Stream Encryption Research Articles

High-capacity multi-MSB predictive reversible data hiding in encrypted domain for triangular mesh models

Reversible data hiding in encrypted domain (RDH-ED) is widely used in sensitive fields such as privacy protection and copyright authentication. However, the embedding capacity of existing methods is generally low due to the insufficient use of model topology. In order to improve the embedding capacity, this paper proposes a high-capacity multi-MSB predictive reversible data hiding in encrypted domain (MMPRDH-ED). Firstly, the 3D model is subdivided by triangular mesh subdivision (TMS) algorithm, and its vertices are divided into reference set and embedded set. Then, in order to make full use of the redundant space of embedded vertices, Multi-MSB prediction (MMP) and Multi-layer Embedding Strategy (MLES) are used to improve the capacity. Finally, stream encryption technology is used to encrypt the model and data to ensure data security. The experimental results show that compared with the existing methods, the embedding capacity of MMPRDH-ED is increased by 53 %, which has higher advantages.

Modeling relationships in non-commutative two-operand two-bit cet-operations of a double cycle when permuting the operands

The object of the research is relationships in non-commutative two-operand two-bit CET-operations of a double cycle when operands are permuted. The article is devoted to studying the results of the computational experiment, which is in building a model of relationships in non-commutative two-operand two-bit CET-operations of a double cycle with the operands permutation in order to ensure the possibility of building cryptographic systems with XOR sequence encryption. The theoretical and practical results of the work are obtained on the basis of the computational experiment data. The results of researching the CET-operations data make it possible to build cryptographic systems with XOR sequence ciphering and to improve the quality of low-resource stream encryption systems. The mathematical description of the computational experiment results made it possible to establish relationships between pairs of non-commutative two-operand two-bit CET-operations of a double cycle when operands are permuted. The possibility of constructing a group of commutative two-operand two-bit CET-operations of a double cycle based on the modification of a known two-operand operation by one-operand operations to within the permutation of the crypto-transformation results has been studied. The correctness of constructing a group of CET-operations, both without operand permutation and such that allow operand permutation, has been verified. The model for building a group of asymmetric two-operand two-bit CET-operations of a double cycle, which allow the operands permutation is proposed. Applying the substitution model made it possible to obtain pairs of interrelated operations in this group. The obtained pairs of interconnected operations provide a description of modification for direct and inverse non-commutative CET operations when permuting the operands. The obtained results provide the possibility of building cryptographic systems that encrypt both the input open information under the control of the XOR sequence and the XOR sequence under the control of the input open information. Further research will be aimed at establishing relationships in non-commutative two-operand two-bit CET operations of the triple cycle when operands are permuted.

Securecipher: An instantaneous synchronization stream encryption system for insider threat data leakage protection

The paper addresses the persistent challenge of insider threat in cybersecurity. Despite advancements in detection and prevention technologies and approaches, the complexity of digital environments and the ingenuity of insiders remain a problem. We propose an encryption algorithm called Securecipher, specifically designed to protect file systems from insider threats. The requirements that an algorithm must meet in this context are outlined, along with a method for its development. A context-based key generation mechanism is introduced, eliminating the need for key storage. A file marking mechanism is proposed that enables protection of the encryption algorithm against specific insider threat attacks. The proposed encryption algorithm meets the requirements posed by insider threats and has successfully passed 87 % of the NIST tests, equivalent to 13 out of 15 tests passed. Compared to conventional algorithms, the proposed encryption algorithm is more efficient in the context of insider threats, allowing access to distant locations instantaneously. In the specific case of the comparison with the RC4 algorithm, it showed a 0.25 s higher speed when accessing the last position of a 128-bytes file. Furthermore, a significant increase in the vocabulary of the encrypted text with Securecipher compared to the original text is observed, approximately 42 times more.

