A transaction data security processing method and system based on a POS machine
By generating unpredictable random perturbation delays and reconstructing communication link timings in POS machines, the problem of POS transaction data being susceptible to tampering by relay devices is solved, achieving efficient physical layer security protection and reducing hardware protection costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENZHEN ZCS TECH
- Filing Date
- 2026-03-31
- Publication Date
- 2026-06-23
Smart Images
Figure CN122268638A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a method and system for secure processing of transaction data based on a POS machine, belonging to the field of transaction verification technology. Background Technology
[0002] Current offline transaction systems use POS machines to collect transaction elements and send them to clearing institutions. Existing technologies typically use terminal security modules to store keys and encapsulate transaction data through encrypted tunnels. This system assumes that as long as the hardware identity is legitimate and the key is not leaked, the generated transaction data will necessarily be authentic. However, this system mainly relies on static keys and algorithm logic, making it difficult to verify the physical authenticity of the transaction data generation process. Relay devices can inject data through the communication gap between the chip card and the card reader driver, or intercept messages and generate delayed replays. Since the encryption algorithm only generates a signature for the result data, the clearing side has difficulty detecting illegal tampering during the edge hardware interaction stage.
[0003] While adding hardware protection or multi-factor tokens improves security, it also increases the deployment and maintenance costs of massive distributed nodes. Furthermore, the passive observation method of simply recording hardware interaction clock cycles, due to the fixed timing standards of the communication protocol, is highly predictable and easily simulated by relay devices with high-frequency sampling capabilities, leading to the invalidation of the uniqueness of physical characteristics. Software-level logical authentication schemes also have vulnerabilities in dealing with underlying link hijacking. For example, Chinese invention patent CN117252599B discloses a dual security authentication method and system for smart POS machines. This method establishes identity verification at the application logic level by constructing a certificate trust chain, blockchain decentralized storage, and application risk assessment algorithms. Under complex operating conditions, such high-level protocol schemes rely on the standardization and predictability of communication clock cycles to verify the legality of anchored data results, rather than the original state of the underlying physical link. When faced with relay agents with microsecond-level clock capture capabilities, they cannot identify and filter the nonlinear clock losses introduced by relay forwarding. Logical signature verification can easily be judged as compliant if the physical link is tampered with.
[0004] Therefore, how to extract the objective physical characteristics of the local data generation process of the POS machine and integrate them into the transaction verification link, thereby breaking the trust mechanism that relies solely on static keys without changing the hardware architecture, has become the technical problem to be solved by this invention. Summary of the Invention
[0005] To address the problems mentioned in the background art, the technical solution of the present invention is as follows: A method for secure processing of transaction data based on a POS machine, comprising the following steps: Step S1: Obtain the business attribute parameters representing the original entropy in the transaction to be processed, and input the business attribute parameters as the source of the original entropy into the streaming hash evolution algorithm to generate feature variables that dynamically evolve with the current transaction content and have unpredictability. Step S2: Modulate the physical layer interaction parameters of the acquiring terminal communication link layer using feature variables, thereby generating a set of random perturbation delays in the instruction scheduling process driven by the underlying communication layer. The magnitude of the random perturbation delay is 10μs to 50μs. Step S3: Inject random perturbation delay into the transmission gap of the communication frame sequence to reconstruct the physical interaction time of the communication link, and send an instruction sequence containing non-standard timing distribution characteristics to the verification medium connected to the acquiring terminal. Step S4: Simultaneously monitor the transient load rate of the acquiring terminal processor, and normalize and compensate the original response delay of the verification medium feedback based on the preset mapping relationship between the transient load rate and the system delay drift, and extract the timing deviation feature vector after removing the influence of random noise in the terminal system. Step S5: Calculate the mapping deviation rate between the timing deviation feature vector and the random perturbation delay, thereby quantitatively characterizing the additional link loss status of the physical interaction link between the verification medium and the acquiring terminal. Step S6: When the mapping deviation rate exceeds the preset threshold, it is determined that the current interaction link has a hardware cache mapping failure introduced by the remote relay agent device, and the current transaction verification logic is stopped in real time.
[0006] Preferably, step S5 further includes the following sub-steps: step S51, extracting the nonlinear hysteresis component relative to the random perturbation delay in the timing deviation feature vector; step S52, analyzing the energy distribution characteristics of the nonlinear hysteresis component under a specific clock tick of the instruction sequence; step S53, comparing the energy distribution characteristics with the preset physical response constant of the hardware gate circuit to establish the mapping deviation rate.
[0007] Preferably, the process of generating random perturbation delay in step S2 includes: inputting the feature variables into the streaming hash evolution algorithm to generate a pseudo-random sequence, and converting the pseudo-random sequence into a discrete delay period corresponding to the frequency of the hardware timer in the underlying driver of the acquiring terminal, so that the physical layer interaction parameters dynamically shift with the transaction entropy.
