CN112332971A - Safe and efficient data transmission method based on superlattice and compressed sensing - Google Patents

Safe and efficient data transmission method based on superlattice and compressed sensing Download PDF

Info

Publication number
CN112332971A
CN112332971A CN202011068734.5A CN202011068734A CN112332971A CN 112332971 A CN112332971 A CN 112332971A CN 202011068734 A CN202011068734 A CN 202011068734A CN 112332971 A CN112332971 A CN 112332971A
Authority
CN
China
Prior art keywords
alice
bob
sequence
superlattice
data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202011068734.5A
Other languages
Chinese (zh)
Other versions
CN112332971B (en
Inventor
张平
唐艳艳
李小龙
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hunan University of Technology
Original Assignee
Hunan University of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hunan University of Technology filed Critical Hunan University of Technology
Priority to CN202011068734.5A priority Critical patent/CN112332971B/en
Publication of CN112332971A publication Critical patent/CN112332971A/en
Application granted granted Critical
Publication of CN112332971B publication Critical patent/CN112332971B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/001—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using chaotic signals
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
    • G16Y30/00—IoT infrastructure
    • G16Y30/10—Security thereof
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
    • H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
    • H04L63/0435—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload wherein the sending and receiving network entities apply symmetric encryption, i.e. same key used for encryption and decryption
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Security & Cryptography (AREA)
  • Computing Systems (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Computer Hardware Design (AREA)
  • General Engineering & Computer Science (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)

Abstract

The data transmission efficiency and the data privacy are important research subjects for data transmission of the internet of things. The invention provides a safe and efficient data transmission coding and decoding method based on a superlattice and compressive sensing technology, and aims to solve two major goals of data transmission efficiency and privacy protection of the Internet of things. The invention constructs a lightweight data coding and decoding method which simultaneously supports compression and encryption by combining a superlattice symmetric key and a compression sensing technology so as to ensure the efficiency and the privacy of data transmission. The method can also be popularized to other network application scenes except the Internet of things.