Comparative Analysis of AES, Blowfish, Twofish, Salsa20, and ChaCha20 for Image Encryption

Nowadays, cybersecurity has grown into a more significant and difficult sci-entific issue. The recognition of threats and attacks meant for knowledge and safety on the internet is growing harder to detect. Since cybersecurity guar-antees the privacy and security of data sent via the Internet, it is essential, while also providing protection against malicious attacks. Encrypt has grown into an answer that has become an essential element of information security systems. To ensure the security of shared data, including text, images, or videos, it is essential to employ various methods and strategies. This study delves into the prevalent cryptographic methods and algorithms utilized for prevention and stream encryption, examining their encoding techniques such as advanced encryption standard (AES), Blowfish, Twofish, Salsa20, and ChaCha20. The primary objective of this research is to identify the optimal times and throughputs (speeds) for data encryption and decryption processes. The methodology of this study involved selecting five distinct types of images to compare the outcomes of the techniques evaluated in this research. The as-sessment focused on processing time and speed parameters, examining visual encoding and decoding using Java as the primary platform. A comparative analysis of several symmetric key ciphers was performed, focusing on handling large datasets. Despite this limitation, comparing different images helped evaluate the techniques' novelty. The results showed that ChaCha20 had the best average time for both encryption and decryption, being over 50% faster than some other algorithms. However, the Twofish algorithm had lower throughput during testing. The paper concludes with findings and suggestions for future improvements.

Design of an Encryption Chat Application Based on ChaCha20-Poly1305

This study introduces the meticulous design and development of a chat application fortified with the robust ChaCha20-Poly1305 encryption algorithm. The selected cryptographic algorithm is renowned for its efficacy in ensuring top-notch security. In our application, ChaCha20 serves as the backbone for stream encryption, ensuring that the message content remains confidential and impenetrable to eavesdroppers. Simultaneously, Poly1305, an esteemed message authentication code, guarantees the integrity and authenticity of each chat message. It ensures that the messages sent are genuine and have not been tampered with during transit. Together, the integration of these two components constructs a fortified wall against potential security breaches, safeguarding user communications. This not only instills confidence in users regarding the privacy of their conversations but also sets a benchmark in chat application security. The overarching aim is to offer an impeccable blend of user-friendly experience and top-tier security, revolutionizing the way secure communications are perceived and utilized.

Two-dimensional modified pixel value differencing ($$2D-MPVD$$) image steganography with error control and security using stream encryption

Two-dimensional modified pixel value differencing ($$2D-MPVD$$) image steganography with error control and security using stream encryption

HIGHLY RECONFIGURABLE SOFT-CPU BASED PERIPHERAL MODULES DESIGN

Research motivation. When developing microcontrollers, manufacturers try to include as many different types of peripherals as possible in order to increase the marketing attractiveness of their products. On the one hand, with a large assortment of various peripheral modules, it is very difficult to implement several devices of the same type in the microcontroller: manufacturers are mainly limited to 1-2 instances, in rare cases 4 modules of the same type are included. On the other hand, most software projects do not use all the peripherals of modern microcontrollers and many devices are left unused, while there may be a shortage of other types of modules. Another problem that has become especially noticeable for microcontrollers used in the field of IoT is the cryptographic protection of data that is transmitted through built-in information exchange interfaces. The main efforts of researchers and developers of cryptographic data protection methods were aimed at reducing energy-intensive operations, memory access iterations and speeding up encryption processes while maintaining a high level of cryptographic protection and enabling efficient data distribution within IoT devices networks. Research results. This paper presents an alternative approach to the manufacture of peripheral modules as part of microcontrollers. The authors propose to use a configurable software processor module based on the MIPS architecture with a reduced instruction set and limited capabilities. Conclusions. This approach would make it possible to dynamically change the functionality of peripheral modules in accordance with the requirements of the developed software solution, which in turn will increase the efficiency of the microcontroller chips capabilities utilization. In addition, the transfer of data stream encryption functions to the reconfigurable core of the peripheral module will provide fast and transparent cryptographic protection, as well as allow offloading the microcontroller core and increasing the energy efficiency of chips while reducing their production cost.

