Encryption Mode Research Articles

Encrypted Storage Method of Oral English Teaching Resources based on Cloud Platform

With the development of the times, the secure storage of educational resources has become one of the key security problems faced by colleges and universities. On the one hand, the cost of traditional resource storage is too expensive, on the other hand, its encryption and access efficiency are low. To solve this problem, this research takes the cloud platform serves as the main carrier for the encrypted storage of school teaching resources. On this basis, the convolutional neural network is encrypted and optimized, and the argmax algorithm is improved to improve the access efficiency of encrypted data. Finally, the effectiveness and superiority of the design method are compared and analyzed through the method of performance detection. The results show that the maximum consumption time of encryption and decryption of the encrypted storage model is no more than 20000ms, which is significantly less than that of the traditional model. The running time of the argmax output encryption module is 1.76ms and the running loss is 0.26 MB, which is less than that of the traditional model. It can be seen that the encrypted storage model has stronger encryption performance and access performance, and has a better application effect in the encrypted storage of oral English teaching resources with a large amount of access data and frequent updates.

25 Gb/s Physical Secure Communication Based on Temporal Spreading-Then-Random Phase Encryption

Ensuring high speed physical layer confidential data exchange in classical optical fiber channels is a critical challenge. In this letter, we experimentally demonstrated a physical secure optical communication system based on temporal spreading-then-random phase encryption scheme for secure transmission of 25 Gb/s intensity-modulated signal. Commercial low cost continuous-wave laser is employed as the optical source, and a chirped fiber Bragg grating followed by a phase modulator is utilized as a two-dimensional encryption module. Successful encryption and decryption of 25 Gb/s confidential data have been achieved by optimizing optical hardware parameters. The demonstrated system can combine the advantages of hardware and digital encryption, exhibiting great potential for providing physical layer security in future high-speed secure optical communication systems.

An Easy-to-Integrate IP Design of AHB Slave Bus Interface for the Security Chip of IoT

Information security is fundamental to the Internet of things (IoT) devices, in which security chip is an important means. This paper proposes an Advanced High-performance Bus Slave Control IP (AHB-SIP), which applies to cryptographic accelerators in IoT security chips. Composed by four types of function registers and AHB Interface Control Logic (AICL), AHB-SIP has a simple and easy-to-use structure. The System on Chip (SoC) design can be realized by quickly converting the nonstandard interface of the security module to the AHB slave interface. AHB-SIP is applied to the security accelerators of SM2, SM3, and SM4 and random number generator (RNG). Combined with a low-power embedded CPU, TIMER, UART, SPI, IIC, and other communication interfaces, a configurable SoC can be integrated. Moreover, SMIC 110 nm technology is employed to tape out the SoC on a silicon chip. The area of AHB-SIP is 0.072 mm2, only occupying 6‰ of the chip (3.45 ∗ 3.45 mm2), and the power consumption of encryption modules combined with AHB-SIP is lower than that combined with AXI interface, which is decreased up to 61.0% and is ideal for the application of IoT.

Identifying Symmetric-Key Algorithms Using CNN in Intel Processor Trace

Malware and ransomware are often encrypted to protect their own code, making it challenging to apply reverse engineering to analyze them. Recently, various studies have been underway to identify cryptography algorithms in malware or ransomware that use anti-reversing technology via deep-learning technology. In particular, CNNs (convolution neural networks) are deep-learning algorithms with superior performance, as compared to existing machine-learning algorithms in image classification. In the cases of malicious files to which anti-debugging techniques or anti-DBI (dynamic binary instrumentation) techniques are applied, if the traces are extracted using various debuggers or DBI, the traces are cut off due to these techniques. The IPT (Intel processor trace) has the advantage of extracting an accurate trace of a program by bypassing the anti-debugging or anti-DBI technique. This paper presents a novel method by which to identify the symmetric-key algorithms by applying a CNN to the traces extracted from the IPT. The IPT minimally interrupts software execution. First, the trace encrypted by the symmetric-key algorithms is extracted using the IPT. Then it is converted into an image to be an input into the CNN. The experiments were carried out with two different datasets. The first dataset contained traces extracted by different types of symmetric-key algorithms, and the training results were classified into nine classes with 100% accuracy. The second dataset contained traces that included the various bit sizes of the security keys and the block-cipher modes for each type of symmetric-key algorithm. Training results were classified into 36 classes with an accuracy of 70.55%. While previous studies have identified the types of encryption algorithms, this study employed a CNN to identify the number of key bits and the block-cipher modes as well.

