205 results about "Steganography" patented technology

The invention discloses a high-load data steganography method, system and device and a medium, and the method comprises the steps: obtaining secret data of a power system, and converting the secret data into a novenary sequence; a quantum key distribution system is utilized to generate a shared key, the novenary sequence is encrypted through an encryption key, encrypted information is obtained, and the shared key comprises the encryption key and a mapping key; determining a corresponding first unit matrix from a preset mapping library based on the mapping key, and performing non-overlapping tiling on the first unit matrix in a two-dimensional plane to obtain a second-order reference matrix; and scanning a preset carrier image into a non-overlapping first pixel pair sequence according to a Hilbert curve, and embedding the encrypted information into the first pixel pair sequence by using the second-order reference matrix to obtain a steganographic image, so that the data transmission security can be improved.

A system and method are configured to commission and decommission an endpoint device using steganography. The system includes a server operatively connected to the endpoint device through a network. The server includes a steganographic module configured to receive configuration instructions, to generate a secret message corresponding to the configuration instructions, and to steganographically embed the secret message in a carrier file, including a media file selected from the group consisting of a text file, an image file, an audio file, and a video file. The carrier file is transmitted to the endpoint device which extracts the secret message from the carrier file, and which executes the configuration instructions in the secret message to reconfigure the endpoint device to commission or decommission the endpoint device or a component thereof. The method implements the system.

Techniques for utilizing invisible and / or inaudible watermarking techniques in media streams (e.g., video and / or audio streams) as a form of in-band steganography to authenticate the source capture camera and / or microphone to prevent deepfakes in network-based communication systems. User device(s) may establish cloud-based connections to a network-based communication system hosting media stream(s). An encoder of a watermarking component of a user device may receive video / audio data directly from a camera / microphone thereof and encode the video / audio data with watermark(s) representing a signed signature. A decoder of a watermarking component of a recipient user device and / or another device associated with the communication system may extract the watermarks and authenticate the signed signature using public certificate(s) associated with the sending user device to validate authenticity of the capture source(s) of the sending user device and that the video / audio data has not been modified since the time of capture.

A machine learning model is scanned to detect actual or potential threats. The threats can be detected before execution of the machine learning model or during an isolated execution environment. The threat detection may include performing a machine learning file format check, vulnerability check, tamper check, and stenography check. The machine learning model may also be monitored in an isolated environment during an execution or runtime session. After performing a scan, the system can generate a signature based on actual, potential, or absence of detected threats.

The invention provides an image privacy protection-oriented reversible adversarial sample generation system and method, and relates to the technical field of artificial intelligence and image privacy protection. The system comprises an input module, a semantic guidance mask generation module, a potential confrontation generation module and a reversible steganography embedding module. The input module acquires an original image, generates a binary mask in the semantic guidance mask generation module, and generates adversarial text description by adopting a visual language model; a final image potential representation is generated in a potential adversarial generation module through forward diffusion and reverse sampling of a diffusion model, and adversarial disturbance is introduced by adopting a gradient optimization algorithm to generate an adversarial sample image; and finally, discrete wavelet transform is adopted in the reversible steganography embedding module to separate out a high-frequency sub-band, and a reversible neural network is combined to obtain a secret-containing hidden image. According to the method, the three requirements of visual authenticity, visual anonymity and machine identifiability can be met at the same time, and an innovative solution is provided for privacy protection in an advanced face recognition scene.

The invention discloses a network traffic restoring and monitoring method, which relates to the technical field of network monitoring, and comprises the following steps of: capturing an original encrypted traffic data packet, and dynamically embedding steganography marks in non-key fields reserved at message headers of a network layer and a transmission layer to generate an encrypted traffic data packet carrying steganography metadata; injecting the behavior element triple set into the constructed cross-protocol threat knowledge graph to perform adjacency relation matching, and outputting a high-risk threat matching result when the overlap ratio of an unknown protocol behavior path and a graph threat link exceeds a preset safety threshold; and triggering real-time blocking according to a high-risk threat matching result, generating an auditing alarm record, updating a cross-protocol threat knowledge graph, and completing encrypted flow reduction and intelligent monitoring closed loop. According to the method, the steganography marks are dynamically embedded in the message heads of the network layer and the transmission layer, so that the encrypted traffic carries steganography metadata in the transmission process, and the hidden marking of the encrypted traffic is realized.