[0008] Preferably, the process of reconstructing the interaction rhythm in step S3 includes: suspending a specific clock cycle during the transmission of two adjacent instruction sequences by controlling the communication driving logic of the acquiring terminal, so that the transmission gap presents a non-standard distribution bound to the business attribute parameters representing the original entropy in the transaction to be processed, thereby inducing the failure of the pipeline pre-read logic of the relay device.
[0009] Preferably, the process of extracting the timing deviation feature vector in step S4 includes: starting a hardware timer when sending each frame of instruction sequence, and stopping the counting when receiving the response frame signal fed back by the verification medium, obtaining the original response delay corresponding to each frame of instruction, and using it as the original parameter data for subsequent normalization compensation and noise stripping.
[0010] Preferably, the criteria for determining that the current interaction link has a hardware cache mapping failure include: identifying the time delay nonlinear step feature that appears in the timing deviation feature vector due to the processing delay of the remote proxy device for non-standard interaction beats, and using the time delay nonlinear step feature as the basis for judging the physical link loss status.
[0011] Preferably, the method further includes the following steps: sending the locally extracted time-series deviation feature vector to the verification server, and the verification server dynamically updates the preset threshold according to the deviation distribution characteristics of historical transaction samples using a sliding window algorithm, thereby realizing adaptive security modeling of the physical link health status of the acquiring terminal.
[0012] Preferably, the method further includes: obtaining the hardware aging coefficient and environmental temperature drift parameter corresponding to the acquiring terminal, and using the hardware aging coefficient and environmental temperature drift parameter to linearly correct the preset threshold to offset the hardware performance fluctuation of the acquiring terminal throughout its entire life cycle and ensure the objectivity of the mapping deviation rate judgment benchmark. The method also includes the following steps: after determining that there is a hardware cache mapping failure in the interaction link, generating an abnormal security report containing the terminal serial number based on the quantitative result of the physical link loss of the acquiring terminal and the environmental security attributes of the current transaction, and uploading the abnormal security report to the acquiring management system in real time.
[0013] A POS machine-based transaction data security processing system includes: The business parameter acquisition module is used to acquire business attribute parameters that represent the original entropy in the transaction to be processed, and input the business attribute parameters as the source of original entropy into the streaming hash evolution algorithm to generate feature variables that dynamically evolve with the current transaction content and have unpredictability. The interactive parameter modulation module is used to modulate the physical layer interactive parameters of the acquiring terminal communication link layer using characteristic variables, thereby generating a set of random perturbation delays in the instruction scheduling process driven by the underlying communication. The magnitude of the random perturbation delay is 10μs to 50μs. The interactive beat reconstruction module is used to inject random perturbation delay into the transmission gap of the communication frame sequence to reconstruct the physical interactive beat of the communication link, and to send an instruction sequence containing non-standard timing distribution characteristics to the verification medium connected to the acquiring terminal. The load monitoring and compensation module is used to synchronously monitor the transient load rate of the acquiring terminal processor, and to normalize and compensate the original response delay of the verification medium feedback based on the preset mapping relationship between the transient load rate and the system delay drift, and to extract the timing deviation feature vector after removing the influence of random noise in the terminal system. The mapping deviation calculation module is used to calculate the mapping deviation rate between the timing deviation feature vector and the random perturbation delay, thereby quantitatively characterizing the additional link loss status of the physical interaction link between the verification medium and the acquiring terminal. The security verification module is used to determine that the current interaction link has a hardware cache mapping failure due to the remote relay agent device when the mapping deviation rate exceeds a preset threshold, and to stop the current transaction verification logic in real time.
[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. In the secure processing of POS machine transaction data, by extracting the valid bit sequence of the transaction amount from the plaintext data of the business and converting it into a low-level perturbation delay vector, which is then injected into the instruction sending gap of the card reader driver, the physical rhythm of the hardware interaction process is controlled by the current specific transaction elements. This mechanism changes the current situation where physical verification and business verification are isolated from each other in existing technologies. This makes it impossible for replay operations or relay hijacking of specific transaction messages to predict and match non-standard interaction rhythms that are deeply linked to the transaction amount in real time. Consequently, it will inevitably produce unforgeable logical deviations at the physical level. Thus, without changing the existing communication protocol framework, it eliminates the risk of static physical rhythms being accurately replicated by high-performance relay devices.
[0015] 2. In response to the technical characteristics of relay devices relying on pipeline pre-reading and buffer alignment to mask forwarding delays, this solution injects unpredictable perturbation delays to induce frequent buffer misses when relay devices process non-standard clock cycles. This physical response distortion driven by logical interference transforms the difficult-to-detect surface network jitter into obvious nonlinear long-tail hysteresis, enabling the verification server to accurately capture the additional clock cycle consumption introduced by the relay link by calculating the mapping deviation rate between the timing deviation feature vector and the perturbation delay vector, thereby achieving high-accuracy monitoring of physical link integrity.
