Symmetric Key Research Articles

IMPLEMENTATION OF THE SYMMETRIC CRYPTOGRAPHIC ALGORITHMS RC2 AND TRIPLE DES IN ECB MODE USING CRYPTOGRAPHIC SOFTWARE PROGRAM CRYPTOOL

This paper presents an in-depth analysis of symmetric key cryptographic algorithms, focusing on RC2 and Triple DES (ECB) as implemented in CrypTool. It is widely used educational software that demonstrates various cryptographic algorithms and methods. This paper aims to provide a foundational understanding of CrypTool, explain the functionalities of RC2 and Triple DES in Electronic Codebook (ECB) mode and evaluate their performance and security.

Encryption with Complex Variable and its Capabilities

Abstract. Cybersecurity is instrumental to the modern world. The most effective protection of data online is cryptography and encryption. There are two main types: symmetric and asymmetric. They employ important mathematical concepts to encode vital information. Nevertheless, the encryption field remains largely within the world of real numbers. This paper analyzes an encryption method presented by George Stergiopoulos et al. utilizing complex numbers and investigates its possible usage. The process involves investigating the necessary complex variable applications and a comparative scoring system which provides vital outlook on the promise of this new methodology. Subsequently, the investigation of the time complexity, security and encryption speeds provides a vital outlook on the practical uses in society. The results are promising feasibility of this new algorithm and the encouragement of further investigation into complex variable applications that encrypt with a more substantial range than any operation in the real numbers. Thus, the explicit novel insightful comparison of both symmetric and asymmetric encryption systems to the proposed complex encryption shows vital promise and further interest in investigation into this field as it opens the possibilities to an infinite array of novel complex operations that were previously inaccessible due to the restraint of real numbers.

Improving Data Security in Cloud Computing through the Implementation of a Hybrid Encryption Algorithm

As cloud computing continues to gain popularity, the security of sensitive data stored in the cloud remains a paramount concern for organizations and individuals alike. Traditional encryption methods, while effective, often struggle to balance security, efficiency, and usability. This paper presents a hybrid encryption algorithm that combines the strengths of symmetric and asymmetric encryption to enhance data security in cloud computing environments. The proposed hybrid approach leverages symmetric encryption for fast and efficient data encryption, while asymmetric encryption is utilized for secure key exchange. By implementing this dual-layer encryption strategy, we can significantly improve data confidentiality and integrity during transmission and storage. Additionally, the algorithm incorporates robust key management practices, ensuring that encryption keys are safeguarded against unauthorized access. Through a series of performance evaluations and security assessments, we demonstrate that our hybrid encryption algorithm not only provides superior security but also maintains acceptable levels of performance, making it suitable for real-time applications. The results indicate that this approach effectively mitigates risks associated with data breaches and unauthorized access, positioning it as a viable solution for enhancing data security in cloud computing. This research contributes to the ongoing discourse on cloud security, offering a practical framework for organizations to protect their sensitive information in increasingly complex digital landscapes.

A secure and privacy preserving model for healthcare applications based on blockchain-layered architecture

Blockchain is one of the emerging technologies that are applied in various fields and its application in Healthcare 4.0 is crucial to handle the vast amount of health records that are growing continuously everyday. This paper explores the application of blockchain technology-based layered architecture integrated with Interplanetary File System (IPFS) storage to provide a secure and robust sharing platform for healthcare system. A multilayer security is provided in the proposed system including a 128-bit Random Deoxyribonucleic Acid (DNA) encoding sequence with a modified version of the 128-bit Advanced Encryption Standard (AES) key expansion symmetric key technique is being used before storing the records in the IPFS storage, Rivest–Shamir–Adleman (RSA) 2048 digital envelope is used for secure transmission of symmetric keys, RSA 1024 is used for digital signature, and Secure Hash Algorithm 256-bit (SHA-256) is used for hashing the record files. Comparative analysis with existing state-of-the-art in blockchain-based E-healthcare system is discussed. The performance of various assessment metrics is evaluated, including encryption and decryption time for EHR records, mining time, record retrieval time, smart contract execution time and network latency. Additionally, a reputation-based filtering mechanism specifically designed in the proposed model to detect and mitigate the various attacks.