The invention discloses a robust two-dimensional code steganography method based on an attention flow model, and particularly relates to the technical field of image super-resolution. According to the method, a carrier image and a two-dimensional code image are used as input, and a steganographic image which is very small in visual difference with the carrier image is obtained. The hidden two-dimensional code can be obtained by decoding the steganographic image, and the recovered two-dimensional code image can be identified and original information can be restored. According to the method, steganography and decoding processes are simultaneously realized through a neural network based on an attention flow model. According to the method, the steganography can be allowed to bear image interference such as noise, image quality compression, printing and photographing on the premise of ensuring that the recovered two-dimensional code can be identified. The steganography model based on the attention mechanism is realized, and explicit visual loss caused by steganography can be effectively reduced. The method can be applied to actual application scenes such as copyright protection and encryption communication, and has relatively high calculation efficiency and anti-interference performance.

The invention relates to the technical field of information security, in particular to a sensitive information detection technology and system based on multi-mode and steganography detection.The sensitive information detection technology and system based on multi-mode and steganography detection.The method comprises the steps that firstly, through a format tampering prevention module, file header information and binary data analysis are utilized, the real type of a file is verified, and format camouflage attacks are prevented; the sensitive data detection module adopts DistilBERT and LSTM structures to preprocess a text, extract text embedding, mine text features through a bidirectional LSTM and Attention mechanism, and finally accurately judge whether the text contains sensitive information or not; the joint content and file steganography detection module fuses a convolutional neural network and multi-modal learning, adopts corresponding models for different data types to carry out steganography information detection, integrates results through a multi-modal neural network, and applies multi-modal feedback and a cross-modal reasoning mechanism to improve the detection accuracy; according to the method, the accuracy, comprehensiveness and system adaptability of sensitive information detection are effectively enhanced.

The invention discloses a three-dimensional steganography method based on a multi-mode large model and micro three-dimensional rendering, which is used for hiding information such as characters, audios or images to be hidden into a three-dimensional model through a micro three-dimensional rendering pipeline by using the multi-mode large model, and is suitable for various scenes such as secret communication and three-dimensional model watermarking. The method comprises the following steps of: 1) training an information decoder by using a multi-modal large model, and noticing that the information decoder can only act on single modal data; 2) generating any three-dimensional model by using the existing three-dimensional reconstruction technology; and (3) performing fine adjustment of specific information on the three-dimensional model generated in the step (2) by using the information decoder obtained in the step (1), and hiding the information into the three-dimensional model through a differentiable three-dimensional rendering pipeline.

The invention discloses a text-image multi-mode generative steganography method and system, an encryption model and a decryption model are constructed based on a conditional diffusion model and are respectively deployed to an information sender and an information receiver, the information sender divides to-be-hidden secret information into two parts, one part generates a secret-containing text by adopting a text steganography method, and the other part generates a secret-containing text by adopting a text steganography method; the other part generates a secret-containing hidden variable, the secret-containing text is used as a condition of the conditional diffusion model, the secret-containing text and the secret-containing hidden variable are input into the encryption model together to generate a secret-containing image, and the information sender sends the secret-containing text and the secret-containing image to the information receiver together. And an information receiver respectively extracts two parts of secret information from the received encrypted text and the received encrypted image, and original secret information is recovered after merging. According to the method, after the to-be-hidden secret information is split, the secret-containing text and the secret-containing hidden variable are generated respectively and input into the conditional diffusion model to generate the secret-containing image, and the secret information hiding capacity is improved.

The invention relates to the technical field of data encryption, in particular to a VPN dynamic hierarchical encryption system and method for cross-border data transmission, and the method comprises the steps: dividing a data flow into different hierarchies based on information entropy; the high-entropy core data is embedded in a steganography mode through a chaos algorithm by means of the low-entropy redundant space; carrying out global basic encryption on the mixed carrier, and respectively executing chaotic scrambling and differential iterative diffusion for the steganography region and the middle entropy region; dynamically injecting a filling block according to entropy feedback to realize flow homogenization shaping; and splitting the deconstructed index through threshold secret sharing, and performing hidden distribution. According to the method provided by the invention, the concealment and security of cross-border data transmission can be effectively improved.