[0016] 3. By synchronously collecting processor utilization and calling preset compensation functions, the original time difference is specifically corrected, effectively removing random system latency noise generated by concurrent background tasks on the terminal. This mechanism ensures that the timing characteristics only reflect the real physical interaction state between the transaction medium and the terminal. Combined with the server-side sliding window adaptive update logic, it offsets the execution errors caused by component aging and environmental temperature drift, ensuring the solution has a low false kill rate and engineering robustness throughout the terminal's entire life cycle. Attached Figure Description
[0017] Figure 1 This is a flowchart of the POS transaction security processing method based on communication link timing reconstruction according to the present invention; Figure 2 This is a diagram showing the correlation between the accuracy of physical identification of relay attacks and link loss in this invention.
[0018] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation
[0019] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.
[0020] A method for securely processing transaction data based on a POS machine includes the following steps: Step S1: Obtain the business attribute parameters representing the original entropy in the transaction to be processed, and input the business attribute parameters as the source of the original entropy into the streaming hash evolution algorithm to generate feature variables that dynamically evolve with the current transaction content and have unpredictability. Step S2: Modulate the physical layer interaction parameters of the acquiring terminal communication link layer using feature variables, thereby generating a set of random perturbation delays in the instruction scheduling process driven by the underlying communication layer. The magnitude of the random perturbation delay is 10μs to 50μs. Step S3: Inject random perturbation delay into the transmission gap of the communication frame sequence to reconstruct the physical interaction time of the communication link, and send an instruction sequence containing non-standard timing distribution characteristics to the verification medium connected to the acquiring terminal. Step S4: Simultaneously monitor the transient load rate of the acquiring terminal processor, and normalize and compensate the original response delay of the verification medium feedback based on the preset mapping relationship between the transient load rate and the system delay drift, and extract the timing deviation feature vector after removing the influence of random noise in the terminal system. Step S5: Calculate the mapping deviation rate between the timing deviation feature vector and the random perturbation delay, thereby quantitatively characterizing the additional link loss status of the physical interaction link between the verification medium and the acquiring terminal. Step S6: When the mapping deviation rate exceeds the preset threshold, it is determined that the current interaction link has a hardware cache mapping failure introduced by the remote relay agent device, and the current transaction verification logic is stopped in real time.
[0021] Preferably, step S5 further includes the following sub-steps: step S51, extracting the nonlinear hysteresis component relative to the random perturbation delay in the timing deviation feature vector; step S52, analyzing the energy distribution characteristics of the nonlinear hysteresis component under a specific clock tick of the instruction sequence; step S53, comparing the energy distribution characteristics with the preset physical response constant of the hardware gate circuit to establish the mapping deviation rate.
[0022] Preferably, the process of generating random perturbation delay in step S2 includes: inputting the feature variables into the streaming hash evolution algorithm to generate a pseudo-random sequence, and converting the pseudo-random sequence into a discrete delay period corresponding to the frequency of the hardware timer in the underlying driver of the acquiring terminal, so that the physical layer interaction parameters dynamically shift with the transaction entropy.
[0023] Preferably, the process of reconstructing the interaction rhythm in step S3 includes: suspending a specific clock cycle during the transmission of two adjacent instruction sequences by controlling the communication driving logic of the acquiring terminal, so that the transmission gap presents a non-standard distribution bound to the business attribute parameters representing the original entropy in the transaction to be processed, thereby inducing the failure of the pipeline pre-read logic of the relay device.
[0024] Preferably, the process of extracting the timing deviation feature vector in step S4 includes: starting a hardware timer when sending each frame of instruction sequence, and stopping the counting when receiving the response frame signal fed back by the verification medium, obtaining the original response delay corresponding to each frame of instruction, and using it as the original parameter data for subsequent normalization compensation and noise stripping.
[0025] Preferably, the normalization compensation process in step S4 follows the following logic: ,in, The corrected response delay is compensated. The raw response delay collected. This refers to the transient load rate, while This is a preset system latency drift compensation function used to offset the random jitter caused by processor multitasking scheduling.
[0026] Preferably, the criteria for determining that the current interaction link has a hardware cache mapping failure include: identifying the time delay nonlinear step feature that appears in the timing deviation feature vector due to the processing delay of the remote proxy device for non-standard interaction beats, and using the time delay nonlinear step feature as the basis for judging the physical link loss status.
[0027] Preferably, the method further includes the following steps: sending the locally extracted time-series deviation feature vector to the verification server, and the verification server dynamically updates the preset threshold according to the deviation distribution characteristics of historical transaction samples using a sliding window algorithm, thereby realizing adaptive security modeling of the physical link health status of the acquiring terminal.
[0028] Preferably, the method further includes: obtaining the hardware aging coefficient and environmental temperature drift parameter corresponding to the acquiring terminal, and using the hardware aging coefficient and environmental temperature drift parameter to linearly correct the preset threshold to offset the hardware performance fluctuation of the acquiring terminal throughout its entire life cycle and ensure the objectivity of the mapping deviation rate judgment benchmark. The method also includes the following steps: after determining that there is a hardware cache mapping failure in the interaction link, generating an abnormal security report containing the terminal serial number based on the quantitative result of the physical link loss of the acquiring terminal and the environmental security attributes of the current transaction, and uploading the abnormal security report to the acquiring management system in real time.