Description

Safe and efficient data transmission method based on superlattice and compressed sensing
Technical Field
The invention relates to the field of Internet of things, in particular to a coding and decoding method for safe and efficient data transmission of the Internet of things.
Background
The coming of the 5G era can accelerate the large-scale application of the Internet of things. The Internet of things is the most promising application field in the 5G era. The 3GPP, a well-known telecommunication standards-making organization, defines three major 5G application scenarios. Two application scenarios are oriented to the relevant application field of the internet of things, and are respectively mMTC (large Machine Type of Communication) oriented to large-scale Machine Type Communication and uRLLC (Ultra-reliable and Low Latency Communications) oriented to scenes such as the internet of vehicles. The development of the related industries of the internet of things such as industrial internet, smart city, environmental monitoring and smart home is accelerated when the 5G era comes.
In the 5G era, the Internet of things has wide market prospect, and the requirements for safe and efficient transmission of mass data are certainly brought forward. Challenges are also presented to the design of a secure and efficient data transmission scheme. For example, mtc requires that each terminal should have a security algorithm and protocol to support secure and efficient transmission of massive data. mtc security algorithms should be lightweight otherwise latency is increased. This dual requirement for safety and simplicity of the algorithm further increases the difficulty of the scheme design.
Many internet of things application scenarios involve the transmission of privacy data, and privacy protection of data is one of the most important requirements. Data privacy protection in data transmission process is usually realized by adopting a symmetric key system, and key distribution is one of the most important and difficult parts in the symmetric key system. In a symmetric key system, a sender and a receiver must share the same secure key to successfully perform secure communication. Traditional symmetric key distribution is achieved by establishing a separate "secure channel". A "secure channel" can be either a specially constructed communication link or a virtual channel. A 'safe virtual channel' is constructed based on an asymmetric key system to realize symmetric key distribution, and the method is one of the most common schemes in the field of traditional network security. However, the traditional symmetric key distribution mechanism based on public key cryptography is not the best solution for solving the high-speed key distribution challenge in the field of the general internet of things. On the one hand, the public key cryptography mechanism is computationally expensive and can only be used to distribute small amounts of data. And many common internet of things devices adopt low-end chips, have limited computing capability and cannot support the symmetric key distribution rate matched with the 5G transmission rate. On the other hand, the resources of the internet of things equipment are limited, the equipment has weak anti-attack capability, and the equipment is easily attacked by an adversary successfully, so that the private key is leaked.
A key generation scheme based on a physical mechanism is one of the research focuses in the field of network security in recent years. The most common concept of symmetric key generation schemes is to extract the common randomness between communicating entities for key generation. However, most of the existing symmetric key generation schemes based on the physical mechanism are not suitable for the security application scenarios of the internet of things in a wider sense. First, the symmetric key generation rate of the existing scheme is not high. The data transmission rate of 5G theory can reach Gbps order of magnitude, and the existing symmetric key generation rate based on physical mechanism is lower than the order of magnitude. This necessarily results in excessive reuse of the symmetric key. In a common application scene of the internet of things, due to the fact that computing capacity of equipment is limited, a lightweight encryption algorithm is widely used, and safety risks are generally increased when symmetric keys are used repeatedly. Secondly, many schemes are more demanding to apply, limited by the physical mechanism itself. For example: in the vibration-based characteristic scheme, since both communication parties need to acquire consistent vibration characteristics, it is necessary for both communication parties to maintain close contact. As another example, sound waves decay rapidly, and safety solutions based on sound wave characteristics have distance requirements.
In the 5G era, the Internet of things has wide market prospect, massive data transmission requirements are generated, and efficient data transmission is also a basic requirement. How to design a large-scale data transmission scheme of the internet of things so as to satisfy both the security and efficiency requirements? How to achieve a secure and efficient unification of data transfer?
In order to solve the safety and efficiency challenges in large-scale internet of things data transmission scenes, the invention combines a superlattice physical mechanism and a compressive sensing technology to research and construct a safe and efficient internet of things data transmission coding and decoding method. On one hand, the high-speed generation of the symmetric key of the Internet of things is realized by utilizing physical characteristics of the superlattice material, such as physical irreproducibility, high-speed chaotic synchronization and the like. On the other hand, the characteristics of sparsity and compressibility in the data of the Internet of things are mined by using a compressed sensing technology, and high-performance data compression and recovery are realized. Meanwhile, the characteristic of low-rank random measurement of compressed sensing is utilized to realize the combination with a superlattice symmetric key generation technology, and a lightweight privacy protection method with low encryption calculation cost is further constructed.
Disclosure of Invention
The invention aims to solve the technical problem of providing a safe and efficient internet of things data transmission coding and decoding method based on superlattice and compressed sensing aiming at the defects of the prior art.
The technical scheme of the invention is as follows:
a safe and efficient Internet of things transmission data coding and decoding method comprises the following steps:
(1) initialization phase
The two communication parties of the Internet of things equipment, namely Alice and Bob, respectively carry at least one superlattice chip, and at least one superlattice chip is respectively arranged in the superlattice chips carried by the Alice and the Bob, is from the same semiconductor wafer and has the same size and shape;
(2) key generation phase