The invention relates to the technical field of information encryption and decryption, in particular to an image information encryption and decryption method and software system based on a digital image steganography technology. According to the technical scheme, the method comprises the following steps that a carrier image format and a to-be-processed information type are determined, the carrier image format comprises a PNG image and a JPEG image, and the to-be-processed information type comprises text information, picture information and audio information; encrypting the plaintext information to generate ciphertext information; and selecting a corresponding steganography path according to the format of the carrier image, embedding the ciphertext information into the carrier image, generating an encrypted image, and generating a key file recording the embedded related information. According to the method, various image formats and information types are supported, the compatibility, safety, robustness and practicability of information encryption and decryption are improved through key encryption, face binding verification and a compensation mechanism for JPEG, and the method is suitable for scenes such as information protection and private transmission.

The invention discloses a coal-fired power generation data encryption method and device, equipment and a medium, and relates to the technical field of encryption, and the method comprises the steps: carrying out the preprocessing of target coal-fired power generation data; converting the preprocessed target coal-fired power generation data into a two-dimensional matrix; performing multi-round iterative encryption on the two-dimensional matrix in a manner of generating a random matrix for encryption by using chaotic mapping to obtain an encrypted data matrix; carrying out steganography on the encrypted data matrix to obtain steganographic data; the steganographic data is used for storage or transmission. According to the invention, the data security can be improved.

The invention discloses a language steganography load enhancement method and device based on a large language model. The method comprises the steps that firstly, a shared semantic restorer obtained through fine adjustment of the large language model LLM is constructed; the sender performs low-redundancy compression and key information protection on the secret message to be processed through the shared semantic restorer; converting the obtained compressed message into a pseudo-random bit stream through index compression coding based on probability; embedding the pseudo-random bit stream into a carrier text generated by a large language model LLM through an underlying steganography algorithm to obtain a steganography text, and transmitting the steganography text through a common channel; and after receiving the steganography text, the receiver losslessly recovers the original secret message through reverse operation based on the steganography algorithm shared with the sender, the coding mode and the shared semantic restorer. According to the method and device, the processing flow of the secret message is optimized through the large language model, and efficient compression and lossless recovery of the secret message are achieved.

Techniques for utilizing invisible and / or inaudible watermarking techniques in media streams (e.g., video and / or audio streams) as a form of in-band steganography to authenticate the source capture camera and / or microphone to prevent deepfakes in network-based communication systems. User device(s) may establish cloud-based connections to a network- based communication system hosting media stream(s). An encoder of a watermarking component of a user device may receive video / audio data directly from a camera / microphone thereof and encode the video / audio data with watermark(s) representing a signed signature. A decoder of a watermarking component of a recipient user device and / or another device associated with the communication system may extract the watermarks and authenticate the signed signature using public certificate(s) associated with the sending user device to validate authenticity of the capture source(s) of the sending user device and that the video / audio data has not been modified since the time of capture.

The application discloses an AAC security steganography algorithm and system based on a masking effect. The human ear hearing masking effect can cause some audio signals with low intensity to be masked by signals with high intensity, and there is space for hiding secret information. Therefore, the application analyzes a quantization process of MDCT coefficients in AAC coding, records the masked audio signals as modifiable positions, and combines an STC adaptive steganography framework to realize embedding of secret information. Experimental results show that the algorithm can achieve a maximum embedding capacity of 13.61 kbps, can guarantee auditory concealment of speech, and has good security.

The present invention discloses an H.265 / HEVC video adaptive steganography method based on improved RDO. The embedding of the secret information includes three parts: extracting the carrier, calculating the distortion cost value, and STC adaptive embedding. According to the characteristics of the block size and the PU partitioning mode, the appropriate PU partitioning mode is classified and extracted from all coding units with a size less than 64×64 in P frames as the carrier, and the distortion cost value of the carrier during simulated embedding is calculated. According to the distortion cost value, the STC algorithm is used for the carrier to achieve adaptive secret information embedding, realizing a data hiding method with the minimum total distortion cost; since the method of the present invention comprehensively considers factors such as video bitrate increase, video picture quality, and inter-frame distortion transfer when calculating the distortion cost value, the method of the present invention can effectively reduce the bitrate increase caused by steganography. The stego video after steganography has better picture quality, lower bitrate, and higher security.

The invention belongs to the technical field of office automation, and discloses a mail security detection method and system based on frequency domain and semantic analysis, electronic equipment and a computer readable storage medium. The method comprises the following steps: obtaining a to-be-detected mail, and carrying out preprocessing operation on an image in an attachment of the to-be-detected mail; performing block operation on the preprocessed image, and then performing DCT (Discrete Cosine Transformation) on each block to generate a corresponding DCT coefficient matrix; according to the DCT coefficient matrix, respectively calculating a high-frequency component entropy # imgabs0 # corresponding to each block; determining a steganography suspicion detection result of the mail according to the # imgabs 1 # value; based on the steganography suspicion detection result, SMTP flow semantic analysis of the mail is triggered, and a comprehensive risk score # imgabs2 is obtained; and based on the comprehensive risk score # imgabs3 #, triggering a linkage mechanism of multi-level alarm. According to the invention, a data stealing protection effect with high detection rate, low delay and strong adaptability on the mail is realized, and a reliable technical guarantee is provided for enterprise-level network security.