[0029] A POS machine-based transaction data security processing system includes: The business parameter acquisition module is used to acquire business attribute parameters that represent the original entropy in the transaction to be processed, and input the business attribute parameters as the source of original entropy into the streaming hash evolution algorithm to generate feature variables that dynamically evolve with the current transaction content and have unpredictability. The interactive parameter modulation module is used to modulate the physical layer interactive parameters of the acquiring terminal communication link layer using characteristic variables, thereby generating a set of random perturbation delays in the instruction scheduling process driven by the underlying communication. The magnitude of the random perturbation delay is 10μs to 50μs. The interactive beat reconstruction module is used to inject random perturbation delay into the transmission gap of the communication frame sequence to reconstruct the physical interactive beat of the communication link, and to send an instruction sequence containing non-standard timing distribution characteristics to the verification medium connected to the acquiring terminal. The load monitoring and compensation module is used to synchronously monitor the transient load rate of the acquiring terminal processor, and to normalize and compensate the original response delay of the verification medium feedback based on the preset mapping relationship between the transient load rate and the system delay drift, and to extract the timing deviation feature vector after removing the influence of random noise in the terminal system. The mapping deviation calculation module is used to calculate the mapping deviation rate between the timing deviation feature vector and the random perturbation delay, thereby quantitatively characterizing the additional link loss status of the physical interaction link between the verification medium and the acquiring terminal. The security verification module is used to determine that the current interaction link has a hardware cache mapping failure due to the remote relay agent device when the mapping deviation rate exceeds a preset threshold, and to stop the current transaction verification logic in real time.
[0030] Example 1: In a high-frequency offline acquiring edge node deployed in a weak network environment and facing the threat of network forwarding delays by remote relay equipment using nanosecond-level high-frequency oscillators to rebuild standard communication protocols and fix interaction rhythms in a remote location, the system acquires business attribute parameters representing the original entropy in the transaction to be processed, extracts the valid bit sequence of the transaction amount from the plaintext data of the business, and inputs the business attribute parameters as the source of the original entropy into the streaming hash evolution algorithm to generate feature variables that dynamically evolve with the current transaction content and have unpredictability. The acquiring system uses the feature variables to modulate the physical layer interaction parameters of the acquiring terminal communication link layer, and drives the underlying communication. During the instruction scheduling process, a set of random perturbation delays ranging from 10μs to 50μs are generated. When implementing link parameter modulation, the system does not change the original general asynchronous transceiver hardware architecture. Instead, the microcontroller directly rewrites the values of the auto-reload register and prescaler register of the general timer of the receiving terminal. When the underlying interrupt controller triggers a data transmission idle interrupt, the firmware layer temporarily suspends the next frame transmission request of the direct memory access channel, forcing the communication bus to remain in a high-impedance idle state until the modified timer triggers an overflow interrupt before resuming the transmission request. This achieves precise clock injection at the microsecond level.
[0031] The acquiring terminal's main control module intercepts the standard clock polling cycle of the underlying card reader driver, injecting random perturbation delays into the transmission gaps of communication frame sequences containing card search interrupts and application selection instructions. This reconstructs the physical interaction clock of the communication link, sending a sequence of instructions containing non-standard timing distribution characteristics to the verification medium connected to the acquiring terminal. This action forcibly changes the standard static physical clock, causing hardware cache mapping failures and cache misses when the remote relay agent device faces non-standard instruction clocks that do not match its pre-read buffer pool. This is because if the remote relay agent device uses a simple forwarding gateway with pure level physical pass-through, the inherent millisecond-level round-trip delay of long-distance transmission over remote networks will directly expose and trigger the underlying physical clock of the local acquiring terminal. Clock timeout mechanism; To mask the time loss caused by the geographical distance, the relay agent device can only construct a fake response state machine locally in terms of physical logic. It uses pipeline pre-reading and buffer alignment mechanisms to send the expected standard clock handshake signal to the acquiring terminal in advance. When a non-standard timing perturbation delay is injected, this inherent and timing-dependent local state machine deception mechanism is broken. During the transmission of two adjacent instruction sequences, the acquiring terminal synchronously monitors the processor's transient load rate. Based on the preset mapping relationship between the transient load rate and the system delay drift, it normalizes and compensates for the original response delay of the verification medium feedback. It extracts the timing deviation feature vector after removing the random noise generated by the terminal system's multi-task scheduling. The compensation formula is... ,in, The corrected response delay is compensated. The raw response delay collected. Transient load rate, The system uses a preset system delay drift compensation function. It extracts the nonlinear hysteresis component relative to random perturbation delay from the timing deviation feature vector, analyzes the energy distribution characteristics of the nonlinear hysteresis component under a specific clock tick of the instruction sequence, compares the energy distribution characteristics with the preset physical response constant of the hardware gate circuit, and calculates the mapping deviation rate between the timing deviation feature vector and the random perturbation delay. The energy distribution of the discrete-time signal in the finite-length time domain discrete sequence is the cumulative sum of the squares of the amplitudes of each sampling point. Although the sampling period of the transient load rate is on the order of milliseconds, while the jitter of a single system delay is on the order of microseconds, the context switching overhead brought by the processor's concurrent tasks will cause the instruction pipeline to be drained and reloaded within the overall sampling window. This causes the response delay of the underlying communication driver on the microsecond scale to follow a Poisson distribution with mean shift. The preset system delay drift compensation function is actually based on the statistical expectation of a large number of discrete surface delay samples.