Privacy-preserving credit evaluation system based on blockchain

In digital intelligence era, the authenticity of data and the privacy protection of data sharing and multiparty collaborative computing are key factors in building a good credit evaluation system. Although blockchain-based credit evaluation system considered this point, more studies on data privacy protection are either only the design of the framework or the proposal of the concept, which is insufficient for privacy protection. To provide a more comprehensive and reliable privacy-preserving scheme, this paper proposes a novel credit evaluation system with secure sharing and multiparty computation based on blockchain. The system consists of five modules: data, access control, data encryption, secure computation and model storage modules. The Hyperledger Fabric blockchain-based data module ensures the authenticity and traceability of the data source. The raw data are encrypted by a linear transformation algorithm in the data encryption module, which minimizes the output and utilization of data when leaving local storage and prevents potential privacy leakage in data sharing to the greatest extent. The phillie homomorphic encryption-based secure computation algorithm in the secure computation module achieves secure data sharing while applying the secure multiparty computation, which makes it possible to data sharing and privacy protection in multiparty computing. The system obtains final summary statistical results without exposing the raw data. Additionally, the final statistical results of the raw data can be inferred from the encrypted data, and their results are consistent. The correctness and accuracy of the linear conversion encryption mechanism and homomorphic encryption algorithm are proven by theoretical analysis. Security analysis and calculation case show the security of the proposed credit evaluation system and the correctness and effectiveness of the proposed encryption scheme.

Authenticated encryption mode with blocks skipping

Block symmetric ciphers are one of the most important components of modern information security systems. At the same time, in addition to the structure of the applied block symmetric cipher, the cryptographic strength and performance of the information protection system is largely determined by the applied encryption mode. In addition to high performance and high-quality destruction of block statistics, modern encryption modes should also protect encrypted information from occurred or intentionally introduced errors. In this paper, we have developed an encryption mode with blocks skipping and using a pseudo-random key sequence generator, which allows checking the integrity of encrypted information with accurate detection of the place where an error was introduced. In this case, the error detection accuracy is determined by the adjustable parameter of the macroblock size and can be set depending on the level of importance of the protected information. The developed encryption mode is characterized by the following key advantages: reducing the number of required encryption operations by half, while providing a high level of cryptographic quality; more effective destruction of macroblock statistics due to the use of an additional generator of pseudo-random key sequences, the impossibility of propagation of the occurred (intentionally introduced) error outside the macroblock, as well as higher values of the number of protection levels due to the possibility of classifying the initial states of the applied generators of pseudo-random key sequences. As proposed in this paper, the mode of authenticated encryption with blocks skipping can be recommended for use on mobile platforms that are demanding both in terms of the quality and reliability of the protected information and are limited in terms of computing and power resources.

1, 2, 3, Fork: Counter Mode Variants based on a Generalized Forkcipher

A multi-forkcipher (MFC) is a generalization of the forkcipher (FC) primitive introduced by Andreeva et al. at ASIACRYPT’19. An MFC is a tweakable cipher that computes s output blocks for a single input block, with s arbitrary but fixed. We define the MFC security in the ind-prtmfp notion as indistinguishability from s tweaked permutations. Generalizing tweakable block ciphers (TBCs, s = 1), as well as forkciphers (s = 2), MFC lends itself well to building simple-to-analyze modes of operation that support any number of cipher output blocks.Our main contribution is the generic CTR encryption mode GCTR that makes parallel calls to an MFC to encrypt a message M. We analyze the set of all 36 “simple and natural” GCTR variants under the nivE security notion by Peyrin and Seurin rom CRYPTO’16. Our proof method makes use of an intermediate abstraction called tweakable CTR (TCTR) that captures the core security properties of GCTR common to all variants, making their analyses easier. Our results show that many of the schemes achieve from well beyond birthday bound (BBB) to full n-bit security under nonce respecting adversaries and some even BBB and close to full n-bit security in the face of realistic nonce misuse conditions.We finally present an efficiency comparison of GCTR using ForkSkinny (an MFC with s = 2) with the traditional CTR and the more recent CTRT modes, both are instantiated with the SKINNY TBC. Our estimations show that any GCTR variant with ForkSkinny can achieve an efficiency advantage of over 20% for moderately long messages, illustrating that the use of an efficient MFC with s ≥ 2 brings a clear speed-up.