The same excitation signal A used by Alice and BobcAs the input of the superlattice chip, based on the chaos synchronization principle of the superlattice, highly similar output signals A are generatedoAnd Bo；
As a further optimization, both parties may use the same pre-stored excitation signal sequence to avoid the overhead of transmitting excitation signals by both communicating parties.
As a further optimization, both parties can also directly generate the same pseudo-random sequence as an excitation signal by using the same pseudo-random function and the same function initial value, so as to avoid the overhead of transmitting the excitation signal by both communication parties.
Alice and Bob respectively pair AoAnd BoObtaining a digital signal A after quantization conversiondAnd BdAlice and Bob should use the same quantization conversion technique and parameters to ensure that the resulting digital signal A is adAnd BdStill highly similar; alice and Bob filter out A by exchanging a certain amount of informationdAnd BdThe mismatch bits in the signals are matched to obtain completely consistent signals Ap and Bp(ii) a Alice and Bob use the same Toeplitz-like matrix, with sequence ApAnd BpAre multiplied respectively to obtain the same new sequence AsAnd Bs；
As a further optimization, Alice and Bob may further pair AsAnd BsIs converted to obtainNew sequences with certain characteristics (still denoted A)sAnd Bs). The new sequences obtained by Alice and Bob should also be identical. As an example, the sequence may be augmented using pseudo-random number generation techniques such that the new sequence length is larger.
(3) Encoding stage
Alice organizes original data to be sent into a one-dimensional array X with the length of N;
alice follows AsTruncating a sequence As1And converting it into a matrix phi of M rows and N columns, where M < N must be satisfied; when A iss1When the length of the matrix is MN, the matrix phi can be directly converted into the matrix phi according to the sequence of row priority or column priority; when A iss1Is less than MN, a pseudo-random function can be selected and A is sets1As the input of the pseudo random function, then generating a random sequence with the length of MN through the pseudo random function, and further converting the random sequence into a matrix phi according to the sequence of row priority or column priority;
performing matrix multiplication operation on the matrix phi and the array X by Alice to obtain a sequence Y with the length of M;
alice sends Y to Bob through a public channel;
(4) decoding stage
Bob receives data Y sent by Alice through a public channel;
bob from BsTruncating a sequence Bs1(ii) a Bob truncated sequence Bs1Should be associated with Alice from AsTruncating a sequence As1Keep synchronous and have the same length to ensure the sequence B intercepted by Bobs1With sequence A intercepted by Alices1Are completely the same; bob uses the same conversion method as that of Alice to intercept the sequence Bs1Converting the matrix into a matrix with M rows and N columns, wherein the matrix is completely the same as a matrix phi obtained by Alice and also marked as phi;
bob recovers the recovered data X 'of length N using compressed sensing recovery techniques (including but not limited to OMP, SAMP) based on the received data Y and the constructed matrix phi, and treats X' as the final received data.
Has the advantages that:
according to the scheme adopted by the invention, the safe and high-speed generation of the symmetric key between the two communication parties of the Internet of things is realized through the superlattice chaotic synchronization technology and the physical irreproducible characteristic of the superlattice material. By combining the superlattice symmetric key high-speed generation technology and the compressed sensing technology, the data privacy protection in the data transmission process of the Internet of things is guaranteed, and the data transmission efficiency is also guaranteed. The scheme is not limited to the field of the Internet of things, and can also be applied to other types of network application scenes.
Drawings
FIG. 1 is a schematic view of the overall structure of the present invention
FIG. 2 high speed symmetric key generation based on superlattice chaotic synchronization
FIG. 3 data encoding and decoding method based on superlattice and compressed sensing
Fig. 4 superlattice chaotic synchronization signal and correlation analysis, (a) upper graph: a superlattice chaotic synchronization signal of the device a; (b) the middle graph is as follows: a superlattice chaotic synchronization signal of the device B; (c) the following figures: and (4) carrying out correlation analysis on the output signals of the A and the B.
Fig. 5 shows an example of image data codec. (a) Left panel: original graphics; (b) the middle graph is as follows: encoded images (encrypted and compressed); (c) right panel: a decoded image.
Fig. 6 shows an example of coding and decoding of a sequence signal. (a) The upper diagram: an original temperature sequence signal; (b) the middle graph is as follows: coded sequence signals (encrypted and compressed); (c) the following figures: a decoded sequence signal.
The specific implementation mode is as follows:
the specific implementation process of the invention is as follows:
1. network model and attack model
1.1 network model
The system implemented by the invention at least comprises two devices. For convenience of description, these two devices will be referred to as Alice and Bob, respectively, and will be the sender and receiver of the data transmission, respectively. Alice and Bob are both common Internet of things devices. And Alice is responsible for acquiring data and performing compression and encryption operations on the data. The present invention collectively refers to compression and encryption operations as encoding operations. Alice sends the encoded result to Bob through a public communication channel. The invention does not relate to communication details such as modulation and demodulation. Bob decodes the received data to obtain the final result. The decoding operation mainly involves decompression and decryption. In reality, the internet of things device is usually both a data sender and a data receiver. The present invention can be generalized to this scenario. In practical applications, if the device is used as a data sender, the detailed function implementation may be performed with reference to descriptions of Alice in the present invention. If the device is used as a data receiver, the detailed function implementation can be performed with reference to the description of Bob in the present invention.
1.2 attack model
The invention focuses on the privacy of data and the efficiency of transmission. Other security problems such as replay attacks, denial of service attacks, tampering with data, and the like are not involved. These security issues can often be safeguarded by means of authentication of the device, digital signatures, data integrity protection, etc.
In the application scenario of the invention, it is assumed that an adversary can launch the following 2 types of attacks:
(1) known as a Ciphertext attack (COA: Ciphertext-only attack).