[0032] By subtracting the mean shift caused by the overall load, the nondeterministic high-frequency transient random jitter is reduced to zero-mean Gaussian white noise. This allows for statistically eliminating system noise without requiring microsecond-level real-time load monitoring. The system establishes N instruction frame periodic sliding sampling windows in its internal cache, extracts N nonlinear hysteresis components within each window to form a discrete-time series, reads the discrete-time series, calculates the sum of squares of the delay amplitude at each sampling point, and outputs the quantized value corresponding to the energy distribution characteristics—the time-domain hysteresis energy. Retrieve the physical response constants of the embedded hardware gate circuits within the underlying security physical zone of the acquiring terminal. According to the formula Establish the mapping deviation rate, where γ is the mapping deviation rate, and its value boundary is greater than or equal to zero; To calculate the time-domain hysteresis energy, To pre-calibrate the physical response constant of the hardware gate circuit, characterize the lower limit of the inherent reference delay energy fluctuation generated by the physical interaction of the underlying medium under the standard direct connection state without relay hijacking, and quantify the additional link loss state of the physical interaction link between the verification medium and the acquiring terminal; the verification server receives a mixed transaction verification message containing plaintext data and dynamic transaction tokens, and the server synchronously derives the perturbation delay vector. The system judges whether the extracted mapping deviation rate exceeds the preset threshold established by the basic timing reference interval corresponding to the terminal model. When the mapping deviation rate exceeds the preset threshold, it is determined that the current interaction link has a nonlinear step delay characteristic caused by the remote relay agent device processing non-standard interaction beat delay. The current transaction verification logic is stopped in real time. The pipeline buffer miss time loss of the remote relay device constitutes the basis for physical verification. The logical plaintext information of the business dimension is converted into the underlying communication timing offset of the physical dimension to block the side channel data hijacking.
[0033] Example 2: In the hardware-in-the-loop engineering test scenario evaluating the anti-relay physical hijacking capability of offline distributed acquiring nodes, the test benchmark platform uses an acquiring terminal equipped with a secure main control chip and a remote proxy attack simulator based on a field-programmable gate array (FPGA) with nanosecond-level clock capture and pipeline pre-reading capabilities. To reproduce the complex electromagnetic environment of supermarkets and the concurrent processing conditions of terminals, broadband white Gaussian noise with a signal-to-noise ratio of 20dB and power frequency interference harmonics with a frequency of 50Hz are injected into the signal interaction link through an arbitrary waveform generator. The acquiring terminal concurrently runs encrypted communication tasks in the background to induce system interference with an amplitude of 0μs to 5μs. The system schedules random jitter; regarding the setting of the core parameter range for random perturbation delay, the system needs to achieve a technical trade-off between the cache prefetch depth failure boundary of the remote proxy device and the standard response timeout tolerance of the legitimate physical verification medium; when the set lower limit of perturbation delay is lower than the time span of the overlapping execution window of the instruction pipeline of the attack simulator, cache mapping failure cannot be triggered; when the upper limit of perturbation delay plus the inherent transmission time of the network exceeds the watchdog reset threshold of the verification medium, legitimate transaction interruption is triggered. Based on the physical response constant of typical gate circuits, the system calibrates the preferred working range of random perturbation delay as 10μs to 50μs.
[0034] The experiment established a control group using a fixed-clock-beat standard communication protocol, an out-of-range control group injected with different levels of perturbation, and the experimental group of this invention. Under the baseline input condition of setting the inherent round-trip time of the underlying physical link to 5ms and superimposed with environmental noise, the original response delay measured by the control group showed a discrete distribution with a mean of 5.02ms and a standard deviation of 0.15ms. The attack simulator absorbed this timing fluctuation and maintained a stable fake interaction beat by pre-reading mechanism. A first out-of-range control group was established by injecting a lower-limit out-of-range perturbation delay of 5μs into the communication frame gap. The measured response delay distribution highly overlapped with that of the control group. This indicates that the remote pre-read buffer absorbs disturbances of this magnitude. A second over-range control group was established by injecting an upper limit perturbation delay of 80 μs into the communication frame gap. The feedback signal of the legitimate verification medium showed nonlinear degradation, and the measured packet loss rate exhibited an exponential jump, reaching 15.4%. This confirmed that excessive timing deviations disrupted the stability of the underlying state machine of the communication protocol and caused physical connectivity failure of the receiving link. A partially missing control group using only static random seeds for generating perturbation delays, after initial fluctuations, saw the attack simulator's adaptive algorithm reconverge the internal mapping deviation rate to below the safety threshold within 80 polling cycles.