Fault attacks on authenticated encryption modes for GIFT

There are several authenticated encryption modes for block cipher GIFT in the NIST lightweight cryptography standardisation process. In this study, the authors research on the fault attacks on this kind of authenticated encryption modes and mainly complete two tasks. First, the fault attack on the nonce-based authenticated encryption mode LOTUS/LOCUS is presented. At Asiacrypt2016, Dobraunig et al. showed the first fault attacks on several nonce-based authenticated encryption modes. Because LOTUS/LOCUS adopts the structure similar to XEX with secret nonce-dependent masks, their work is not applicable to LOTUS/LOCUS. A new fault attack is launched on LOTUS/LOCUS assuming that two bits can be made to reset in the fixed location during the encryption process. In this attack, neither plaintext nor ciphertext of the underlying block cipher is necessary to be known. To recover the correct key, a few hundred faulty ciphertexts are needed when transient faults are injected, while just one faulty ciphertext is sufficient for a permanent fault. Second, the Collision Fault Attack on GIFT is shown, in which 64 faulty ciphertexts are needed to recover the correct key. Based on this attack, authenticated encryption modes ESTATE_TweGIFT-128, GIFT-COFB and SUNDAE-GIFT are analysed and their keys are efficiently obtained with chosen nonce.

The Design and Evolution of OCB

We describe OCB3, the final version of OCB, a blockcipher mode for authenticated encryption (AE). We prove the construction secure, up to the birthday bound, assuming its underlying blockcipher is secure as a strong-PRP. We study the scheme’s software performance, comparing its speed, on multiple platforms, to a variety of other AE schemes. We reflect on the history and development of the mode.

Development of complete image processing system including image filtering, image compression & image security

Computer vision is nowadays is one of the promising & evolving areas in information technology. Image processing is increasingly used in several applications such as automotive, medical or aerospace. Every computer vision application involves capturing several images with the help of camera. Image acquisition, image transmission & image security are the three important aspects of image processing system. This paper includes development of complete image processing system including improved median filtering with better PSNR & operating frequency, Image compression module with better PSNR & compression ratio, Image Encryption module using Advanced Encryption Standard.

Sparse representation based compressive video encryption using hyper-chaos and DNA coding

This work proposes a new and efficient sparse representation-based spatial compression of video signals integrated with a hyper-chaotic DNA coding-based encryption module that provides higher security. The betterment of compression efficiency is achieved by introducing sparse coding on the video frames, and higher security is obtained by applying 5D hyper-chaotic DNA coding on the sparse coded frames. This novel technique is applied to a large set of video signals for testing and compares its performance with some recently proposed video coding and encryption systems. To test and measure the efficiency and reliability of different encoding and encryption schemes, we consider a set of well-defined quality metrics, e.g., compression ratio, bit rate in compression, PSNR, NPCR, UACI, correlation coefficients, and histogram analysis, and measure the values of those metrics for different encoding and encryption modules. In addition, an ablation analysis is done. It shows improved quality matrices when we utilize DNA coding along with the 5D hyper-chaotic system-based encryption mechanism. We also perform the differential attack analysis for testing the security of the encryption modules. The quantitative measurements of these quality metrics for different algorithms demonstrate the superiority of the proposed algorithm to the other algorithms in efficiency, quality, and security.

Observations on the Security of COMET

Abstract This paper investigates the security of counter mode encryption with authentication tag (COMET), one of the 32 second-round candidates in National Institute of Standards and Technology’s lightweight cryptography standardization process, against differential cryptanalysis. CHAM-64/128 is a block cipher chosen as one of the underlying block ciphers in COMET for hardware-oriented applications, and a differential characteristic with a high probability for CHAM-64/128 is useful for forgery attacks on COMET. However, we find that the optimal $\mathbf{39}$-round differential characteristic for CHAM-64/128 proposed by Roh et al., which is the longest differential characteristic of CHAM-64/128, is invalid. Then, we propose a new method of distinguishing an $\mathbf{m}$-bit block cipher from an $\mathbf{m}$-bit random permutation using a differential characteristic with a probability not higher than $\mathbf{2^{-m}}$. Using our method, we use two $\mathbf{39}$-round differential characteristics with a probability of $\mathbf{2^{-64}}$ for CHAM-64/128 to distinguish $\mathbf{39}$-round-reduced CHAM-64/128 from a $\mathbf{64}$-bit random permutation, respectively. Furthermore, we refine the probabilities of two differentials with the same input and output differential masks as the two $\mathbf{39}$-round differential characteristics, respectively. Finally, we present the first forgery attacks on COMET with the two differentials without using weak keys. Our forgery attacks follow the nonce-misuse scenario. It should be noticed that this attack does not invalidate the security claims of the designers.