The communication parties use the common channel for data transmission. The adversary can perform operations such as eavesdropping on the data transmitted in the public channel, so as to acquire the ciphertext data transmitted by the two parties. Therefore, the adversary can launch known ciphertext attacks on the scheme.
(2) Known as a plaintext attack (KPA: knock-play attack).
The internet of things equipment may be deployed in an unattended scene and collects environmental data. At which point the adversary can launch a known plaintext attack. In one aspect, the adversary may acquire the required plaintext data by deploying the same sensors in the vicinity of the transmitting device. On the other hand, the adversary can acquire ciphertext data transmitted in the public channel by eavesdropping.
It is generally assumed that the adversary has difficulty or cost in obtaining the plaintext. Thus, the adversary's ultimate goal is to crack the decryption key through a small number of plaintext-ciphertext pairs.
2. Scheme integral structure
The overall framework of the solution of the invention is shown in figure 1. The internet of things equipment Alice and Bob are a sender and a receiver of data transmission respectively. Data transmission is performed based on a common channel, and transmitted data may be eavesdropped by a third party adversary. Both parties transmit compressed and encrypted data through a common channel to achieve efficiency and privacy protection of data transmission. The study protocol mainly consists of two parts, respectively: (1) a symmetric key high-speed generation method based on superlattice chaotic synchronization; (2) data encoding and decoding methods based on superlattice and compressed sensing.
The devices Alice and Bob carry one to a plurality of superlattice chips. The devices carried by Alice and Bob have a certain pairing relationship with each other. In one embodiment, at least one of the superlattice chips carried by Alice and Bob is processed using the same or similar processing environment or manufacturing process. As an example, there may be one chip in each of the superlattice chips carried by Alice and Bob, from the same semiconductor wafer, and of the same size and shape. For convenience of description, the subsequent operations of the present invention are described based on the superlattice chips carried by Alice and Bob, respectively, and having a pairing relationship. The present invention also refers to such superlattice chips with matching relationships as twin or multiple superlattice chips. According to the physical properties of the superlattice materials, the superlattice chips with the pairing relationship can generate highly similar output signals under the action of the same excitation signals. The superlattice chips which are not in pairing relationship can not generate similar output signals under the action of the same excitation signals.
3. Symmetric key high-speed generation method based on superlattice chaotic synchronization
The process of generating the symmetric key between the devices of the internet of things at high speed is shown in fig. 2. The process of generating the superlattice symmetric key at high speed mainly comprises four stages: (1) generating a superlattice chaotic synchronization signal; (2) quantization generation of synchronous random sequences; (3) collaborative filtering of mismatched bits; (4) privacy amplification of weak security keys.
3.1 Generation of superlattice chaotic synchronization signals
In fig. 2, matching superlattice chips are carried by the internet of things devices Alice and Bob. They can produce highly similar output signals under the same excitation signal.
The same excitation signal A used by Alice and BobcAs the input of the superlattice chip, based on the chaos synchronization principle of the superlattice, highly similar output signals A are generatedoAnd Bo. The excitation signal does not need to be kept secret, so Alice and Bob can dynamically generate the same excitation signal either by directly transmitting the excitation signal over a public channel or by using the same pseudo-random function and the same initialization seed.
3.2, the quantization generation of synchronous random sequence;
the chaotic synchronization signal belongs to an analog signal. It needs to go through the quantization generation stage of synchronous random sequence to obtain highly correlated synchronous random sequence signal. Alice and Bob respectively pair AoAnd BoObtaining a digital signal A after quantization conversiondAnd BdAlice and Bob should use the same quantization conversion technique and parameters to ensure that the resulting digital signal A is adAnd BdStill highly similar; the rate of the quantization stage will have some effect on the final symmetric key generation rate. The method for improving the quantization generation rate is more, a high-speed ADC chip can be directly adopted, and high-speed quantization generation can be realized based on a low-speed ADC through a parallel technology. In specific implementation, the key generation rate needs to be determined by integrating requirements such as cost budget and symmetric key generation rate.
3.3 collaborative filtering of mismatch bits
Due to the influence of flaw factors in the process of processing the superlattice chip, a certain number of unmatched bits must exist in the synchronous sequences of both communication parties. The highly correlated random sequences obtained by Alice and Bob are not identical, for example, the random sequence generated in fig. 3 has a mismatch phenomenon at the 3 rd bit. In order to generate identical symmetric keys on both sides of communication, Alice and Bob exchange a certain amount of information to filter out adAnd BdTo obtain a completely consistent signal ApAnd Bp. The fuzzy extraction technology is a representative method for filtering mismatching bits of synchronous sequences, and the method is adopted to coordinate and filter mismatching bits in sequences of both sides.
3.4 privacy amplification of weak security keys.
During the mismatch bit coordination phase, some assistance data needs to be exchanged in the common communication channel, thereby weakening the security key. Therefore, the security performance of the keys of the two communication parties is weakened to a certain extent, and the weak security key is obtained. After the weak security key is subjected to privacy amplification, a superlattice symmetric key with information theory security can be obtained. In order to obtain a superlattice symmetric key with information theory security, in the invention, Alice and Bob use the same Toeplitz-like matrix as the sequence ApAnd BpAre multiplied respectively to obtain the same new sequence AsAnd BsAnd the result is used as the final superlattice symmetric key between the two parties.