[0035] The system startup employed a test group with a random perturbation delay of 10μs to 50μs, modulated by a feature variable generated from the effective bit sequence of the dynamic transaction amount. The acquiring terminal continuously collected transient load rates synchronously in the background. At a specific clock tick point, it captured raw state data with a transient load rate of 85% and an original response delay of 5.12ms. The delay drift compensation function was called to process the transient load rate, outputting a delay drift compensation value of 0.08ms. Based on the normalized compensation logic, the corrected response delay was calculated to be 5.04ms. This step eliminated random noise interference caused by multi-task concurrency in the terminal system, ensuring that the extracted timing deviation feature vector reflected the pure timing variation of the physical link. To verify the adaptability of the solution to different attack intensities, the system established a proxy prediction depth gradient comparison system. When the instruction prediction depth of the remote proxy simulator was set to a 4-stage pipeline, the test group calculated... The mapping deviation rate suddenly increased to 2.5 times that of the normal state. When the instruction prediction depth was increased to 8-stage pipeline, in the face of non-standard timing interactions that are strongly bound to transaction entropy, the remote agent simulator generated a serious cache miss failure. In order to resynchronize the data stream, it was forced to consume additional instruction cycles, and the mapping deviation rate reached 4.2 times that of the normal state. When the instruction prediction depth was pushed to 16-stage pipeline, the pipeline flushing cost caused by branch prediction failure was nonlinearly amplified, and the mapping deviation rate jumped to 6.8 times that of the normal state. The aforementioned gradient data confirms that the technical architecture of mapping the high-entropy parameters of the business plaintext dimension across domains to the physical interaction layer modulation perturbation delay produces a synergistic effect that cannot be achieved by a single physical layer defense. The nanosecond-level forwarding operation introduced by the remote relay agent device is transformed into a measurable nonlinear hysteresis long tail. Based on this, the system blocks side-channel data hijacking and establishes physical quantification criteria.
[0036] Example 3: In an engineering deployment scenario involving the solidification of the underlying algorithm and dynamic calibration of security benchmark parameters for acquiring terminals, the system faces the technical challenge of mapping business logic to physical timing to filter out nonlinear operational drift of the hardware system at the industrial application layer. The main control module of the acquiring terminal extracts the valid bit sequence of the transaction amount of the transaction to be processed, converts the valid bit sequence of the transaction amount into a hexadecimal byte stream, and extracts the lower 8 bits of the hexadecimal byte stream as the initial vector. The system calculates the bitwise XOR operation result of the initial vector and the true random number seed of the hardware physical non-cloning function, and inputs the bitwise XOR operation result into a streaming hash evolution algorithm containing a shift register and a nonlinear permutation network. The least significant bit segment of the output hash value after 44 clock cycles of confusion diffusion is extracted, and the least significant bit segment is mapped to a preset physical clock step grid using linear scaling logic. The output value ranges from 10μs to 50μs for specific feature variables. This step establishes a conversion path from business attribute parameters to perturbation delay.
[0037] The system starts the benchmark test program in a network-disconnected shielded state to determine the system latency drift compensation function independent of the network environment. The main control module generates pseudo-random card seek interrupts at nine discrete gradients where the processor transient load rate is between 10% and 90% through internal hardware timers. It records the system's internal instruction scheduling response time corresponding to each load gradient. The system extracts the data pairs of transient load rate and corresponding system internal instruction scheduling response time, and uses the least squares method to fit the data pairs to construct a characteristic polynomial, establishing the specific compensation relationship. ,in, This is a preset system delay drift compensation function. Transient load rate, as well as The fitting coefficients are used to characterize the nonlinear hysteresis characteristics of the hardware architecture. As the inherent static transmission constant of the underlying bus, the system call compensation relationship normalization process includes the original response delay containing multi-task concurrency noise. The verification server extracts the mapping deviation rate from historical transaction samples to form a discrete time series. The system establishes a sliding window with a length of 512 time periods based on the hardware configuration level of the acquiring terminal. The verification server calculates the statistical arithmetic mean and standard deviation of all mapping deviation rate elements within the sliding window and updates the preset threshold to the arithmetic mean plus 3 times the standard deviation. The system obtains the hardware aging coefficient and the environmental temperature drift parameter of the deployment area from the acquiring terminal firmware operation record, calculates the product of the hardware aging coefficient and the environmental temperature drift parameter as a correction factor, and uses the correction factor to adjust the arithmetic mean. Through this parameter evolution mechanism, the hardware performance fluctuations throughout the entire life cycle of the acquiring terminal are offset, so that the side channel data hijacking judgment benchmark and the physical attenuation state of the terminal are kept synchronized, and the adaptive security modeling of the physical link health status is completed.