Lossless Reversible Data Hiding in Encrypted Image for Multiple Data Hiders Based on Pixel Value Order and Secret Sharing

Reversible data hiding in encrypted images (RDH-EI) is instrumental in image privacy protection and data embedding. However, conventional RDH-EI models, involving image providers, data hiders, and receivers, limit the number of data hiders to one, which restricts its applicability in scenarios requiring multiple data embedders. Therefore, the need for an RDH-EI accommodating multiple data hiders, especially for copyright protection, has become crucial. Addressing this, we introduce the application of Pixel Value Order (PVO) technology to encrypted reversible data hiding, combined with the secret image sharing (SIS) scheme. This creates a novel scheme, PVO, Chaotic System, Secret Sharing-based Reversible Data Hiding in Encrypted Image (PCSRDH-EI), which satisfies the (k,n) threshold property. An image is partitioned into N shadow images, and reconstruction is feasible when at least k shadow images are available. This method enables separate data extraction and image decryption. Our scheme combines stream encryption, based on chaotic systems, with secret sharing, underpinned by the Chinese remainder theorem (CRT), ensuring secure secret sharing. Empirical tests show that PCSRDH-EI can reach a maximum embedding rate of 5.706 bpp, outperforming the state-of-the-art and demonstrating superior encryption effects.

Spatial-Temporal Feature with Dual-Attention Mechanism for Encrypted Malicious Traffic Detection

While encryption ensures the confidentiality and integrity of user data, more and more attackers try to hide attack behaviours through encryption, which brings new challenges to malicious traffic identification. How to effectively detect encrypted malicious traffic without decrypting traffic and protecting user privacy has become an urgent problem to be solved. Most of the current research only uses a single CNN, RNN, and SAE network to detect encrypted malicious traffic, which does not consider the forward and backward correlation between data packets, so it is difficult to effectively identify malicious features in encrypted traffic. This study proposes an approach that combines spatial-temporal feature with dual-attention mechanism, which is called TLARNN. Specifically, first we use 1D-CNN and BiGRU to extract spatial features in encrypted traffic packets and temporal features between encrypted streams, respectively, which enriches the features of different dimensions, and then, the soft attention mechanism is focused on the encrypted data packets to extract features. Ultimately, the second layer of the soft attention mechanism is used for aggregating malicious features. Several comparative experiments are designed to prove the effectiveness of the proposed scheme. The experimental results demonstrate that the proposed scheme has a significant performance improvement compared to existing ones.

Air target recognition method against ISRJ for radio frequency proximity sensors using chaotic stream encryption

The interrupted-sampling repeater jamming (ISRJ) can cause false targets to the radio-frequency proximity sensors (RFPSs), resulting in a serious decline in the target detection capability of the RFPS. This article proposes a recognition method for RFPSs to identify the false targets caused by ISRJ. The proposed method is realized by assigning a unique identity (ID) to each RFPS, and each ID is a periodically and chaotically encrypted in every pulse period. The processing technique of the received signal is divided into ranging and ID decryption. In the ranging part, a high-resolution range profile (HRRP) can be obtained by performing pulse compression with the binary chaotic sequences. To suppress the noise, the singular value decomposition (SVD) is applied in the preprocessing. Regarding ID decryption, targets and ISRJ can be recognized through the encryption and decryption processes, which are controlled by random keys. An adaptability analysis conducted in terms of the peak-to-side lobe ratio (PSLR) and bit error rate (BER) indicates that the proposed method performs well within a 70-kHz Doppler shift. A simulation and experimental results show that the proposed method achieves extremely stable target and ISRJ recognition accuracies at different signal-to-noise ratios （SNRs） and jamming-to-signal ratios (JSRs).

