Encryption Key Generation Research Articles

Implementation of Chaotic Neural Key Generation Algorithm For IoT Devices

This paper presents a new method for generating encryption keys for Internet of Things (IoT) devices. This method combines chaos theory with neural networks to create secure and efficient keys. We use the Lorenz chaotic system to generate complex patterns and a Convolutional Neural Network (CNN) to learn and predict these patterns. This approach is designed to address the unique security challenges of IoT devices, which often have limited computing power. We tested our method with different key sizes and evaluated its performance using accuracy, loss, entropy, and correlation metrics. The results show that key sizes between 256 and 512 bits offer the best balance between model performance and security for IoT devices. We also conducted Diehard statistical tests, which our key generation method passed successfully, demonstrating its ability to produce high-quality random keys.

Stochastic switching and analog-state programmable memristor and its utilization for homomorphic encryption hardware

Homomorphic encryption performs computations on encrypted data without decrypting, thereby eliminating security issues during the data communication between clouds and edges. As a result, there is a growing need for homomorphic encryption hardware (HE-HW) for the edges, where low power consumption and a compact form factor are desired. Here, a Pt/Ta2O5/Mo metallic cluster-type memristors (Mo-MCM) characterized by the Mo as a mobile species, and its utilization for the HE-HW via a 1-trasistor-1-memristor (1T1M) array as a prototype HE-HW is proposed. The Mo-MCM exhibits inherent stochastic set-switching behavior, which can be utilized for generating the random numbers required for encryption key generation. Furthermore, the device can accurately store analog conductance states after set-switching, which can be used as an analog non-volatile memristor. By simultaneously leveraging these two characteristics, encryption key generation, data encryption, and decryption are possible within a single device through an in-memory computing manner.

Blockchain-Enabled Secure Data Sharing with Honey Encryption and DSNN-Based Key Generation

Ensuring data confidentiality is a critical requirement for modern security systems globally. Despite the implementation of various access-control policies to enhance system security, significant threats persist due to insecure and inadequate access management. To address this, Multi-Party Authorization (MPA) systems employ multiple authorities for authorization and authentication, utilizing blockchain technology to store and access data securely, ensuring immutable and trusted audit trails. In this work, we propose a hybrid key-generation approach called the Identity and Attribute-Based Honey Encryption (IABHE) Algorithm combined with Deep Spiking Neural Network (DSNN) denoted by IABHE+DSNN for secure data sharing in a multi-party blockchain-based system. This approach incorporates various entities and multiple security functionalities to ensure data security. The data-sharing process involves several steps: initialization, authentication, initial registration, data protection, validation, and data sharing. Data protection is executed within the MapReduce framework, with data encryption performed using IABHE and key generation managed by DSNN. Experimental results demonstrate that the proposed IABHE+DSNN approach achieves a decryption time of 10.786 s, an encryption time of 15.765 s, and a key complexity of 0.887, outperforming existing methods.

Blood-inspired random bit generation using microfluidics system

The development of random number generators (RNGs) using speckle patterns is pivotal for secure encryption key generation, drawing from the recent statistical properties identified in speckle-based imaging. Speckle-based RNG systems generate a sequence of random numbers through the unpredictable and reproducible nature of speckle patterns, ensuring a source of randomness that is independent of algorithms. However, to guarantee their effectiveness and reliability, these systems demand a meticulous and rigorous approach. In this study, we present a blood-inspired RNG system with a microfluidics device, designed to generate random numbers at a rate of 5.5 MHz and a high-speed of 1250 fps. This process is achieved by directing a laser beam through a volumetric scattering medium to procure speckle patterns. Additionally, designed microfluidic device requires only a minimal blood sample of 5 µl to capture these speckle patterns effectively. After implementing the two-pass tuple-output von Neumann debiasing algorithm to counteract statistical biases, we utilized the randomness statistical test suite from the National Institute of Standards and Technology for validation. The generated numbers successfully passed these tests, ensuring their randomness and unpredictability. Our blood-inspired RNG, utilizing whole blood, offers a pathway for affordable, high-output applications in fields like encryption, computer security, and data protection.