The method is not only used for privacy amplification, but also used for improving the subsequent compressed sensing recovery performance. In the digital signal obtained after quantization, the effective bit on the left side changes slowly. Taking a 3-bit binary number as an example, the decimal number changes from 7 to 4, the leftmost significant bits thereof all remain 1, while the rightmost significant bits thereof have changed 3 times between 0 and 1. The left-hand significant bit is changed less frequently than the right-hand significant bit. Too many left-hand significant bits may reduce the random performance of the sequence. In reality, the effective number of ADC bits for quantization conversion is usually much larger than 3, so that a large number of binary bits on the left side of the digital conversion result are changed slowly, which affects the degree of randomization of the local segment of the output random sequence. Since the compressed sensing is to be implemented based on the random sequence, the performance of the compressed sensing is negatively affected.
4. Data coding and decoding method based on superlattice and compressed sensing
The framework structure of the data transmission coding and decoding scheme is shown in fig. 3. The internet of things equipment Alice and Bob represent a sending end and a receiving end of data transmission respectively. The scheme consists of two parts, encoding and decoding. And the data encoding process is completed by the data sending end Alice. And the coded result is sent to Bob by Alice through the public channel for decoding and recovery. And the data decoding process is completed by the data receiving end Bob.
The following describes specific implementation processes of data encoding and data decoding, respectively.
4.1 symmetric key generation.
The two communication parties Alice and Bob carry a superlattice chip which is twin or multi-twin with each other respectively. The two parties synchronously generate a symmetric key sequence by using the 'Internet of things symmetric key high-speed generation method based on synchronization of superlattice wontons' introduced in the previous section. We will respectively name the symmetric key sequences generated synchronously by Alice and Bob as AsAnd Bs。
4.2 Transmission data encoding Process
Both the data compression and the data encryption are completed in the data encoding stage, and the specific encoding process is as follows.
(1) Data collection and preparation. The data sending end Alice organizes the original data to be sent into a one-dimensional array X with the length of N.
(2) A measurement matrix is constructed. Alice symmetric key sequence A from superlatticesTruncating a sequence As1And converted into an M × N matrix phi. Wherein M is less than N. Alice follows AsIn the truncated sequence As1May or may not be MN long. When A iss1When the length of the matrix is MN, the matrix phi can be directly converted into the matrix phi according to the sequence of row priority or column priority; when A iss1Is less than MN, a pseudo-random function can be selected and A is sets1As the input of the pseudo random function, then generating a random sequence with the length of MN through the pseudo random function, and further converting the random sequence into a matrix phi according to the sequence of row priority or column priority;
(3) the sensing measurements are compressed. And performing compressed sensing measurement operation on the original data X by using a compressed sensing-based technology to obtain an output result Y. And the Alice performs matrix multiplication operation on the one-dimensional array X and the matrix phi to obtain a sequence Y with the length of M.
In fig. 3, Y is called encrypted compressed data because the above-described operation realizes both functions of data compression and data encryption. In one aspect, a data compression function is implemented. Due to the low-rank measurement characteristic of compressed sensing, the length M of the obtained data Y is far smaller than the length N of the original data X. Thus, a data compression operation is achieved. On the other hand, an encryption function is realized. Since the random measurement matrix phi is dynamically generated based on the superlattice symmetric key. The random measurement matrix phi is therefore inherently secure. And the original data X is subjected to a compressed sensing measurement process, which is equivalent to the completion of an encryption process of a one-time pad. The privacy of data X is protected.
(4) Alice sends Y to Bob over the public channel.
4.3 Transmission data decoding Process
The data decoding process in fig. 2 is performed by the data receiving end Bob. The method mainly comprises the following three stages:
(1) data reception and data separation
And Bob receives the data packet sent by Alice from the public channel. And separates the encrypted compressed data Y according to the communication protocol.
This document focuses on privacy protection of data and efficiency of data transfer. And other security contents such as integrity protection of data are not involved. For example, the data may not have been sent by Alice, or the data may have been tampered with illegally. Therefore, in actual application, other mechanisms such as signature verification can be introduced between the two communication parties according to needs.
(2) Decryption and decompression
Bob generates a symmetric key sequence B identical to Alice by using a superlattice symmetric key generation mechanisms. Then, based on the symmetric key sequence, a random measurement matrix phi identical to Alice is constructed according to the same rule as Alice.
And finally, recovering the recovered data X 'with the length of N from the encrypted compressed data Y obtained in the last step by utilizing a compressed sensing data recovery technology or a cooperative compressed sensing data recovery technology, and taking the X' as the finally received data. In the compressed sensing data recovery stage, the existing mainstream compressed sensing data recovery technology can be adopted for data recovery. Such as OMP (organic Matching pursuit) and SAMP (sparse Adaptive Matching pursuit), among others. A main stream cooperative recovery technique such as KCS or DCS may be used.
5. Security analysis
The section comprehensively analyzes and demonstrates the safety of the proposed scheme, and the method is respectively developed from two aspects of the safety of the superlattice symmetric key and the safety of the data transmission coding and decoding method.
5.1 Security analysis of superlattice keys
(1) Physical unclonability of superlattice chips
Superlattice materials have a physically unclonable characteristic that results from random fluctuations at the molecular level. The superlattice material is processed by adopting a molecular beam epitaxy growth technology MBE. According to thermodynamics and statistical mechanics theory, random fluctuation of molecular level is inevitably introduced in the MBE growth process. The random fluctuation of molecular level is widely existed in each quantum well layer and barrier layer of the superlattice, so that the superlattice material can not be copied artificially.
The conditions for generating the superlattice chaotic synchronization signal are very strict. Typically only between superlattice chips of the same size and shape from the same semiconductor wafer, called matched superlattices. Resonant tunneling currents in the superlattice are extremely sensitive to molecular level fluctuations in the quantum well layer and the barrier layer. Even if the same manufacturing equipment and process conditions are adopted, the difference of the chaotic oscillation modes can be obvious among different superlattice chips processed from two different semiconductor wafers.
