The invention relates to a reversible information hiding method for an encrypted image, belonging to the technical field of cryptology and information safety. The method comprises the following steps of: (1), encrypting an original plaintext image according to an encryption key so as to generate the encrypted image; (2), embedding secret information into the encrypted image according to an information hiding key so as to generate the encrypted image including the secret information; and (3), decrypting the encrypted image including the secret information according to the encryption key so as to generate a decrypted image including the secret information, and recovering the plaintext image and extracting the secret information according to a hidden secret. The reversible information hiding method disclosed by the invention has the benefits that: the number of effective pixels used in fluctuation function calculation is increased; the quality of the decrypted image is improved; and the reversible information hiding method for the encrypted image is high and steady in performance.

Reversible information hiding method for encrypted image

The invention relates to an RFID positioning method based on an adaptive deep belief network. The method comprises a step of laying the positions of a reader and reference tags, and calculating distances from the reference tags to the reader, a step of allowing the reader to send electromagnetic wave signals to the reference tags and receive signal intensity RSSI values, and constructing a training sample vector matrix, a step of constructing the adaptive deep belief network, taking the RSSI value of each reference tag as an input value, and taking the distance d of each reference tag as an output value, a step of using a contrastive divergence algorithm to complete the pretraining of a network parameter, a step of using an adaptive moment estimation method to adjust a weight of each layer of a deep learning network, and a step of allowing the reader to send a signal to a tag to be measured and receive an RSSI value, and using the deep belief network to predict the position of the tag to be measured. According to the method, the adaptive deep belief network is used, a nonlinear relationship between a signal intensity value and the distance is constructed, a cross entropy cost function is used, and a problem of a slow learning rate is alleviated.

RFID positioning method based on adaptive deep belief network

The invention relates to the field of DNA encoding, image encryption and error correcting code, and specifically relates to an image encryption error correction method based on DNA encoding. The image encryption error correction method based on DNA encoding includes the steps: according to the gray scale space of an image, bringing forward piecewise linearity chaotic mapping; introducing Hamming code to a DNA sequence set, constructing a Hamming distance constraint condition among sequences and invertibly completing a Hamming distance constraint condition among sequences, and with combination of a GC content constraint condition, constructing a DNA sequence set and designing a combination constraint condition; and utilizing the improved genetic algorithm to design DNA sequences with an error correction function, and using the DNA sequences to encode the encrypted image so as to generate a DNA encoding encryption image which can correct errors. The image encryption error correction method based on DNA encoding has a good encryption effect, and can realize the error correction function.

Image encryption error correction method based on DNA encoding

The invention provides a cellular automata and chaotic mapping-based digital image encryption method and a decryption method thereof. The encryption method includes the following steps that: a 288-bit key is utilized to generate chaotic mapping parameters and cellular automaton evolution rules which are required by an encryption algorithm; pre-processing such as three-dimensional decomposition and blocking, is carried out on an original image; 3D chaotic mapping is adopted to scramble pixel positions; cross-exclusive-OR operation is performed on image blocks to be encrypted; and a 2D second-order cellular automata used for generating boundaries, which is provided by the present invention, is utilized to carry out iterative encryption on an unfolded plaintext, pixels are mixed, and iteration is repeated until an iteration requirement is satisfied; and reverse pre-processing is carried out, and blocked ciphertext images are combined into a ciphertext image.

Cellular automata and chaotic mapping-based digital image encryption method and decryption method thereof

The invention discloses a chaos theory-based digital image parallel encryption method comprising the following steps: a chaotic sequence is used for subjecting a plaintext image to overall position scrambling operation, the plaintext image is divided into a number of parts, each part of the plaintext image is subjected to parallel local dispersal operation, a last pixel of each part of the plaintext image and a first pixel of a next part of the plaintext image are swapped, and the last step is repeated till overall dispersal of the plaintext image is completed. Compared with technologies of the prior art, the chaos theory-based digital image parallel encryption method is advantageous in that differential attacks and statistical characteristic analysis can be well resisted, chose-plaintext or cryptograph attacks can be also effectively resisted, large secret key space and good encryption effect can be exerted, and parallel calculating capability of a computer multinucleated cpu can be effectively used for effectively improving calculating speed and encryption performance.

Chaos theory-based digital image parallel encryption method

The invention relates to the field of image encrypting and encoding and designs a novel piecewise linear chaotic mapping image encrypting and encoding method. In the method, image pixel based piecewise linear chaotic mapping is put forward, and a true encrypting secret key is obtained by the aid of an initial secret key and a cleartext; the true encrypting secret key is taken as an initial value of the piecewise linear mapping, an image is subjected to encrypting operation by the aid of two rounds of chaotic operations to complete encryption of the image; finally the encrypted image pixel and the piecewise linear chaotic mapping put forward are subjected to reverse iteration to complete recoding of the encrypted image. As is shown from the analog result and safety analysis, the method is good in encrypting effect and can resist relevant attacks of an invader. The problem about how to apply the piecewise chaotic mapping put forward to encrypting and encoding of the image simultaneously is emphatically solved.

Novel piecewise linear chaotic mapping image encrypting and encoding method

The invention relates to the field of artificial intelligence and in particular to a method for improving a restricted Boltzmann machine (RBM). The RBM is trained by a new objective function which is described in the description, wherein the logp(V|[theta]) is an unimproved objective function (log likelihood), the F(v; [theta]) is a free energy function, and [lambda] is a penalty coefficient. By restricting the value of the energy function, an energy plane is made more flat, thereby making it easier to sample from a model and obtaining a more excellent RBM. The excellence of the RBM not only lies in a capability of extracting more excellent features, and but also a capability of searching a better parameter space to initialize a deep network.

Method for improving restricted Boltzmann machine

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Novel piecewise linear chaotic mapping image encrypting and encoding method

Method for improving restricted Boltzmann machine