Encryption using True Random Number

In moment's connected digital geography, data security and sequestration have come consummate enterprises. Traditional encryption ways frequently calculate on mock arbitrary number creators (PRNGs) to induce encryption keys, which are deterministic and vulnerable to attacks. This design proposes a new approach to enhance data encryption by exercising true arbitrary number creators (TRNGs) for generating encryption keys. In this work, a secure optic ultrafast arbitrary number creator grounded on arbitrary ray gamut’s was demonstrated. Unlike the usual system of recording ray intensity over time, the arbitrary ray diapason under each pump palpitation was recorded and converted into arbitrary figures through post-processing. Approaches in three different confines — space, diapason and time were used to increase the rate of arbitrary number generation. The randomness of performing arbitrary bit aqueducts was vindicated by the NIST statistics tests

The key security management scheme of cloud storage based on blockchain and digital twins

As a secure distributed ledger technology, blockchain has attracted widespread attention from academia and industry for its decentralization, immutability, and traceability characteristics. This paper proposes a cloud storage key security management scheme based on blockchain. To resist brute-force attacks launched by adversaries on ciphertexts, the scheme uses an oblivious pseudo-random function (OPRF) to generate randomized convergent keys and improve data confidentiality. Second, the scheme enhances the reliability of concurrent key management through a secret sharing mechanism, where convergent keys are split into key fragments and distributed on blockchain for storage. Even if a certain number of key fragments are lost or damaged, users can still recover complete key information through block transaction records. In addition, the scheme effectively supports file-level and block-level data security deduplication. Security analysis and experimental performance evaluation indicate that this scheme can ensure the security of keys and the confidentiality of data, and it has a low computational overhead for generating file-level encryption keys under this scheme. Even for a 100 MB file, the computational overhead required for generating encryption keys is less than 2 s, which improves computational efficiency.

A novel compression-based 2D-chaotic sine map for enhancing privacy and security of biometric identification systems

Human biometric images are utilized for cell phone authentication, airport security, and biometric passports. To improve the biometric identification process, this should be protected from cyber attackers because it is sensitive to any minor changes. Thus, security is a major concern in biometric images. Traditional encryption and compression methods are ineffective for encrypting biometric images due to their high execution time and algorithm complexity. In this paper, a novel 2D chaotic sine map is proposed for generating encryption keys and improving security for biometric identification systems. The proposed scheme uses the 2D chaotic map to generate the private key and diffusion process. Here, the Hénon-Sine Map (HSM-512), Secure Hash Algorithm (SHA-256), and DNA computing are also used in the key generation process. The pixel values of the original images in the proposed schemes are shuffled using Mersenne Twister (MT) to improve the security of biometric images. Moreover, the Differential Huffman Compression (DHC) method is used for lossless compression while performing the XOR-based encryption process. The proposed model has been tested on different RGB biometric images, namely the SOCOFing dataset and the COVID-19 chest X-ray dataset. The experiment results have been evaluated using many performance metrics, such as entropy, key space, histogram analysis, key sensitivity, robustness analysis, correlation, and similarity analysis. The outcomes demonstrate that the proposed scheme is more effective than the state-of-the-art schemes.

Research on abnormal access control of database management system under cloud computing platform

Abstract Access control is a security technique that can restrict access to protected resources, and data to only authorized users. In this paper, we design a blockchain-based access control scheme for cloud storage that is enabled by revocation. First, initialize blockchain to generate global parameters, generate complete user encryption keys and decryption keys, and perform data encryption. When the blockchain receives a user’s access request, the authorization contract determines if it is on the revocation list. If not, the key is checked. Then, it determines abnormal access and adds its identity to the revocation list, preventing further access to the database. The access control model is created by combining attribute-based encryption. After the security analysis and operational efficiency test, it can be considered that the model meets the security features, such as IND-CPA security. Regarding the time overhead of generating encryption keys, the computational overhead of this paper is the lowest, and the time required to generate encryption keys for 10 attributes is only 0.09 seconds, and for 100 attributes is only 1.62 seconds, which is better than the performance of the two attribute-based access control schemes, FIFC and AACE. The user access time overhead for 10 to 100 attributes at user encryption time is 1.38, 1.56, 1.98, 2.1, 2.53, 2.76, 3.03, 3.27, 3.66, and 3.94 seconds, respectively. The lowest decryption time consumed ensures data security and a good access experience. This study achieves fine-grained access control while protecting data privacy.

Key dependent information confidentiality scheme based on deoxyribonucleic acid (DNA) and circular shifting

In this era of advanced information technology, the exploration and development of novel mechanisms to ensure information confidentiality have consistently captivated the attention of upcoming researchers. In this article, we present a pioneering approach that combines DNA sequencing with a four-dimensional (4D) hyperchaotic map to bolster the security of digital information. Our primary focus is on the design of a robust and secure scheme for encrypting color images, leveraging DNA cryptography and hyperchaos. By extracting three distinct DNA sequences, we generate encryption keys through the integration of DNA computing and 4D hyperchaotic maps. Notably, these keys are intricately linked to the plaintext and vary with any alterations in the input. Consequently, the proposed encryption method stands resilient against an array of potential cryptographic attacks. To gauge the algorithm's security, we subject it to rigorous standard statistical analysis. Our findings underscore the efficiency and robustness of the proposed framework, establishing its potential for facilitating secure communication.