The present application relates to the technical field of information security, and discloses a text steganography method and apparatus for a browser webpage, and an electronic device. The method comprises: on the basis of a preset character set, converting target text information requiring steganography, to obtain a encoding set, each encoding record in the encoding set comprising a digital code and an encoding sequence number; on the basis of a preset adjustment strategy and all the encoding records, adjusting original font size values of target nodes in a target node set; creating a pseudo element set on the basis of the adjusted target node set, wherein a specified style defined by each pseudo element has a first association relationship with an original style of the corresponding target node, the pseudo element is used for inserting the specified style at a specified position in the corresponding target node, and a display attribute of the pseudo element is set not to be directly displayed on a browser webpage; and generating the browser webpage on the basis of the target node set and the pseudo element set.

The invention discloses a steganographic text detection technology based on text reconstruction and word order semantic features, and belongs to the technical field of information hiding. The method comprises the following steps: selecting an open source English steganography text data set containing three fields of social platform speaking, news manuscripts and film review; words in non-steganographic text sentences in the data set are randomly disorganized and sent to a large language model for reconstruction training, and the training target of reconstruction is an original text; and randomly disorganizing a data set text, and inputting the disorganized data set text into the trained model to generate a reconstructed text. And finally, inputting the original text, the disordered text and the reconstructed text into a steganography detection model, calculating a cosine similarity matrix, extracting a semantic difference feature map through a CNN, flattening, splicing semantic vectors of the original text, and inputting the semantic vectors into a classifier to output a binary detection result. Through continuous training, an error between a classifier output result of the model and a real labeling result is continuously reduced, so that parameters of a feature extractor and a classifier are optimized, and the model steganography detection accuracy is improved. According to the method, semantic information and word order features are utilized for classification, high accuracy, low cost and good interpretability are achieved, steganographic texts can be effectively detected, and information safety is improved.

The invention discloses a fault detection method for multi-modal sensing data fusion and embedded optimization for intelligent manufacturing, and the method comprises the steps: detecting the operation state of intelligent manufacturing equipment, collecting multi-modal sensing data, and carrying out the preprocessing of the multi-modal sensing data; based on an optimization criterion, obtaining embedding characteristics of each mode, and mapping the embedding characteristics to a uniform low-dimensional embedding space; introducing an optimization constraint mechanism for feature fusion; carrying out weighted fusion on each modal embedding feature; carrying out encryption transmission and steganography optimization regulation and control on the fusion embedded features, and uploading the fusion embedded features to a cloud for cross-factory collaborative operation and maintenance; an information and data bidirectional reversible reconstruction and precision guarantee mechanism is constructed, and accurate decoding of embedded information, lossless restoration of original data and accurate traceability of faults are realized. According to the method, the response precision and deployment adaptability of fault detection and predictive maintenance in the industrial intelligent manufacturing process are improved, and the method is suitable for a complex working condition environment with extremely high requirements on model stability and processing efficiency in a manufacturing field.

Exemplary systems and methods are disclosed for removing steganography from digital data is disclosed. The method and system involve receiving a digital data. At least one processing device accesses a steganography purifier model. The at least one processing device includes at least a generator configured to scale a magnitude of individual data elements of the digital data from a first value range to a second value range. The scaled data elements are downsampled to remove steganography data embedded in the digital data and produce a purified version. The purified version is upsampled by interpolating new data elements between one or more adjacent data elements to provide an upsampled purified version. The magnitude of the data elements of the upsampled purified version are scaled from the second value range to the first value range to generate a purified output version.

A method includes providing an image; analyzing the image to determine one or more encodable areas; determining a plurality of distinct serial numbers; adding the plurality of distinct serial numbers to a database; and producing a first plurality of first tags based on the image, each of the first tags including encoded information in at least one encodable area thereon, the encoded information for each particular first tag including a corresponding particular unique serial number of the distinct serial numbers, wherein at least some of the encoded information is encoded using steganography. Information in the image is used to authenticate a product.