The superlattice chip can be regarded as a Physical Uncloneable Function (PUF), which has important safety significance. The safety of the superlattice key can be guaranteed through a safety management system and a safety management process of a chip real object. The number of the superlattice chips processed from the same wafer is limited, and the superlattice chips cannot be copied and regenerated, so that the safety management and control on the system level of the chip entity are operable.
(2) Unpredictability of superlattice chaotic signals
The pseudo-random number, which is currently commonly used in security algorithms, is essentially a deterministic algorithm. Given the known pseudo-random number algorithm and initial values, the pseudo-random number sequence can be reproduced accurately.
The superlattice symmetric key is generated based on a superlattice chaotic signal. The randomness comes from a microscopic physics level, and an adversary cannot detect the physical generation process of the superlattice chaotic signal. Theoretically, as long as the adversary does not possess the physical entity of the superlattice chip, even by adopting advanced machine learning means, the output signal and the random signal sequence (key) cannot be predicted.
5.2 Security of data Transmission encoding and decoding methods
The security of the present invention is analyzed below based on the aforementioned attack models, respectively.
(1) Known ciphertext attacks
The encoding process of the scheme herein is achieved by a compressed sensing technique. In known ciphertext attack, ciphertext data acquired by an adversary is essentially a compressed sensing measurement result.
The random measurement matrix used in the compressed sensing measurement process is dynamically generated according to a superlattice symmetric key sequence. Only the data sender Alice and the data receiver Bob possess the symmetric key sequence, and thus the random measurement matrix is secure.
A random out-of-order aliasing operation exists in the measurement process of compressed sensing. In particular, this operation is achieved by a matrix multiplication operation between the random measurement matrix and the raw data. In theory, it is not feasible to achieve reverse recovery of data without knowledge of the random measurement matrix.
(2) Known plaintext attacks
In the known plaintext attack model, an adversary can acquire y and a small number of x. And attempt to crack the key with a small number of plaintext-ciphertext pairs.
According to the secure compressed sensing theory, the key of the lightweight encryption algorithm is a random measurement matrix. In the scheme, random measurement matrixes used in each compressed sensing measurement process are different from each other and are dynamically constructed according to a brand-new superlattice symmetric key sequence. Thus, even if the adversary is able to break the corresponding key from the known plaintext-ciphertext pair, the key is invalidated because it is dynamically updated.
The random measurement operation of compressed sensing is a low-rank operation, and a dimension compression process exists. This further increases the difficulty for an adversary to crack the key from the pair of historical plaintext ciphertexts.
In fact, even if the key updating speed is reduced, the safety of the scheme can still be guaranteed. A simple quantitative analysis is performed below. And according to the compressed sensing measurement process Y being phi X, the number of unknowns in the secret key phi is MN. If at least MN unknowns are to be solved, we need to construct at least MN linearly independent equations. In each plaintext and ciphertext pair, the length of X is N, and the length of Y is M. The number of plaintext cipher text pairs required for solving phi is not less than N. The amount of data required is even larger, taking into account the correlation between the different equations. That is, as long as the number of key reuses is less than N, the scheme remains secure.
6. Demonstration of feasibility
In this subsection, we experimentally demonstrated the feasibility of the key modules of the protocol herein. To enhance the understanding of the protocol, the experimental demonstration process will emphasize the intuitiveness of the results. Specific arguments will be developed from the following two aspects. One is experimental demonstration of superlattice chaotic synchronization, which is the basis for constructing superlattice symmetric keys. The other is experimental demonstration of security compressed sensing coding and decoding, which is the basis for realizing data compression and data privacy protection.
6.1 Experimental demonstration of chaos synchronization of superlattice.
Experimental demonstration is carried out on the generation of the superlattice chaotic synchronization signal, and the result is shown in fig. 4. Fig. 4a and 4b are chaotic synchronization signals respectively obtained by Alice and Bob. Fig. 4c is the correlation analysis result of the two signals. From the test results, it can be seen that the signals a and B exhibit a high correlation characteristic, which is the basis for constructing a symmetric key between a and B. At the same time, the randomness of signals a and B is better. On the one hand, this means that it is difficult for an adversary to attempt to predict this signal by machine learning means. On the other hand, a random measurement matrix satisfying the compressed sensing requirement can be conveniently constructed from random signals.
6.2 Experimental demonstration of secure compression codec
The compressive sensing technology has been widely accepted in the industry, and significantly improves the data compression capability by mining sparsity or compressible features contained in a signal. The random low rank measurement feature in the compressed sensing measurement may provide privacy protection for the data.
Image data and sequence data are two representative data types in the context of the internet of things. The project applicant respectively shows the data compression performance and the data privacy protection capability of the compressed sensing coding and decoding scheme on the basis of the two types of data. The effect is shown in fig. 5 and 6. Where fig. 5a and 6a are raw data, fig. 5b and 6b are encoding results, and fig. 5c and 6c are decoding results. As can be seen from the experimental results of fig. 5 and 6: firstly, the privacy protection effect of the coding scheme is better. The coded image and the coded sequence have good random characteristics, and the detail information of the original image and the sequence is effectively hidden. Secondly, the compression effect of the coding scheme is good. Although the data size of the encoded image sequence in this experiment is less than 40% of the original image and sequence, the decoding results of the two examples retain most of the detail characteristics of the original image and sequence, respectively.