Improved Salsa20 Stream Cipher Diffusion Based on Random Chaotic Maps

To enhance stream ciphers, numerous studies have concentrated on the randomness, unpredictable nature, and complexity of keystream. Numerous stream algorithms have been put forth. Most of them require a significant amount of computational power. Salsa20 is a high-performance stream encryption solution that works on computers with fewer resources and uses a secure method that is faster than AES. They suggest Salsa20 for encryption in common cryptographic applications. Users who value speed over certainty should utilize the Salsa20 family of reduced-round ciphers, such as the (8,12) round cipher. It uses a 256-bit key and a hash algorithm. A successful fusion makes use of both the Salsa20 algorithm's and the random maps' advantages to improve the Salsa20 algorithm's shortcomings by increasing its unpredictability. Particularly now that Salsa20/7 has been hacked and Salsa20/12 is no longer as secure as it previously was. As a result, Salsa20 needs to achieve a high level of diffusion to withstand known attacks. Right now, salsa20 and its shortened versions rank among the fastest ciphers. This study presents a novel lightweight approach to construct a strong keystream that is sufficiently random to avoid being predicted by adversaries, achieve good diffusion, and withstand known assaults. A NIST test found that the performance of the (Salsa20-chaotic maps) approach in terms of data integrity and secrecy is nearly 0.3131 higher than that of the Salsa20 .

Joint Optimization–Encryption Model Based on Auto Encoder Neural Network, Variable-Length Dynamic S-Box and New Stream Encryption

The openness of the Internet makes information transmission prone to the risk of illegal eavesdropping, and data security and user privacy protection have become one of the key research hotspots. Aiming to solve the problem that a single encryption method cannot provide comprehensive security guarantees and the traditional one-time pad encryption method consumes a large amount of secure channel resource, this paper innovatively proposes a variable-length dynamic S-box and a cross-mapping sequence-based new type of stream encryption, and an improved method of synchronizing keys during a one-time pad transmission. On this basis, this paper innovatively proposes a joint optimization–encryption model based on the auto encoder neural network, variable-length dynamic S-box and new stream encryption. Finally, taking the optical fiber transmission as an example, the simulation results show that the joint optimization–encryption model proposed in this paper can save security channel resources and effectively resist common security attacks in the process of high-speed information transmission.

SEMMI: Multi-party security decision-making scheme for linear functions in the internet of medical things

In the Internet of Medical Things(IoMT), developing models using machine learning algorithms can detect and assist users effectively in identifying health issues. Due to the risk of private user information being leaked during the machine learning application process, the widespread application and development of IoMT applications are hampered. Encrypting data is a good way to protect user privacy. However, given the participants’ limited resources, processing and analyzing ciphertext data presents a significant challenge.As a result, this paper proposes a secure and efficient assisted decision-making scheme (SEMMI) that is appropriate for the IoMT applications. SEMMI performs a thorough analysis of each participant’s resource constraints, divides the data circulation process into four stages, and constructs a data circulation and ciphertext calculation protocol. Data transmission security is ensured through the use of stream encryption and homomorphic encryption. Each participant sends the ciphertext to the cloud, and the cloud calculates the ciphertext data, effectively relieving each participant’s computational load. The security of the final result is guaranteed by matching the result with pre-decryption. The scheme’s security and efficiency are demonstrated experimentally. The results indicate that the accuracy loss of each data set under the ciphertext is no more than 3% at most and that the cloud performs most of the calculations for each participant. Finally, SEMMI is applied to the FedAvg algorithm, demonstrating the scheme’s universality.

