result is abnormal, the collected data is discarded and an early warning is continuously sent, eliminating the possibility of data continuing to be uploaded when the anchoring fails.

[0047] 5) Data on-chain and integrity verification; like Figure 5 As shown, in the entire container transportation supervision system, the edge computing unit uploads encrypted status data, integrity hash value, anchor verification result, hardware fingerprint and timestamp to the consortium blockchain through the gateway. After receiving the data, the smart contract first verifies whether the hash value of the encrypted data is consistent with the uploaded integrity hash value, and at the same time verifies whether the data format conforms to the on-chain specifications. After the verification is passed, the data is written to the blockchain, generating an on-chain certificate containing transaction hash and block height, which is fed back to the supervision terminal for real-time query and verification by multiple nodes such as customs, logistics companies, and regulatory agencies.

[0048] 6) Dynamic anchoring verification and anomaly monitoring; The system dynamically adjusts the verification interval based on the confidence level: when the container is sailing smoothly at sea, its anchoring status remains normal, and the confidence level is higher than the stability threshold, the verification interval gradually increases from the baseline of 5 minutes to 30 minutes, reducing energy consumption and communication load; once the door magnetic sensor detects illegal opening of the container door or an anomaly in the anchoring verification, the verification interval immediately returns to the minimum interval and triggers a real-time warning. The abnormal information is signed by the edge computing unit and uploaded to the blockchain. The monitoring terminal pushes the alarm instantly through the APP. The supervisor can remotely retrieve the abnormal snapshot and issue a locking command to prevent the spread of fraudulent activities.

[0049] 7) Anchor release and tag self-destruction; After the container arrives at its destination and completes customs clearance, the supervisors initiate an anchor release request via a mobile app. The request includes a temporary session token generated based on hardware fingerprints, request timestamps, and random numbers. After the edge computing unit verifies the token's validity, it performs a secure erasure operation to delete all sensitive data stored locally and sends an instruction containing a self-destruct verification code to the PUF tag. After the tag verifies the verification code, it permanently physically disables the tag by melting the connection between the internal storage unit and the external pin, ensuring that the tag cannot be recycled and reused, thus forming a closed loop for the entire lifecycle supervision of the container.

[0050] The PUF tag-based physical anchoring and data monitoring method provided in this embodiment ensures the immutability of the tag-to-physical binding relationship through a dual verification mechanism of physical and data anchoring. It achieves end-to-end tamper-proof status data from collection to storage through the deep integration of PUF hardware fingerprints and blockchain. Furthermore, through dynamic adaptive verification intervals and a two-way security authentication mechanism based on PUF fingerprints, it ensures the timeliness of monitoring while achieving the irreversibility of anchor release. This enables reliable monitoring from source to end, ensuring that the physical identity is unforgeable, the status data is tamper-proof, and abnormal behavior is traceable in real time.

[0051] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0052] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for physical anchoring and data monitoring based on PUF tags, characterized in that, Includes the following steps: S1. Generate a PUF hardware fingerprint, and bind and store the PUF hardware fingerprint with the PUF tag identifier and physical basic information to establish a trusted association between the edge computing unit and the PUF tag; S2. Generate physical anchoring verification results based on the tamper-proof status of the PUF tag; S3. Send a random challenge signal to the PUF tag to verify the response signal, generate a data anchoring verification result, and fuse it with the physical anchoring verification result to obtain the final anchoring verification result; S4. Obtain the physical object's status data, encrypt it using the PUF hardware fingerprint and timestamp, and generate encrypted status data and its integrity hash value. S5. Upload the encrypted state data, integrity hash value, final anchoring verification result, PUF hardware fingerprint, tag identifier, physical basic information, and timestamp to the blockchain, store them after integrity verification, and generate on-chain credentials. S6. Repeat S2 and S3 to update the final anchor verification result. If there is an error, trigger an alert and record the error information to the blockchain. S7. After authorization verification, destroy sensitive data and trigger PUF tag self-destruction to complete anchor release.