Claims (1)

1. A safe and efficient data transmission method based on superlattice and compressed sensing is characterized by comprising the following steps:
(1) initialization phase
The two communication parties of the Internet of things equipment, namely Alice and Bob, respectively carry at least one superlattice chip, and at least one superlattice chip is respectively arranged in the superlattice chips carried by the Alice and the Bob, comes from the same semiconductor wafer and has the same size and shape;
(2) key generation phase
The same excitation signal A used by Alice and BobcAs the input of the superlattice chip, based on the chaos synchronization principle of the superlattice, highly similar output signals A are generatedoAnd Bo(ii) a Alice and Bob respectively pair AoAnd BoObtaining a digital signal A after quantization conversiondAnd BdAlice and Bob should use the same quantization conversion technique and parameters to ensure that the resulting digital signal A is adAnd BdStill highly similar; alice and Bob filter out A by exchanging a certain amount of informationdAnd BdTo obtain a completely consistent signal ApAnd Bp(ii) a Alice and Bob use the same Toeplitz-like matrix, with sequence ApAnd BpAre multiplied respectively to obtain the same new sequence AsAnd Bs；
(3) Encoding stage
Alice organizes original data to be sent into a one-dimensional array X with the length of N;
alice follows AsTruncating a sequence As1And converting it into a matrix phi of M rows and N columns, where M < N must be satisfied; when A iss1When the length of the matrix is MN, the matrix phi can be directly converted into the matrix phi according to the sequence of row priority or column priority; when A iss1Is less than MN, a pseudo-random function can be selected and A is sets1As the input of the pseudo random function, then generating a random sequence with the length of MN through the pseudo random function, and further converting the random sequence into a matrix phi according to the sequence of row priority or column priority;
performing matrix multiplication operation on the matrix phi and the array X by Alice to obtain a sequence Y with the length of M;
alice sends Y to Bob through a public channel;
(4) decoding stage
Bob receives data Y sent by Alice through a public channel;
bob from BsTruncating a sequence Bs1(ii) a Bob truncated sequence Bs1Should be associated with Alice from AsTruncating a sequence As1Keep synchronous and have the same lengthTo ensure the sequence B intercepted by Bobs1With sequence A intercepted by Alices1Are completely the same; bob uses the same conversion method as that of Alice to intercept the sequence Bs1Converting the matrix into a matrix with M rows and N columns, wherein the matrix is completely the same as a matrix phi obtained by Alice and also marked as phi;
bob recovers the recovered data X 'of length N using compressed sensing recovery techniques (including but not limited to OMP, SAMP) based on the received data Y and the constructed matrix phi, and treats X' as the final received data.
CN202011068734.5A 2020-09-27 2020-09-27 Safe and efficient data transmission method based on superlattice and compressed sensing Active CN112332971B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011068734.5A CN112332971B (en) 2020-09-27 2020-09-27 Safe and efficient data transmission method based on superlattice and compressed sensing