Analysis of outage performance in a 6G‐V2X communications system utilising free‐space optical quantum key distribution

AbstractQuantum‐based technologies will provide system engineers with new capabilities for securing data communications. The UK AirQKD project has implemented a Free‐Space Optical Quantum Key Distribution (QKD) system to enable the continuous generation of symmetric encryption keys. One of the use cases for the generated keys is to secure Vehicle‐to‐Everything (V2X) communications. V2X applications would benefit from the certificate‐free security provided by QKD for a post‐quantum society. How FSO‐QKD could integrate into a V2X architecture is examined. An overview of V2X is provided with the role that FSO‐QKD could secure V2X data though some obstacles exist. One of the issues with 6G communications is the potential line‐of‐sight (LOS) considerations between the V2X devices. The modelling required for LOS is examined to analyse the outage performance of the building to infrastructure links in the 6G architecture. The results from the model show that further work is required if 6G LOS communications are going to be relied upon for future safety‐critical V2X applications.

Physical Layer Key Generation Scheme for MIMO System Based on Feature Fusion Autoencoder

Recently, the use of wireless channel state information (CSI) to generate encryption keys in the physical layer has gained significant attention from researchers. Unlike classical cryptography, this approach relies on the variability of the wireless channel, channel reciprocity, and spatial decorrelation to ensure security, making it more lightweight and providing strong randomness. This paper proposes a physical layer key generation scheme for wireless LAN MIMO systems based on feature fusion autoencoder (FFAEncoder) to address the issue of a high key disagreement rate (KDR). Our approach involves extracting amplitude and phase features separately, fusing them through multiplication operator in a neural network, and using an autoencoder to extract common features. The proposed scheme was evaluated on multiple datasets in different real-world scenarios, and it was found that the transmitter and receiver codeword’s mean squared error (MSE) and mean absolute error (MAE) were smaller than those of the current models, indicating better key generation performance. Additionally, the proposed scheme’s KDR was smaller, with a decay rate faster than that of the other two models in the same environment, and the primary key bits were 1/2 and 1/3 that of the other models, respectively, as the signal-to-noise ratio (SNR) increased.

Enhanced Security for Large-Scale 6G Cloud Computing: A Novel Approach to Identity based Encryption Key Generation

Cloud computing and 6G networks are in high demand at present due to their appealing features as well as the security of data stored in the cloud. There are various challenging methods that are computationally complicated that can be used in cloud security. Identity-based encryption (IBE) is the most widely used techniques for protecting data transmitted over the cloud. To prevent a malicious attack, it is an access policy that restricts access to legible data to only authorized users. The four stages of IBE are setup, key extraction or generation, decryption and encryption. Key generation is a necessary and time-consuming phase in the creation of a security key. The creation of uncrackable and non-derivable secure keys is a difficult computational and decisional task. In order to prevent user identities from being leaked, even if an opponent or attacker manages to encrypted material or to decode the key this study presents an advanced identity-based encryption technique with an equality test. The results of the experiments demonstrate that the proposed algorithm encrypts and decrypts data faster than the efficient selective-ID secure IBE strategy, a competitive approach. The proposed method's ability to conceal the identity of the user by utilizing the Lagrange coefficient, which is constituted of a polynomial interpolation function, is one of its most significant aspects.

Spectral sensitivity near exceptional points as a resource for hardware encryption

The spectral sensitivity near exceptional points (EPs) has been recently explored as an avenue for building sensors with enhanced sensitivity. However, to date, it is not clear whether this class of sensors does indeed outperform traditional sensors in terms of signal-to-noise ratio. In this work, we investigate the spectral sensitivity associated with EPs under a different lens and propose to utilize it as a resource for hardware security. In particular, we introduce a physically unclonable function (PUF) based on analogue electronic circuits that benefit from the drastic eigenvalues bifurcation near a divergent exceptional point to enhance the stochastic entropy caused by inherent parameter fluctuations in electronic components. This in turn results in a perfect entropy source for the generation of encryption keys encoded in analog electrical signals. This lightweight and robust analog-PUF structure may lead to a variety of unforeseen securities and anti-counterfeiting applications in radio-frequency fingerprinting and wireless communications.