Properties of the cost function in the iterative algorithm for generating nonlinear substitution

To ensure the security of information technology, cryptographic information protection tools are used, in particular block and stream encryption algorithms with a symmetric key. Reliability and cryptographic strength of cryptoalgorithms is provided by the properties of the applied primitives. For example, non-linear substitutions (S-boxes) are used as the main component of modern symmetric ciphers. Therefore, generation of substitutions is an important scientific task directly related to the security of information technology and improvement of modern symmetric ciphers. The paper investigates the properties of iterative algorithms for generating non-linear substitutions and special cost functions, which play a decisive role in the heuristic search for S-boxes with the required properties. We consider the cost function of the WCF (Cost Function of the content of the Walsh-Hadamard spectrum) and optimize its parameters. The obtained optimization results in combination with the Hill Climbing iterative search algorithm can reduce significantly the number of iterations. In particular, we show that for a substitution search with a non-linearity of 104, on average, we reduce the computational complexity of generation by more than 20%. In addition, it is possible to increase the success rate of the heuristic search. In particular, for the selected settings, in 100% of cases, a beaktive S-box with a non-linearity of 104 was found.

Study of a new cost function for generating random substitutions of symmetric ciphers

Cryptographic transformations with a secret key play an essential role in providing information and cyber security. Block and stream symmetric ciphers are used in various applications both as a separate cryptographic protection mechanism and as part of other applications (pseudo-random sequence generators, hashing algorithms, electronic signature protocols, etc.). Therefore, the design and study of individual components of symmetric ciphers is a relevant and important scientific task. In this paper we consider and investigates iterative algorithms for generating non-linear substitutions (substitutions, S-boxes), which are used in modern block and stream encryption algorithms with a symmetric key. Cryptographic resistance of symmetric ciphers to statistical, differential, linear and other methods of cryptanalysis is provided by the properties of substitutions. In addition, S-boxes must be random from the point of view of the possibility to use algebraic cryptanalysis. Therefore, the task of quickly generating random S-boxes with the desired cryptographic properties is an urgent, but extremely difficult task. For example, the best known generation algorithm requires more than 65 thousand iterations to find a random bijective 8-bit substitution with a non-linearity of 104. In this paper, we study an iterative algorithm for generating substitutions for hill climbing with different cost functions and propose a new cost function, the use of which can significantly reduce the number of search iterations. In particular, the search for a bijective S-box with nonlinearity 104 requires less than 50 thousand iterations.

On Privacy Risks of Watching YouTube over Cellular Networks with Carrier Aggregation

One's core values, personality, and social status may be reflected in the watch history of online video streaming services such as YouTube. Unfortunately, several prior research work demonstrates that man-in-the-middle or malware-assisted attackers can accurately infer the titles of encrypted streaming videos by exploiting the inherent correlation between the encoded video contents and the traffic rate changes. In this paper, we present a novel video-inference attack called Moba that further exacerbates the problem by only requiring the adversary to simply eavesdrop the broadcast messages of a primary cell of a targeted user's cellular phone. Our attack utilizes a side channel in modern cellular networks that leaks the number of actively transmitting cells for each user. We show that this seemingly harmless system information leakage can be used to achieve practical video-inference attacks. To design effective video-inference attacks, we augment the coarse-grained side-channel measurements with precise timing information and estimate the traffic bursts of encrypted video contents. The Moba attack considers an adversary-chosen set of suspect YouTube videos, from which a targeted user may watch some videos during the attack. We confirm the feasibility of Moba in identifying the exact YouTube video title (if it is from the suspect set) via our over-the-air experiments conducted in LTE-Advanced networks in two countries. Moba can be effective in verifying whether a targeted user watches any of the suspect videos or not; e.g., precision of 0.98 is achieved after observing six-minutes of a single video play. When further allowed to observe multiple video plays, Moba adversary is able to identify whether the targeted user frequently watches the suspect videos with a probability close to one and a near-zero false positive rate. Finally, we present a simple padding-based countermeasure that significantly reduces the attack effectiveness without sacrificing any cellular radio resources.