A SURVEY OF HOMOMORPHIC ENCRYPTION OF DATA IN CLOUD FOR SECURE STORAGE

Cloud computing is the transportation of computing assistance and the opportunity of computer system assets for storing of data and calculating ability without the administration of the user. Against the publishing business and the technical applications of cloud, more probable users are still to join the cloud and the users of cloud can put their less confidential data in the cloud. Loss of security in the cloud is an important problem. The information will be encrypted and gathered in the storage of cloud .The problem here is the informations can be send to or from a cloud in encrypted mode, the servers that function the cloud will not any task on it. In this paper wereviewe the homomorphic encryption techniques, Advantages and disadvantages of various research papers.

An Enhanced Data Security and Task Flow Scheduling in Cloud-enabled Wireless Body Area Network

Wireless body area networks (WBAN) consist of various sensors to collect essential data signals to monitor blood pressure, heartbeat, blood sugar level, pulse, and body temperature. However, such dense sensor networks face serious issues due to interference which degrades the system throughput. Similarly, data security is another important factor to be considered in WBAN. Interference can be avoided by dividing the sensors into a group based on their operational characteristics and data security can be enhanced using suitable encryption modules. Recently, cloud-based WBAN has gained more attention, as concepts of cloud offer various advantages for efficient data management and security factors. Considering these issues in WBAN and the advantages of a cloud environment, this research work proposes an enhanced data security through Advanced Encryption Standard (AES) and efficient task flow scheduling using Genetic Algorithm (GA). The proposed model outperforms better in task scheduling which greatly reduces the interference and increases the system throughput. The proposed model is experimentally validated in terms of throughput, execution time, response time, and encryption time. Conventional models such as DES and 3DES are used to compare the outcomes of the proposed model to validate the superior performance, and the proposed model performs better than conventional models.

Energetic Data Security Management Scheme using Hybrid Encryption Algorithm over Cloud Environment

Now-a-days all documents are in a digital format as well as everyone need to maintain their data in electronic mode with the help of cloud servers. A cloud server provides lots of facilities to users such as remote data maintenance, huge data handling and so on. But in the case of security many cloud servers are providing probabilistic results alone. So, that a new cloud server data maintenance scheme is required to provide a high-level data security to the cloud system in an efficient manner. This paper introduces a new crypto-approach called Novel Hybrid Encryption Mode (NHEM), in which this algorithm integrates several latest approaches of crypto logics into it and provides a top-end security level to the cloud data. This NHEM is derived from the base factors of two cryptographic algorithms called Advanced Encryption Standard with 512-bit size of key frequency with Message Digest (MD5) algorithm. By using the integration of these two powerful approaches, a novel approach called NHEM is designed and it provides a huge support to preserve security on cloud medium. The cloud data needs to be protected from unwanted threats and intruders by means of raising an interruption attacks on server. The proposed approach of Novel Hybrid Encryption Mode concentrates more on access control logics and the crypto norms with respect to privacy measures. In this paper, the proposed scheme assures the data is too robust and no one can attack the data without proper credentials as well as the outcome proofs are clearly given on the resulting unit of this paper. The Advanced Encryption Standard algorithm is a well-known and powerful crypto scheme and the MD5 algorithm is also considered to be the unique unidirectional algorithm to provide security level in energetic manner. These two algorithms are combined together with the bit frequency of 512 to achieve the highest accuracy levels in data security over cloud environment as well as the resulting portion clearly illustrates that with proper graphical outcome.