Hybrid cloud storage system with enhanced multilayer cryptosystem for secure deduplication in cloud

Data deduplication is a crucial technique in the field of data compression that aims to eliminate redundant copies of recurring data. This technique has gained significant popularity in the realm of cloud storage due to its ability to effectively reduce storage requirements and optimize bandwidth utilization. To ensure the safeguarding of sensitive data while simultaneously facilitating deduplication, researchers have put forth the concept of convergent encryption as a potential solution. This technique involves encrypting the data prior to its outsourcing, thereby enhancing the confidentiality of the information. In this work, an earnest endeavor is undertaken to formally tackle the issue of authorized data deduplication, with the aim of enhancing data security. Our approach combines the Diffie-Hellman algorithm and symmetrical external decision to protect and popularize information, ensuring end-to-end encryption to encourage user adoption of cloud storage. The proposed model employs block-level deduplication and guarantees the randomness of ciphertexts by generating encryption keys using the Diffie-Hellman algorithm. This method effectively counters both internal and external brute-force attacks, enhancing data security while reducing computational costs. An extensive experimentation is carried out to demonstrate that our approach is particularly beneficial in scenarios with multiple privilege sets. Overall, the proposed model offers an elaborate framework that maintains data privacy and strengthens security measures, contributing to a more efficient and secure cloud-based document search.

Remote Sensing Image Encryption Using Optimal Key Generation-Based Chaotic Encryption

The Internet of Things (IoT) offers a new era of connectivity, which goes beyond laptops and smart connected devices for connected vehicles, smart homes, smart cities, and connected healthcare. The massive quantity of data gathered from numerous IoT devices poses security and privacy concerns for users. With the increasing use of multimedia in communications, the content security of remote-sensing images attracted much attention in academia and industry. Image encryption is important for securing remote sensing images in the IoT environment. Recently, researchers have introduced plenty of algorithms for encrypting images. This study introduces an Improved Sine Cosine Algorithm with Chaotic Encryption based Remote Sensing Image Encryption (ISCACE-RSI) technique in IoT Environment. The proposed model follows a three-stage process, namely pre-processing, encryption, and optimal key generation. The remote sensing images were preprocessed at the initial stage to enhance the image quality. Next, the ISCACE-RSI technique exploits the double-layer remote sensing image encryption (DLRSIE) algorithm for encrypting the images. The DLRSIE methodology incorporates the design of Chaotic Maps and deoxyribonucleic acid (DNA) Strand Displacement (DNASD) approach. The chaotic map is employed for generating pseudorandom sequences and implementing routine scrambling and diffusion processes on the plaintext images. Then, the study presents three DNASD-related encryption rules based on the variety of DNASD, and those rules are applied for encrypting the images at the DNA sequence level. For an optimal key generation of the DLRSIE technique, the ISCA is applied with an objective function of the maximization of peak signal to noise ratio (PSNR). To examine the performance of the ISCACE-RSI model, a detailed set of simulations were conducted. The comparative study reported the better performance of the ISCACE-RSI model over other existing approaches.

Time-Based Steganography Image with Dynamic Encryption Key Generation

The rapid advancement of technology has necessitated stronger protection measures for data exchange. Encryption, coupled with robust keys, is an effective method to safeguard sensitive information. This study aims to improve the security of key levels by implementing a combination of steganography and encryption. The approach involves using two keys, one in the form of a normal string and the other based on the insertion time. These keys are combined to create a new, stronger encryption key. The secret messages are then encrypted using this new key and inserted using the Least Significant Bit method in steganography. This integrated approach aims to provide a higher level of protection for data during transmission and storage.

Testing of the Random Codes Generator of Embedded Crypto Protection System

The goal of the publication is to test the random codes generator of the built-in crypto-protection system Following the list of critical technologies in the production of weapons field and military equipment (following the Decree of the Cabinet of Ministers of Ukraine dated 30.08.2017 No. 600-r), an embedded microcontroller system for the protection of information for on-board equipment has been developed. A valuable stage of the system introduction is its research and testing. One of the stages of testing is the verification of the generator of random codes to use for the generation of encryption keys and digital signatures. Based on the previous works and research of the Kalyna algorithm, methods and tools for creating a random code generator have been studied to use in the built-in cryptographic data protection system for data encryption/decryption and for working with a digital signature. Means of checking generated random codes and comparing them with existing counterparts have been developed. The purpose of this article is to check the generator of random codes before using it in the built-in information protection system.