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011068734.5A CN112332971B (en) 2020-09-27 2020-09-27 Safe and efficient data transmission method based on superlattice and compressed sensing

Publications (2)

Publication Number Publication Date
CN112332971A true CN112332971A (en) 2021-02-05
CN112332971B CN112332971B (en) 2022-06-07

Family

ID=74314658

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011068734.5A Active CN112332971B (en) 2020-09-27 2020-09-27 Safe and efficient data transmission method based on superlattice and compressed sensing

Country Status (1)

Country Link
CN (1) CN112332971B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117896064A (en) * 2024-03-14 2024-04-16 中国人民解放军火箭军工程大学 Superlattice twin PUF key synchronization method and system with low calculation overhead

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102938698A (en) * 2012-10-16 2013-02-20 东北大学秦皇岛分校 Security data transmission method based on compressive sensing theory
US20140064479A1 (en) * 2012-09-06 2014-03-06 Samsung Electronics Co., Ltd Method and systems for multilevel data security
US20180091300A1 (en) * 2016-09-29 2018-03-29 Shigeki Tomishima Technologies for physically unclonable functions with magnetic tunnel junctions
CN110519036A (en) * 2018-05-22 2019-11-29 中国科学院苏州纳米技术与纳米仿生研究所 The application method of data encryption and transmission method, terminal device and superlattices chaos device
CN111314065A (en) * 2020-01-21 2020-06-19 中国科学院苏州纳米技术与纳米仿生研究所 Data encryption transmission method, server and system based on virtual private network

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140064479A1 (en) * 2012-09-06 2014-03-06 Samsung Electronics Co., Ltd Method and systems for multilevel data security
CN102938698A (en) * 2012-10-16 2013-02-20 东北大学秦皇岛分校 Security data transmission method based on compressive sensing theory
US20180091300A1 (en) * 2016-09-29 2018-03-29 Shigeki Tomishima Technologies for physically unclonable functions with magnetic tunnel junctions
CN110519036A (en) * 2018-05-22 2019-11-29 中国科学院苏州纳米技术与纳米仿生研究所 The application method of data encryption and transmission method, terminal device and superlattices chaos device
CN111314065A (en) * 2020-01-21 2020-06-19 中国科学院苏州纳米技术与纳米仿生研究所 Data encryption transmission method, server and system based on virtual private network

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117896064A (en) * 2024-03-14 2024-04-16 中国人民解放军火箭军工程大学 Superlattice twin PUF key synchronization method and system with low calculation overhead
CN117896064B (en) * 2024-03-14 2024-05-31 中国人民解放军火箭军工程大学 Superlattice twin PUF key synchronization method and system with low calculation overhead

Also Published As

Publication number Publication date
CN112332971B (en) 2022-06-07

Similar Documents

Publication Publication Date Title
Hua et al. Visually secure image encryption using adaptive-thresholding sparsification and parallel compressive sensing
García-Guerrero et al. Randomness improvement of chaotic maps for image encryption in a wireless communication scheme using PIC-microcontroller via Zigbee channels
Zhang et al. Embedding cryptographic features in compressive sensing
Zhang A new unified image encryption algorithm based on a lifting transformation and chaos
Chen et al. An efficient image encryption scheme using lookup table-based confusion and diffusion
Bakhshandeh et al. An authenticated image encryption scheme based on chaotic maps and memory cellular automata
US11699361B2 (en) Data security apparatus and method using constant optical signal input to analog component
Liu et al. Cryptanalysis and improvement in a plaintext-related image encryption scheme based on hyper chaos
Singh et al. A comprehensive survey on encryption techniques for digital images
Xiao et al. Low-cost and secure multi-image encryption scheme based on P-tensor product compressive sensing
CN102523365A (en) Method for encrypting and decrypting image based on cellular automata
Priyanka et al. A survey of image encryption for healthcare applications
Achkoun et al. SPF-CA: A new cellular automata based block cipher using key-dependent S-boxes
Yang et al. A visually meaningful image encryption scheme based on lossless compression spiht coding
Zhang et al. Secure compressive sensing in multimedia data, cloud computing and IoT
CN112332971B (en) Safe and efficient data transmission method based on superlattice and compressed sensing
Khan et al. Elliptic curve cryptography for the security of insecure Internet of Things
Huang et al. Secure frequency-domain image compressed sensing with matrix-inversion-free recovery
Ramírez-Torres et al. Fpga implementation of a reconfigurable image encryption system
Mohaisen et al. Stream cipher based on chaotic maps
Ahmad Cryptanalysis of chaos based secure satellite imagery cryptosystem
Zhang et al. Privacy-preserving image compressed sensing by embedding a controllable noise-injected transformation for IoT devices
Ahmad et al. A multi-level blocks scrambling based chaotic image cipher
Hameed et al. SMX algorithm: A novel approach to avalanche effect on advanced encryption standard AES
Ge et al. Efficient Hyperchaotic Image Encryption Algorithm Based on a Fast Key Generation Method and Simultaneous Permutation‐Diffusion Structure

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant