Random Keys 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.

Scenarios for Optical Encryption Using Quantum Keys

Optical communications providing huge capacity and low latency remain vulnerable to a range of attacks. In consequence, encryption at the optical layer is needed to ensure secure data transmission. In our previous work, we proposed LightPath SECurity (LPSec), a secure cryptographic solution for optical transmission that leverages stream ciphers and Diffie–Hellman (DH) key exchange for high-speed optical encryption. Still, LPSec faces limitations related to key generation and key distribution. To address these limitations, in this paper, we rely on Quantum Random Number Generators (QRNG) and Quantum Key Distribution (QKD) networks. Specifically, we focus on three meaningful scenarios: In Scenario A, the two optical transponders (Tp) involved in the optical transmission are within the security perimeter of the QKD network. In Scenario B, only one Tp is within the QKD network, so keys are retrieved from a QRNG and distributed using LPSec. Finally, Scenario C extends Scenario B by employing Post-Quantum Cryptography (PQC) by implementing a Key Encapsulation Mechanism (KEM) to secure key exchanges. The scenarios are analyzed based on their security, efficiency, and applicability, demonstrating the potential of quantum-enhanced LPSec to provide secure, low-latency encryption for current optical communications. The experimental assessment, conducted on the Madrid Quantum Infrastructure, validates the feasibility of the proposed solutions.

Enhance Key Stage Generation for Developing Kasumi Encryption Algorithm

Today, data security is a critical component of the efficient performance of every organization's diverse requirement, one of the important requirements is to provide a secure connection for data transmission in organization's networks. Cryptography algorithms are used to protect transmitted data from unauthorized access. Every day, a great deal of research is being done. The process of encrypting data is currently under development. Therefore, a substantial technological or research effort is still required. Cellular networks and secure communication. This proposal calls for the development of a new encryption system based on Using random keys in all the rounds. That’s mean we generated random keys as 128 bits for each round and save it in an array with size (8×8) because we have 8 rounds and each key divided into 8 sub keys as 16 bits for each to use in encryption and decryption. The developed random keys and traditional algorithm keys were tested with statistical tests of NIST, which made up a comparison and conclusion that the developed keys have a higher randomness specially in linear complexity, Frequency within block and random excursion tests, which leads to a better quality of encryption. Then we could test the cipher text with frequency within block test that was evaluated by (0.49590998713105255) and the approximate entropy test that was evaluated by (0.4922198616875501) for each cipher text which resulted from standard and modified Kasumi algorithm that’s means we can conclude that our modified Kasumi algorithm achieved more secure data in its resulted cipher text.

Color Image Encryption Model Based on 3-D Chaotic Logistic Map and JAYA Algorithm

In this research, we have proposed a color image encryption model based on a three-dimensional chaotic logistic map and the JAYA algorithm. The 3-D chaotic logistic map generates three random keys for the color image. Further, the JAYA algorithm is utilized to find the parameter values of a 3-D chaotic logistic map based on the objective function. The JAYA algorithm is chosen because no parameter tuning is required and it has a better convergence rate to find the best solution over others. After generating the random key, exclusive-OR, and pixel-level bits are shuffled to get the final encrypted image. With the typical collection of color images, the simulation assessment was performed. The outcome indicates that the distorted image is entirely noisy. In comparison to best-practice approaches described in the literature, the suggested model outperforms them in terms of entropy while demonstrating poor PSNR and CC.

Computational Competent & Random Key based Image Cryptography for Dynamic Network: A Literatutre Review

Computational Competent & Random Key based Image Cryptography for Dynamic Network: A Literatutre Review

Chaotic Map based Random Binary Key Sequence Generation

Chaotic Map based Random Binary Key Sequence Generation

TOPAS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf {TOPAS}$$\\end{document}2-pass key exchange with full perfect forward secrecy and optimal communication complexity

We present Transmission optimal protocol with active security (TOPAS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf {TOPAS}$$\\end{document}), the first key agreement protocol with optimal communication complexity (message size and number of rounds) that provides security against fully active adversaries. The size of the protocol messages and the computational costs to generate them are comparable to the basic Diffie-Hellman protocol over elliptic curves (which is well-known to only provide security against passive adversaries). Session keys are indistinguishable from random keys—even under reflection and key compromise impersonation attacks. What makes TOPAS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf {TOPAS}$$\\end{document}stand out is that it also features a security proof of full perfect forward secrecy (PFS), where the attacker can actively modify messages sent to or from the test-session. The proof of full PFS relies on two new extraction-based security assumptions. It is well-known that existing implicitly-authenticated 2-message protocols like HMQV\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf {HMQV}$$\\end{document}cannot achieve this strong form of (full) security against active attackers (Krawczyk, Crypto’05). This makes TOPAS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf {TOPAS}$$\\end{document}the first key agreement protocol with full security against active attackers that works in prime-order groups while having optimal message size. We also present a variant of our protocol, TOPAS+\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf {TOPAS+}$$\\end{document}, which, under the Strong Diffie-Hellman assumption, provides better computational efficiency in the key derivation phase. Finally, we present a third protocol termed FACTAS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf {FACTAS}$$\\end{document}(for factoring-based protocol with active security) which has the same strong security properties as TOPAS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf {TOPAS}$$\\end{document}and TOPAS+\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf {TOPAS+}$$\\end{document}but whose security is solely based on the factoring assumption in groups of composite order (except for the proof of full PFS).

Improvement the International Data Encryption Algorithm(IDEA)based on Chaos Theory

Background: The (IDEA), which represents International Data Encryption Algorithm is a widely used cipher algorithm that has raised concerns due to the discovery of numerous weak keys, as highlighted in previous research. These weak keys, specifically those containing consecutive sequences of single digits, have been found to impede the algorithm's evolution and result in a sluggish avalanche effect. To address these vulnerabilities, this research aims to develop an enhanced and secure encryption algorithm by incorporating Chaos Theory principles into IDEA. Materials and methods: The primary objective is to address the weaknesses associated with IDEA's key generation process by leveraging Chaos Theory to generate strong, highly random keys that replace the algorithm's weak keys t. The study also aims to assess the security and cryptographic strength of the enhanced IDEA algorithm through evaluations and comparisons with the original algorithm. Results: The results showed that the proposed key passed 11 tests out of the 15 total tests, while the Traditional key of IDEA passed only 7. This indicates that the proposed method is superior by 4 tests over the Traditional method of generating keys. Also, cipher text 1 with the proposed key passed 10 tests out of the 15 total tests, while with the Traditional key passed only 8 . Conclusion: This indicates the superiority of the proposed method of IDEA in encryption over the traditional method of IDEA.

Efficient Cyber Security Framework for IoT Using Machine Learning Algorithms

Through the network's infrastructure, the IoT can impart perception, recognition, and remote control to inanimate objects. Due to IoT's characteristics, it's possible to integrate the real world into a digital system, which improves precision, productivity, and bottom line. While traditional internet infrastructure comprises of highly capable computers and servers, IoT gadgets have limited processing power and storage space. The authentication and key agreement system SecureAuthKey is very lightweight. The suggested technique is meant to solve the security and privacy problems that plague modern constraint-based CPS programmes. A lightweight approach for authenticating cyber-physical objects is one of the expected outcomes. Adaptation and autonomy in cyber-physical systems need not be compromised by a lack of trust or security in users' data or the devices themselves, according to a new type of security algorithm. To provide flexibility and scalability, a new middleware module has been developed on the Raspberry platform to facilitate communication between CPS-based devices and services. Secure Internet of Things (IoT) evaluation methodology that may be used in a variety of contexts and is user-focused. With the suggested system, the two CPS units will be able to authenticate one another. When a network grows larger, the possibility of an attack rises. Therefore, the IoT network is much more susceptible to attacks than conventional networks. As the number of connected devices grows, so do the number of potential threats to their security. To protect the IoT ecosystem from current threats, cutting-edge technology is essential. The proposed approach must be very efficient and have low computational overheads. It creates random session keys to protect wireless transmissions. The system is protected from a variety of cyber threats. The current constraint-based CPS system requires a new lightweight security solution.

Hybrid watermarking and encryption techniques for securing three-dimensional information

A hybrid digital watermarking and encryption technique based on the Computer Generated Holography (CGH) and fractional Fourier transform (FRFT) combined with singular value decomposition (SVD) algorithm is proposed for securing three-dimensional (3D) information. Initially, hierarchical 3D information is encrypted using the angular spectrum diffraction method and a random phase key. This process yields a binary real valued CGH, where incorporating a random phase key broadens the key space and adds complexity, effectively scrambling and concealing the 3D information. Subsequently, the encrypted binary real valued CGH is embedded into the host image as a watermark using the FRFT-SVD algorithm. This hybrid approach enhances the security of the watermarking process. In the final step, the CGH watermark is extracted using the inverse operation of the embedding algorithm. Applying the correct optical key and angular spectrum inverse algorithm successfully reconstructs the 3D information. The watermark algorithm’s efficiency significantly improves by leveraging the rapid computational speed and high focusing capabilities of the FRFT. Additionally, integrating SVD enhances the image’s resistance to geometric attacks, thereby improving the algorithm’s invisibility and robustness. The proposed scheme effectively achieves the encryption and digital watermarking of 3D information. Simulation results substantiate the presented watermarking scheme’s efficacy and robustness.

Chaotic Encryption Scheme for Colour Image using 3D Lorenz Chaotic Map and 3D Chen System

Chaos-based image encryption system is an encryption method that uses chaotic systems in encrypting digital images for the purpose of enhancing security. Chaos theory exhibits some distinctive characteristics, which include butterfly-like patterns, unpredictable behavior, and sensitive dependence to initial conditions. . In the past few decades, image encryption based on a single chaotic map has been a common technique in encrypting images. However, there are still unauthorized interceptors who illegally access and obtain the private information of the image. With that being the case, an encryption method that applies more than one chaotic system will contribute to creating a more complex relationship between the original and encrypted images, making it challenging for unauthorized individuals to decipher or extract the original content of the image without the appropriate decryption key. In this study, two chaotic maps, 3D Lorenz Map and 3D Chen system, are applied to generate random cryptographic keys for encrypting color images using permutation and diffusion mechanisms. The proposed algorithm that employs two chaotic maps is proven to be an effective system that achieves excellent results in security.

Blockchain assisted blind signature algorithm with data integrity verification scheme

SummaryAs the demand for cloud storage systems increases, ensuring the security and integrity of cloud data becomes a challenge. Data uploaded to cloud systems are vulnerable to numerous sorts of assaults, which must be handled appropriately to avoid data tampering issues. In addition, quantum computers are expected to be introduced soon, which may face multiple security issues by destroying all traditional cryptosystems. This work introduces a quantum‐resistant blockchain centered data integrity verification system with the use of several techniques. Initially, the keys and signatures are generated by the users with the help of the lattice‐based blind signature algorithm (L_BSA), which is a combination of lattice cryptography and a blind signature algorithm. From the generated random keys, the most optimal key is then selected by the Puzzle Optimization Algorithm (POA), which is then made available to the encryption phase. Then, the upgraded Merkle tree‐assisted vacuum filter (Vac‐UMT) algorithm is executed to accomplish the encryption task. Then the data are converted into blocks using blockchain technology and uploaded to the cloud. When receiving the audit requests, the verification process is carried out, and the evidence report is generated for the users. The proposed work is simulated in JAVA and assessed with the UNSW‐NB15 dataset, and the outcomes demonstrated that the system is highly efficient and secure.

Performance enhancement of cloud security with migration algorithm for choosing virtual machines in cloud computing

The management of the hardware as well as software resources entrusted to third-party service suppliers have shown to be extraordinarily remarkable and accessible with Cloud Computing (CC), a potential computing technology for the future. Yet, a major undertaking is characterized by security as well as the use of Virtual Machines (VMs) to perform a request. The main issue with using technology is security worries, which raises the need for a strong security system to safeguard data on the cloud. Thus, to address this problem, a method called Weighted Mean-based Radial Basis Function Network with Advanced Encryption Standard (WMRBFN-AES) is developed to improve cloud security along with the time of execution. Random keys are produced utilizing the Pseudo Random Number Generator (PRNG) technique, and the best keys are created employing the WMRBFN technique. In the WMRBFN technique, randomly generated keys are used as input, and the hidden layers yield an estimate associated with the secret key of the input. The output layer generates the most precise secret keys to encrypt the data. Encryption is carried out using the AES algorithm. The files about the encrypted data are kept in a cloud storage system. Reduced execution times for stakeholder demands (tasks) as well as optimal cloud resource utilization result from the selection of VMs, which significantly improves reliability. The Migration Algorithm (MA) is used in the cloud framework to optimize the selection of VMs to improve resource utilization and performance. The experimental findings of the suggested framework and the state-of-the-art frameworks are compared, and it was found that the new model performed better in terms of cost, resource utilization, service latency, throughput, and execution time.

Encryption and Description of RGB Values in Images Using the Hill Chiper Algorithm

Information security related to computer use cannot be separated from cryptography. Hill cipher is an application of modulo arithmetic in cryptography. This cryptography technique uses a square matrix as the key used to carry out encryption and decryption. This cryptographic technique was created with the intention of being able to create ciphers (codes) that cannot be broken using frequency analysis techniques. Hill Cipher does not replace each of the same letters in the plaintext with other letters that are the same in the ciphertext because it uses matrix multiplication as a basis for encryption and decryption. Hill Cipher cryptography is a type of classic cryptography that uses a substitution method by providing random keys and the number is the same as the plaintext. The use of encryption and decryption using the Hill cipher algorithm is to help secure data so that it is not easily falsified or accessed by irresponsible people by changing the original image into a different form where the image is not easy to recognize. The encryption and decryption process was designed using the Java programming language using NetBeans 8.2 and the Hill Cipher algorithm to encrypt RGB digital images

Classifying World War II era ciphers with machine learning

We determine the accuracy with which machine learning and deep learning techniques can classify selected World War II era ciphers when only ciphertext is available. The specific ciphers considered are Enigma, M-209, Sigaba, Purple, and Typex. We experiment with three classic machine learning models, namely, Support Vector Machines (SVM), k-Nearest Neighbors (k-NN), and Random Forest (RF). We also experiment with four deep learning models: Multi-Layer Perceptrons (MLP), Long Short-Term Memory (LSTM), Extreme Learning Machines (ELM), and Convolutional Neural Networks (CNN). Each model is trained on features consisting of histograms, digrams, and raw ciphertext letter sequences. Furthermore, the classification problem is considered under four distinct scenarios: Fixed plaintext with fixed keys, random plaintext with fixed keys, fixed plaintext with random keys, and random plaintext with random keys. Under the most realistic scenario, given 1,000 characters per ciphertext, we are able to distinguish the ciphers with more than 97% accuracy. In addition, we consider the accuracy of a subset of the learning techniques as a function of the ciphertext length. We find that classic learning models outperform the deep learning models that we tested, and ciphers that are more similar in design are somewhat more challenging to distinguish.

Discrete Spectral Encryption of Single-Carrier Signals With Pseudo Random Dynamic Keys

Discrete Spectral Encryption of Single-Carrier Signals With Pseudo Random Dynamic Keys

Combining Riemann–Lebesgue-Based Key Generator and Machine-Learning-Based Intelligent Encryption Scheme for IoMT Images Infosecurity

Imaging examinations, such as chest X-ray (CXR) images, can be used for early detection of diseases inside the human body, such as lung cancer, and cardiopulmonary-related diseases; however, they may contain patients’ private information, which raises concerns about the security levels of medical images in internet of medical things (IoMT) systems. The promising authorization protocol algorithm in 5th-generation networking technology can protect medical image confidentiality, recoverability, and availability. Hence, we propose a symmetric cryptography protocol based on the Riemann-Lebesgue (R-L) -based key generator and a machine learning (ML)-based cryptography scheme for CXR image infosecurity. The R-L-based key generator uses the composite function“, g(x)sin((1/2+N)x)”, to dynamically produce the oscillation function by controlling the terms of the nonlinear function“, g(x)”, and frequency“, N”, which are used to produce the randomnumber seed and to select non-ordered numbers and nonrepeated 256 secret keys in the key space. The ML-based scheme uses these random secret keys to train an image encryptor and decryptor, respectively. Based on the diffusion method, the ML-based cryptography scheme is used to change image pixel values. For evaluation experiments, CXR images are collected from the National Institutes of Health Chest X-ray database and used to evaluate image quality after encryption and decryption processes. For different cardiopulmonary-related disease images, the number of pixel change rates (NPCR) and unified averaged changed intensity (UACI) are used to evaluate the security level and decryption quality. The experimental results show an average NPCR of 99.6% and average UACI of 32.61% between plain and cipher images for evaluating the security level, enabling further online diagnosis applications in IoMT systems.