[0038] Example 4: In the on-site pre-deployment calibration scenario where the acquiring terminal first accesses the commercial network and initializes hardware timing parameters, the acquiring system starts a physical connectivity benchmark probe in an isolated state with external service routing interfaces blocked. The main control module continuously sends a non-interference detection sequence consisting of 500 standard application selection instructions to the communication link. The acquiring terminal synchronously starts a hardware timer to record the time difference from the physical layer sending of each non-interference detection instruction to the local confirmation feedback received from the verification medium. The system calculates the arithmetic mean of the 500 time differences, filters out single-signal crosstalk noise, and writes the arithmetic mean into non-volatile memory, using it as the inherent static transmission constant of the underlying bus at the specific deployment location. The system delay drift compensation function reads this static transmission constant. This establishes an absolute latency benchmark under zero load conditions.
[0039] The system switches to a test channel carrying controlled perturbations. The main control module calls a pseudo-random number generator to generate a test byte stream, which replaces the valid bit sequence of the transaction amount. The system inputs the test byte stream into the streaming hash evolution algorithm to modulate a baseline perturbation delay. The acquiring terminal continuously sends probe messages containing the baseline perturbation delay to the verification server under the field network channel. The verification server continuously receives the initial mapping deviation rate and fills the initial mapping deviation rate into a sliding window containing 512 sampling nodes. When the sliding window reaches data saturation, the system extracts the arithmetic mean and standard deviation of the initial mapping deviation rate sequence within the sliding window. The system calculates and generates an initial preset threshold based on the arithmetic mean plus three times the standard deviation. Through the above baseline calibration process, a quantitative judgment boundary suitable for the current physical deployment environment is established.
[0040] Example 5: In scenarios where the acquiring terminal faces fluctuating ambient temperatures and requires parameter calibration and boundary protection for quantifying underlying hardware operating parameters, the acquiring terminal's main control module activates the kernel performance monitoring register. During a 10ms sampling observation period, it acquires the number of active clock cycles allocated to non-idle threads and the corresponding global clock cycles. The system calculates the quotient of the active clock cycles and the global clock cycles, determining this quotient as the transient load rate. Based on the transient load rate, it calls a preset system delay drift compensation function to output the delay drift compensation value. The thermistor component integrated on the acquiring terminal's motherboard continuously acquires the measured motherboard temperature at a sampling frequency of 1Hz. The system compares the measured motherboard temperature with a preset safe operating temperature range, set to -10℃ to 60℃. When the measured motherboard temperature deviates from the safe operating temperature range, the temperature drift effect of the crystal oscillator triggers the inherent static transmission constant of the underlying bus. This generates nonlinear distortion, causing the system to truncate the input channel of the current streaming hash evolution algorithm.
[0041] In isolated mode, the physical connectivity reference probe is awakened. The main control module injects a non-perturbation detection sequence consisting of 500 standard application selection instructions into the communication link, collects 500 time differences under the current temperature boundary, and calculates the arithmetic mean. The system uses the calculated arithmetic mean to overwrite the original static transfer constant in the non-volatile memory. The main control module measures the system's internal instruction scheduling response time under transient load rate gradients ranging from 10% to 90%, and uses the least squares method to fit the fitting coefficients characterizing the nonlinear hysteresis of the hardware architecture in the system's time delay drift compensation function. as well as This parameter reconstruction procedure enables the acquiring terminal to maintain the calculation of the mapping deviation rate under the boundary conditions of alternating physical environment, and to block the quantization verification state of side channel data hijacking.
[0042] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.
[0043] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims
1. A method for securely processing transaction data based on a POS machine, characterized in that, Includes the following steps: Step S1: Obtain the business attribute parameters representing the original entropy in the transaction to be processed, and input the business attribute parameters as the source of the original entropy into the streaming hash evolution algorithm to generate feature variables that dynamically evolve with the current transaction content and have unpredictability. Step S2: Modulate the physical layer interaction parameters of the acquiring terminal communication link layer using feature variables, thereby generating a set of random perturbation delays in the instruction scheduling process driven by the underlying communication layer. The magnitude of the random perturbation delay is 10μs to 50μs. Step S3: Inject random perturbation delay into the transmission gap of the communication frame sequence to reconstruct the physical interaction time of the communication link, and send an instruction sequence containing non-standard timing distribution characteristics to the verification medium connected to the acquiring terminal. Step S4: Simultaneously monitor the transient load rate of the acquiring terminal processor, and normalize and compensate the original response delay of the verification medium feedback based on the preset mapping relationship between the transient load rate and the system delay drift, and extract the timing deviation feature vector after removing the influence of random noise in the terminal system. Step S5: Calculate the mapping deviation rate between the timing deviation feature vector and the random perturbation delay, thereby quantitatively characterizing the additional link loss status of the physical interaction link between the verification medium and the acquiring terminal. Step S6: When the mapping deviation rate exceeds the preset threshold, it is determined that the current interaction link has a hardware cache mapping failure introduced by the remote relay agent device, and the current transaction verification logic is stopped in real time.