Enhanced Data Security Using 5x5 Hill Cipher with Modular 53

This research presents an optimized approach to the Hill Cipher encryption and decryption algorithm using a 5x5 matrix and modular 53 arithmetic. The traditional Hill Cipher, a well-known symmetric key algorithm, typically utilizes smaller matrices and modular arithmetic, which may not provide sufficient security for contemporary applications. By expanding the key matrix to a 5x5 structure and adopting a larger modulus of 53, the complexity and security of the cipher are significantly enhanced. The study details the methodology for constructing and implementing the 5x5 key matrix, as well as the processes for encryption and decryption under the modular 53 system. The computational efficiency and security improvements achieved through this optimization are analyzed. Comparative assessments with the conventional Hill Cipher demonstrate that the enhanced approach offers superior resistance against cryptographic attacks while maintaining manageable computational requirements. The results of this research indicate that the proposed optimized Hill Cipher can serve as a robust encryption method suitable for securing sensitive data in various modern applications. This study contributes to the field of cryptography by providing a more secure and efficient variant of the classical Hill Cipher algorithm

A Comprehensive Review of MI-HFE and IPHFE Cryptosystems: Advances in Internal Perturbations for Post-Quantum Security

The RSA cryptosystem has been a cornerstone of modern public key infrastructure; however, recent advancements in quantum computing and theoretical mathematics pose significant risks to its security. The advent of fully operational quantum computers could enable the execution of Shor’s algorithm, which efficiently factors large integers and undermines the security of RSA and other cryptographic systems reliant on discrete logarithms. While Grover’s algorithm presents a comparatively lesser threat to symmetric encryption, it still accelerates key search processes, creating potential vulnerabilities. In light of these challenges, there has been an intensified focus on developing quantum-resistant cryptography. Current research is exploring cryptographic techniques based on error-correcting codes, lattice structures, and multivariate public key systems, all of which leverage the complexity of NP-hard problems, such as solving multivariate quadratic equations, to ensure security in a post-quantum landscape. This paper reviews the latest advancements in quantum-resistant encryption methods, with particular attention to the development of robust trapdoor functions. It also provides a detailed analysis of prominent multivariate cryptosystems, including the Matsumoto–Imai, Oil and Vinegar, and Polly Cracker schemes, alongside recent progress in lattice-based systems such as Kyber and Crystals-DILITHIUM, which are currently under evaluation by NIST for potential standardization. As the capabilities of quantum computing continue to expand, the need for innovative cryptographic solutions to secure digital communications becomes increasingly critical.

Loss tolerance quantum key distribution based on the signal extraction model and advantage distillation technology

Compared with traditional networks, quantum key distribution (QKD) offers the ultimate resources, allowing two remote users to share secret symmetric keys regardless of the capabilities of eavesdroppers. However, the widespread application of commercial QKD is still challenging due to the low photon detection efficiency and the extremely high transmission loss. Here we demonstrate a fully commercial phase-encoding QKD system using a signal extraction model and advantage distillation technology to suppress detector noise and perform real-time pre-error correction. 1.89 × 10−10 in the asymptotic case and 7.43 × 10−12 in the nonasymptotic case secret key bits per pulse are achieved with a total loss of 70.05 dB. This method not only increases the transmission loss tolerance but also provides a more realistic deployment of quantum communication.