Secure Selections on Encrypted Multi-writer Streams

Performing searches over encrypted data is a very current and active area. Several efficient solutions have been provided for the single-writer scenario in which all sensitive data originate with one party (the Data Owner ) that encrypts and uploads the data to a public repository. Subsequently, the Data Owner accesses the encrypted data through a Query Processor , which has direct access to the public encrypted repository. Motivated by the recent trend in pervasive data collection, we depart from this model and consider a multi-writer scenario in which the data originate with several and mutually untrusted parties, the Data Sources . In this new scenario, the Data Owner provides public parameters so that each Data Source can add encrypted items to the public encrypted stream; moreover, the Data Owner keeps some related secret information needed to generate tokens so that different Query Sources can decrypt different subsets of the encrypted stream, as specified by corresponding access policies. We propose security model for this problem that we call Secure Selective Stream ( SSS ) and give a secure construction for it based on hard problems in Pairing-Based Cryptography. The cryptographic core of our construction is a new primitive, Amortized Orthogonality Encryption , that is crucial for the efficiency of the proposed implementation for SSS .

Deceptive Techniques to Hide a Compressed Video Stream for Information Security.

With the recent development of video compression methods, video transmission on traditional devices and video distribution using networks has increased in various devices such as drones, IP cameras, and small IoT devices. As a result, the demand for encryption techniques such as MPEG-DASH for transmitting streams over networks is increasing. These video stream security methods guarantee stream confidentiality. However, they do not hide the fact that the encrypted stream is being transmitted over the network. Considering that sniffing attacks can analyze the entropy of the stream and scan huge amounts of traffic on the network, to solve this problem, the deception method is required, which appears unencrypted but a confidential stream. In this paper, we propose the new deception method that utilizes standard NAL unit rules of video codec, where the unpromised device shows the cover video and the promised device shows the secret video for deceptive security. This method allows a low encryption cost and the stream to dodge entropy-based sniffing scan attacks. The proposed stream shows that successful decoding using five standard decoders and processing performance was 61% faster than the conventional encryption method in the test signal conformance set. In addition, a network encrypted stream scan method the HEDGE showed classification results that our stream is similar to a compressed video.

A NEW TECHNIQUE FOR DETERMINING REGION OF INTEREST IN SELECTIVE VIDEO PROTECTION APPROACH

Today, the use of video communication in real-time applications is rising at a rapid rate and most of these videos require secure transmission like surveillance, video conferencing, video on demand, and medical and military imaging systems. The trade-off between data security and real-time performance is the main challenge in this field. This paper presents a protection approach for H.246 compression standard that provides a balancing between the security level and coding efficiency. A new technique of region selection for the motion information of the video is designed based on canny edge detection scaling which reduces the amount of encrypted data ,and a strong and fast stream encryption is presented using key generation model of chaos method and RC4 algorithm. The experimental results of the performance metrics confirmed the high perceptual and cryptographic security of the proposed approach against attacks and showed that all the requirements of compression efficiency are satisfied.

IMG‐forensics: Multimedia‐enabled information hiding investigation using convolutional neural network

Information hiding aims to embed a crucial amount of confidential data records into the multimedia, such as text, audio, static and dynamic image, and video. Image-based information hiding has been a significantly important topic for digital forensics. Here, active image deep steganographic approaches have come forward for hiding data. The least significant bit (LSB) steganography approach is proposed to conceal a secret message into the original image. First, the lightweight stream encryption cryptography encrypts secret information in the cover image to protect embedded information from source to destination. Whereas the encrypted embedded cover information into the carrier of stego-image with the help of the LSB and then transmit. In the proposed investigational scheme, a convolutional neural net is used. A model is trained to detect and extract patterns of image hidden features, encrypted stego-image optimization, and classify original and cover images of steganography. Through the experiment result on the forensic image database for mobile steganography of the Center for Statistics and Application in Forensic Evidence, the overall embedded and extracting that the proposed scheme can achieve information hiding as well as revealing with an accuracy rate of 95.1%. The experimental result shows the robustness of the model in terms of efficiency as compared to other state-of-the-art schemes.