Intelligent Logistics Management System Based On Improved AES Algorithm

With the rapid development of China's economy and information technology, the Internet has penetrated into People's Daily life, especially with the rise of mobile e-commerce, online shopping has become a convenient, fast, cost-effective consumption mode. However, this convenience also brings challenges to the logistics industry, mainly in terms of user privacy and logistics efficiency. In order to solve these challenges, an intelligent logistics management system based on improved AES algorithm is designed to improve the quality and efficiency of logistics services. The system includes a new logistics management system and a pick-up verification APP. By using AES algorithm to encrypt order information, generate order QR code, and realize goods tracking, the system effectively protects user privacy and improves the efficiency of logistics services. In order to enhance the security, this research also combines the chaotic system to generate random keys and encrypts the order information with AES algorithm, which fundamentally solves the security problem of AES algorithm. The new logistics management system has greatly improved the logistics efficiency and reduced the logistics cost by automatically generating the pick-up number and sending the pick-up short message using the instant communication technology. The pick-up verification APP further strengthens the security and timeliness of pick-up, and provides practical significance for the development of logistics enterprises. These research results have important implications for promoting the development of intelligent logistics management system, and provide new ideas and inspirations for the research and application of related fields.

Optimizing Automated Manufacturing Processes Using a Hybrid BRKGA Algorithm: A Case Study on Flexible Job-Shop Scheduling

In the modern era, industrial automation ofers significant competitive advantages. Replacing human labor with robots allows processes to be carried out much faster and more efficiently, with lower waste rates and the possibility of scheduling production 24/7. However, this also presents new challenges and opportunities in optimizing these automated processes. This paper proposes a hybrid algorithm BRKGA (Biased Random Key Genetic Algorithm) to optimize fexible job shop scheduling (FJSSP) problems in automated manufacturing systems. The algorithm is applied to a real-world case study in the Cinvestav Intelligent Manufacturing Laboratory, seeking to optimize the production of a four-piece product. The results demonstrate that the proposed algorithm outperforms previous results in terms of both, solution quality and computational efficiency.

Integrated Shared Random Key Agreement Protocol for Wireless Sensor Network

The secured data transmission in Wireless Sensor Network (WSN) relies on effective key generation and secured sharing. The generated key must be random to enhance data confidentiality. The processes associated with the security in WSN must be designed at reduced computing time and communication cost. Our research work aims to design a novel lightweight key-sharing protocol that is needed for ensuring data confidentiality. The protocol must meet the constraints of WSN by being lightweight and consuming less energy. Security breaches in WSNs occur due to insecure keys. This can be overcome by generating shared keys which are generated once using the dynamic features of Sensor Nodes (SNs) when the Cluster Heads (CHs) are selected. In this research work, we have generated the Master Shared Key (MSK) at the transmitter node by forming a Galois Ring (GR) using WSN parameters and derived the Shared Random Key (SRK) using matched positions of exchanged Random Sequences (RSs). It is protected using a Physically Unclonable Function (PUF). The novelty lies in the SRK generation from MSK which is chosen at random from the polynomials generated during the formation of GR. The MSK is securely shared with the receiver node by encrypting using a Preloaded Key (PK). After this exchange, the key for encryption and decryption is derived by the transmitter and the receiver by exchanging RSs. The SRK is then encrypted using a key which is a unique fingerprint of the SN generated using PUF and stored in the SNs and the CHs to prevent node capture attack that occurs in WSN. Our proposed Shared Random Key Agreement Protocol (SRKAP) is comparable to the Localized Encryption and Authentication Protocol (LEAP) and performs better compared to the Elliptic Curve Diffie Hellman (ECDH) algorithm