A blockchain-based collaborative training method for multi-party data sharing

In recent years, the construction of Space–Ground Integrated Network has been accelerated, connecting different types of networks in remote regions. The various devices are connected together, so that data that was difficult to communicate before can be used to train particular models together, giving birth to new service models. Privacy issues, however, remain a substantial concern affecting data sharing among multiple parties. Cooperative training methods such as federated learning usually require a centralized aggregator to aggregate the dispersed sub-models. In general, various privacy-preserving methods assume the aggregator as an honest-but-curious (HBC) role and cannot guarantee that the program can be executed correctly. In this paper, we propose a blockchain-based collaborative training method that uses the decentralized accounting technology of the blockchain to solve the trust problem between different participants. Through the anti-repudiation nature of the blockchain, it is ensured that the aggregation of the model is executed correctly. We designed a function encryption-based privacy preserving method in which the aggregator can only obtain the results of the aggregation model, and cannot access the models uploaded to the blockchain from other participants. Subsequently, a prototype system based on blockchain is developed to analyze and evaluate the time consumption of our proposed cooperative training method and function encryption module. The result of our experiments shows the feasibility of our cooperative training model.

A trojan framework in AES core to evade state-of-the-art HT detection schemes

This paper explores cipher-destroying and secret key emitting Hardware Trojan (HT) in Advanced Encryption Standard (AES) cores. It reports a malicious trojan circuit which is implanted in the 10th round of encryption modules to make the AES core vulnerable for system design. Stealthiness of the combinational trojan against the dimension of signal lines, involved to trigger the trojan, is examined. It is shown that such trojans are malicious and hard to detect following the existing trojan detection methodologies. The explored malevolent HT can be the cause of severe damage to a system as it leaks out the secret key to an intruder. An existing trojan detection technique is, therefore, modified to propose seamless detection of such trojans.

CFB-Then-ECB Mode-Based Image Encryption for an Efficient Correction of Noisy Encrypted Images

During the last few decades, the transmission of images over secure networks has exponentially grown. Data security in certain applications such as secure storage, authentication or privacy protection on cloud platforms, require specific strategies for multimedia. Cryptography can be used for this purpose. Indeed, using a secret key, it is possible to make data unreadable in order to secure it. Although encryption approaches are effective to make the original data unreadable, they are also very sensitive to noise. Because of the introduction of noise into an encrypted image during its transmission or storage, the original data cannot be recovered. In this article, we first describe a new encryption mode called CFB-then-ECB and based on a combination of the CFB mode and the ECB mode for AES encryption. Using this new encryption mode, if one encrypted pixel block is noised, this will result in two incorrectly reconstructed pixel blocks during the decryption (the current and the following pixel blocks). This noise spreading is then exploited in a new proposed approach of noisy encrypted image correction. It contains two main steps involving a classifier to discriminate clear and encrypted pixel blocks. After a direct decryption of a noisy encrypted image, the first step is to identify and localize the pixel blocks that are probably incorrectly decrypted. The second step of our proposed approach is to analyze and correct these pixel blocks. Experimental results show that the proposed method can be used to blindly correct noisy encrypted images, while preserving the image structure without increasing the original data size with additional information.

Symmetric Cryptoalgorithms in the Residue Number System

This paper presents theoretical backgrounds of the symmetric encryption based on the residue number system. The peculiarities of this approach are that in the case of restoring a decimal number based on its residuals using the Chinese remainder theorem, multiplication occurs by arbitrarily chosen coefficients (keys). It is established that cryptostability of the developed methods is determined by the number of modules and their bit size. In addition, the described methods are found to allow to almost indefinitely increase the block of plain text for encryption, which eliminates the necessity to use different encryption modes.

On the Adoption of Physically Unclonable Functions to Secure IIoT Devices

The growing convergence among information and operation technology worlds in modern Industrial Internet of Things (IIoT) systems is posing new security challenges, requiring the adoption of novel security mechanisms involving light architectures and protocols to cope with IIoT devices resource constraints. In this article, we investigate the adoption of physically unclonable functions (PUFs) in the IIoT context, and propose the design of a PUF-based architecture (Pseudo-PUF), obtained by suitably combining a weak PUF and an encryption module, that can be successfully adopted to implement advanced security primitives while meeting the existing requirements of IIoT devices in terms of cost and resource demand. To demonstrate the feasibility of our proposal, we analyzed the overall quality of different Pseudo-PUF instances with respect to well-known PUF quality metrics, and found that it is possible to obtain good results with a negligible impact on the devices, thus making our approach suited to IIoT deployments.