2. The method for securely processing transaction data based on a POS machine according to claim 1, characterized in that, Step S5 further includes the following sub-steps: Step S51, extract the nonlinear hysteresis component relative to the random perturbation delay in the timing deviation feature vector; Step S52, analyze the energy distribution characteristics of the nonlinear hysteresis component under a specific clock tick of the instruction sequence; Step S53, compare the energy distribution characteristics with the preset physical response constant of the hardware gate circuit to establish the mapping deviation rate.
3. The method for secure processing of transaction data based on a POS machine according to claim 1, characterized in that, The process of generating random perturbation delay in step S2 includes: inputting feature variables into a streaming hash evolution algorithm to generate a pseudo-random sequence, and converting the pseudo-random sequence into a discrete delay period corresponding to the frequency of the hardware timer in the underlying driver of the acquiring terminal, so that the physical layer interaction parameters dynamically shift with the transaction entropy.
4. The method for securely processing transaction data based on a POS machine according to claim 1, characterized in that, The process of reconstructing the interaction rhythm in step S3 includes: suspending a specific clock cycle during the transmission of two adjacent instruction sequences by controlling the communication drive logic of the acquiring terminal, so that the transmission gap presents a non-standard distribution bound to the business attribute parameters representing the original entropy in the pending transaction, thereby inducing the failure of the pipeline pre-read logic of the relay device.
5. The method for securely processing transaction data based on a POS machine according to claim 1, characterized in that, Step S4 involves extracting the timing deviation feature vector, which includes: starting a hardware timer when sending each frame of instruction sequence and stopping the counting when receiving the response frame signal from the verification medium, obtaining the original response delay corresponding to each frame of instruction, and using it as the original parameter data for subsequent normalization compensation and noise stripping.
6. The method for secure processing of transaction data based on a POS machine according to claim 1, characterized in that, The criteria for determining that there is a hardware cache mapping failure in the current interaction link include: identifying the nonlinear step characteristics of delay caused by the processing delay of non-standard interaction beats by the remote agent device in the timing deviation feature vector, and using the nonlinear step characteristics of delay as the basis for judging the physical link loss status.
7. The method for securely processing transaction data based on a POS machine according to claim 1, characterized in that, The method also includes the following steps: sending the locally extracted time-series deviation feature vector to the verification server, which uses a sliding window algorithm to dynamically update the preset threshold based on the deviation distribution characteristics of historical transaction samples, thereby achieving adaptive security modeling of the physical link health status of the acquiring terminal.
8. The method for securely processing transaction data based on a POS machine according to claim 7, characterized in that, The method also includes: obtaining the hardware aging coefficient and environmental temperature drift parameters corresponding to the acquiring terminal, and using the hardware aging coefficient and environmental temperature drift parameters to linearly correct the preset threshold in order to offset the hardware performance fluctuations of the acquiring terminal throughout its entire life cycle and ensure the objectivity of the mapping deviation rate judgment benchmark. The method also includes the following steps: after determining that there is a hardware cache mapping failure in the interaction link, generating an abnormal security report containing the terminal serial number based on the quantitative results of the physical link loss of the acquiring terminal and the environmental security attributes of the current transaction, and uploading the abnormal security report to the acquiring management system in real time.
9. A POS machine-based transaction data security processing system, used to implement the POS machine-based transaction data security processing method as described in claim 1, characterized in that, include: The business parameter acquisition module is used to acquire business attribute parameters that represent the original entropy in the transaction to be processed, and input the business attribute parameters as the source of original entropy into the streaming hash evolution algorithm to generate feature variables that dynamically evolve with the current transaction content and have unpredictability. The interactive parameter modulation module is used to modulate the physical layer interactive parameters of the acquiring terminal communication link layer using characteristic variables, thereby generating a set of random perturbation delays in the instruction scheduling process driven by the underlying communication. The magnitude of the random perturbation delay is 10μs to 50μs. The interactive beat reconstruction module is used to inject random perturbation delay into the transmission gap of the communication frame sequence to reconstruct the physical interactive beat of the communication link, and to send an instruction sequence containing non-standard timing distribution characteristics to the verification medium connected to the acquiring terminal. The load monitoring and compensation module is used to synchronously monitor the transient load rate of the acquiring terminal processor, and to normalize and compensate the original response delay of the verification medium feedback based on the preset mapping relationship between the transient load rate and the system delay drift, and to extract the timing deviation feature vector after removing the influence of random noise in the terminal system. The mapping deviation calculation module is used to calculate the mapping deviation rate between the timing deviation feature vector and the random perturbation delay, thereby quantitatively characterizing the additional link loss status of the physical interaction link between the verification medium and the acquiring terminal. The security verification module is used to determine that the current interaction link has a hardware cache mapping failure due to the remote relay agent device when the mapping deviation rate exceeds a preset threshold, and to stop the current transaction verification logic in real time.