The invention relates to a message mapping-based generative implicit representation steganography method, which comprises the following steps of: representing multimedia data by using an implicit neural representation technology, and converting the multimedia data into uniform point cloud data for message embedding; a secret message needing to be embedded is expressed in a binary mode and then converted into noise data through mapping, the noise data are input into a function generator to be subjected to message embedding, a message extractor is used for extracting the noise data, and the secret-containing message is recovered through inverse mapping; the function generator and the message extractor are obtained through training of a training set; in a message embedding process, a noise space of the function generator applies a single-bit and multi-bit message mapping scheme to embed noise data; in a noise extraction process, a message extractor extracts noise data by setting a plurality of point convolution layers and a full connection layer. According to the method, multimedia data of different sizes can be received, the robustness is good, the message extraction accuracy reaches the baseline level, and the method also has the advantage in the quality of the generated secret-containing carrier.

A method and system for detecting computer network data leaks over optical channels, for example using a mobile phone or other handheld device to rapidly scan a room with many light sources to identify the hidden transmission of data via optical steganography. The method of identification leverages spectral divergence created by the entropy produced by steganographically embedding data in the optical channel. The method and system proceed through multiple steps that can be computed in near real-time to eliminate background spectrum effects and isolate likely sources of information. The user or automated detection system captures a short video, and the video frames are then subdivided into smaller blocks effectively producing many adjacent videos of smaller pixel area.

The invention relates to a robust image watermark embedding method based on fixed neural network steganography, and belongs to the technical field of computers. According to the method, the problems that a traditional image watermarking technology is prone to being damaged by attacks such as compression and cutting and the fine tuning cost is high are solved, robustness is obtained by adopting a HiDDeN framework to pre-train a watermark extractor, a potential diffusion model is constructed, the decoder weight is frozen, binary watermark information is mapped into potential spatial disturbance vectors, and therefore the robustness of the image watermarking technology is improved. A learnable module is utilized to generate disturbance through an L-BFGS optimizer, a visual undifferentiated image is reconstructed through a fixed decoder, and a fixed extractor verifies the watermark. According to the method, steganography is pre-set in a generation stage, post-processing performance loss is avoided, watermark consistency, attack resistance and safety are remarkably improved in combination with a fixed network structure, and the method is suitable for digital copyright protection and content traceability.

The present invention provides a video steganography method and device, belonging to the field of video processing technology. The method comprises: determining a suitable 4×4 residual coefficient block from candidate 4×4 residual coefficient blocks based on the embedding strength and random seed of each candidate 4×4 residual coefficient block; collecting the first N high-frequency residual coefficients of the 4×4 residual coefficient block in a preset scanning order to construct a residual coefficient array; converting the residual coefficient array into an intermediate array according to a preset conversion rule, using the intermediate array to determine a target point in N-dimensional space, and calculating the mapping value of the target point and its 2N neighboring points according to a preset spatial encoding rule; and modifying the residual coefficient array into a target residual coefficient array based on the mapping value of the target point and its 2N neighboring points and the value of the secret information, thereby embedding the secret information. The present invention has the advantages of large embedding capacity, small embedding error, and high visual quality of the carrier video.

The application discloses a high-capacity provably secure steganographic embedding and extracting method and system based on cascade sampling, and belongs to the technical field of message steganography. The method comprises the following steps: acquiring input content and a secret message, and initializing a steganographic set; inputting the input content at a time step into a generation model for inference prediction to obtain a predicted candidate word set and a probability set corresponding to the predicted candidate word set; performing recursive uniform grouping on the candidate word set in combination with the probability set, and selecting a target group according to the secret message; updating the steganographic set according to the selected target group, and generating input content according to the updated steganographic set; re-executing the step of inputting the input content at the time step into the generation model for inference prediction until the secret message is intercepted completely, and outputting a final steganographic set. The application improves the steganographic capacity and the quality of generated content while proving the security of steganography.

The invention discloses a JPEG image batch steganography method and system based on experience security, and belongs to the technical field of information security. The method comprises the following steps: screening batch steganography carriers from a candidate JPEG image set based on experience security; calculating a non-zero DCT coefficient feature and a cost response curve D-alpha of each batch of steganography carriers; and calculating the optimal load rate of each batch of steganography carriers based on the non-zero DCT coefficient characteristics, the cost response curve D-alpha and the length of the load message, and executing steganography of the load message according to the optimal load rate. According to the method, the security of large-batch image steganography communication under an adaptive steganography algorithm can be improved.