Вдосконалення методів генерації ключів шифрування за допомогою дивних атракторів

The urgency of the work is determined by the need to transfer confidential information through open communication channels. Such information can be of two types: symmetric encryption keys and directly informational messages that are encrypted with encryption keys. The article deals with the problem of improving the transmission of closed information over open channels using the Diffie- Hellman algorithm. The improvement is due to the introduction of a new type of one-sided function based on the numerical solution of the system of ordinary differential equations describing the dynamics of the phase coordinate movement of the strange attractor. For this purpose, the classic Diffie-Hellman algorithm based on the one-sided function of the discrete logarithm was considered. The required properties of one-sided functions in the general case were considered. Next, the peculiarities of algorithm modification in the case of transition to a one-sided function based on the use of a strange attractor were considered. It is assumed that at the beginning of the operation of the modified algorithm, through a secret channel, the exchange parties (agents) exchange information regarding the properties of the strange attractor to be used, namely, the definition of the differential equations describing the dynamics of a strange attractor, the values of the parameters of the equations, the initial integration conditions and the integration step (for methods with a constant step of integration). After that, all exchanges are conducted exclusively through open channels. The paper also considers the case of information exchange between more than two agents, in particular, the approach of hiding the number of agents participating in the exchange. Approbation of the method is carried out and intermediate and final results of the one-sided function based on strange attractors are given. Possibilities regarding partial disclosure by agents of certain parameters of the use of one-way functions are discussed. But at the same time, the safety of revealing such information is justified in the general case (both in the classical and in the modified Diffie-Hellman method). It was determined that depending on the needs of users, the complexity of the encryption keys can be increased by changing the initial parameters of the attractor, which will also allow controlling speed of key generation and encryption in general. The software that implements the proposed modified algorithm is implemented in three programming languages, C#, Python, and MatLab. This made it possible to perform a comparative analysis of the results and consciously choose the programming language of individual parts of the software to optimize the encryption key generation process for specific conditions.

Intelligent Bio-Latticed Cryptography: A Quantum-Proof Efficient Proposal

The emergence of the Internet of Things (IoT) and the tactile internet presents high-quality connectivity strengthened by next-generation networking to cover a vast array of smart systems. Quantum computing is another powerful enabler of the next technological revolution, which will improve the world tremendously, and it will continue to grow to cover an extensive array of important functions, in addition to it receiving recently great interest in the scientific scene. Because quantum computers have the potential to overcome various issues related to traditional computing, major worldwide technical corporations are investing competitively in them. However, along with its novel potential, quantum computing is introducing threats to cybersecurity algorithms, as quantum computers are able to decipher many complex mathematical problems that classical computers cannot. This research paper proposes a robust and performance-effective lattice-driven cryptosystem in the context of face recognition that provides lightweight intelligent bio-latticed cryptography, which will aid in overcoming the cybersecurity challenges of smart world applications in the pre- and post-quantum era and with sixth-generation (6G) networks. Since facial features are symmetrically used to generate encryption keys on the fly without sending or storing private data, our proposal has the valuable attribute of dramatically combining symmetric and asymmetric cryptography operations in the proposed cryptosystem. Implementation-based evaluation results prove that the proposed protocol maintains high-performance in the context of delay, energy consumption, throughput and stability on cellular network topology in classical Narrowband-Internet of Things (NB-IoT) mode.

ElGamal algorithm with hyperchaotic sequence to enhance security of cloud data

PurposeIn the cloud-computing environment, privacy preservation and enabling security to the cloud data is a crucial and demanding task. In both the commercial and academic world, the privacy of important and sensitive data needs to be safeguarded from unauthorized users to improve its security. Therefore, several key generations, encryption and decryption algorithms are developed for data privacy preservation in the cloud environment. Still, the outsourced data remains with the problems like minimum data security, time consumption and increased computational complexity. The purpose of this research study is to develop an effective cryptosystem algorithm to secure the outsourced data with minimum computational complexity.Design/methodology/approachA new cryptosystem algorithm is proposed in this paper to address the above-mentioned concerns. The introduced cryptosystem algorithm has combined the ElGamal algorithm and hyperchaotic sequence, which effectively encrypts the outsourced data and diminishes the computational complexity of the system.FindingsIn the resulting section, the proposed improved ElGamal cryptosystem (IEC) algorithm performance is validated using the performance metrics like encryption time, execution time, decryption time and key generation comparison time. The IEC algorithm approximately reduced 0.08–1.786 ms of encryption and decryption time compared to the existing model: secure data deletion and verification.Originality/valueThe IEC algorithm significantly enhances the data security in cloud environments by increasing the power of key pairs. In this manuscript, the conventional ElGamal algorithm is integrated with the pseudorandom sequences for a pseudorandom key generation for improving the outsourced cloud data security.