2. The method for physical anchoring and data monitoring based on PUF tags according to claim 1, characterized in that, S2 includes: Within the preset time window Internal acquisition of multiple sets of signals , For tamper prevention signal, This is the fit signal; Calculate the anti-tamper fluctuation coefficient Fitting the fluctuation coefficient ;in , Here, N represents the corresponding signal mean, and N is the number of sampling points. like , ,and , The physical anchoring verification result =1, otherwise 0; where , For fluctuation threshold, , This is the mean threshold.

3. The method for physical anchoring and data monitoring based on PUF tags according to claim 1, characterized in that, In step S3, the response signal verification includes: The edge computing unit generates a random challenge signal (Chal) and sends it to the PUF tag; The PUF tag's built-in PUF circuit generates a response signal Resp for the Chal operation and returns it; The edge computing unit utilizes its PUF hardware subunit to calculate the reference response Resp′ for the same Chal and to calculate the difference. , where j is the bit index of the response signal and L is the bit length; like , If the fault tolerance threshold is used, then the data anchoring verification result is... Otherwise, it is 0.

4. The method for physical anchoring and data monitoring based on PUF tags according to claim 1, characterized in that, In step S3, the final anchoring verification result is obtained. include: Obtain the historical final anchoring result sequence Calculate confidence level ; Calculate the current anchoring consistency coefficient ;like and ,but ;like but If so, historical backtracking verification is triggered to re-verify historical data; if ,but ; in, For the physical anchoring verification results, The data is used to anchor the verification result, where M is the total number of elements in the sequence. This is the confidence threshold.

5. The method for physical anchoring and data monitoring based on PUF tags according to claim 1, characterized in that, In step S4, the encrypted state data Represented as: Integrity hash value Represented as: in, For encryption functions, For hash functions, For PUF hardware fingerprinting, The root key is pre-placed in the secure storage area of ​​the edge computing unit. This indicates splicing / joining. For the collected physical state data, For collection timestamps.

6. The method for physical anchoring and data monitoring based on PUF tags according to claim 1, characterized in that, In S5, integrity verification includes: The blockchain smart contract processes the received encrypted state data Enc through... The hash function calculates a hash value, and the result is compared with the received integrity hash value. The data is compared; if they match, the data is written to the blockchain, and an on-chain certificate containing the transaction hash and block height is generated. Otherwise, the blockchain will be rejected and an alert will be triggered.

7. The method for physical anchoring and data monitoring based on PUF tags according to claim 1, characterized in that, In step S6, updating the final anchoring verification result includes: Set dynamic verification interval ,in, As the baseline verification interval, For adaptive coefficients, This represents the current confidence level. Execute S2 and S3 at each verification time to obtain the current final anchoring verification result. ; Update historical anchoring result sequence And slide to update the confidence level ρ; If the K consecutive verification results Ac=1 and the confidence level is... Then dynamically increase the verification interval to If Ac=0 occurs even once, the check interval will be immediately restored to the previous value. ;in Minimum verification interval The maximum verification interval, This is the confidence threshold for the steady state.

8. The method for physical anchoring and data monitoring based on PUF tags according to claim 1, characterized in that, In step S7, destroying sensitive data and triggering PUF tag self-destruction includes: The monitoring terminal initiated an anchor release request, which included a PUF-based hardware fingerprint. Generated temporary session token ,in To request a timestamp, It is a random number; The edge computing unit verifies the validity of the token. After successful verification, it performs a secure erasure operation to delete the locally stored PUF hardware fingerprint, tag identification, physical basic information, and root key. Send a self-destruct command containing a self-destruct verification code to the PUF tag. ,in This is the timestamp for the self-destruct instruction; after receiving the self-destruct verification code, the PUF tag will disconnect its internal storage unit from the external pins once the verification is successful.

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