Design and Performance Evaluation of an Authentic End-to-End Communication Model on Large-Scale Hybrid IPv4-IPv6 Virtual Networks to Detect MITM Attacks

After the end of IPv4 addresses, the Internet is moving towards IPv6 address architecture quickly with the support of virtualization techniques worldwide. IPv4 and IPv6 protocols will co-exist long during the changeover process. Some attacks, such as MITM attacks, do not discriminate by appearance and affect IPv4 and IPv6 address architectures. In an MITM attack, the attacker secretly captures the data, masquerades as the original sender, and sends it toward the receiver. The receiver replies to the attacker because the receiver does not authenticate the source. Therefore, the authentication between two parties is compromised due to an MITM attack. The existing authentication schemes adopt complicated mathematical procedures. Therefore, the existing schemes increase computation and communication costs. This paper proposes a lightweight and authentic end-to-end communication model to detect MITM attacks using a pre-shared symmetric key. In addition, we implement and analyze the performance of our proposed security model on Linux-based virtual machines connected to large-scale hybrid IPv4-IPv6 virtual networks. Moreover, security analyses prove the effectiveness of our proposed model. Finally, we compare the performance of our proposed security model with existing models in terms of computation cost and communication overhead.

Secure Data Aggregation and Transmission System for Wireless Body Area Networks Using Twofish Symmetric Key Generation

Nowadays, Wireless Body Area Networks (WBANs) are mostly used in the healthcare industry. They represent a portable, inexpensive network that exhibition adaptability. The data developed using WBAN devices is vulnerable to transmission-related internal and external attacks; nevertheless, this vulnerability arises due to resource restrictions; by employing data aggregation technologies to conduct statistical analyses of medical data while protecting patient privacy, medical professionals can enhance the precision of diagnoses and assist medical insurance firms in selecting optimal plans for their clients. Maintaining the confidentiality and integrity of sensitive health information becomes more stimulating at the stages of aggregation and transmission due to security issues. This study proposes a novel method, Twofish Symmetric Key Generation (TFSKG), combined into a Secure Data Aggregation (SDA) and transmission system intended for WBANs. The Twofish technique is animatedly employed to make the secure symmetric keys chosen for its robust encryption capabilities. These keys are used to encrypt and decrypt aggregated health data through transmission. The proposed TFSKG-SDA method implements effective algorithms for aggregating data to safeguard end-to-end privacy and preserve data accuracy while reducing bandwidth consumption. Thus, for improved performance, an innovative genetic algorithm for data security is presented in this study. This paper introduces TFSKG-SDA, a system that, by employing rigorous simulation testing, enhances security protocols, resistance against recognized threats, and data transmission efficacy in the context of resource-constrained WBANs. We assess the encryption strength, computational cost, and communication efficiency of the TFSKG- SDA method to prove its significance to real-world healthcare applications.

Super Encryption Feal Algorithm and Base64 Algorithm Image File Security

In the rapidly advancing digital era, image file security has become a critical issue, especially with the increasing risks of data breaches and attacks on digital files. This study aims to enhance the security of image files by implementing a combination of two cryptographic algorithms: Fast Data Encipherment Algorithm- 4 (FEAL-4) and Base64. FEAL-4 is a symmetric encryption algorithm known for its high speed and processing efficiency, while Base64 is used for encoding binary data into ASCII format to ensure safer transmission. This research develops a super encryption system that integrates these two algorithms to protect the integrity and confidentiality of image files, particularly for BMP, JPEG, and PNG formats. The implementation was carried out using the Visual Basic programming language. The results of the study show that the combination of FEAL-4 and Base64 algorithms significantly enhances the security of image files, with a high success rate in the encryption and decryption processes.

DLSEA-64: dynamic lightweight symmetric encryption algorithm for secure data transmission in IoT based pervasive sensing applications

ABSTRACT Remote patient monitoring, particularly for the elderly, is gaining popularity due to the Internet of Medical Things (IoMT). However, IoMT devices are highly vulnerable to cyber attacks related to data confidentiality. Hence, lightweight cryptographic algorithms are found to be highly necessary to ensure safe data transfer in such devices. This paper introduces a Dynamic Lightweight Symmetric Encryption Algorithm (DLSEA) in order to challenge issues related to real-time data security and privacy. DLSEA is executed on Arduino Uno (ATmega328P) and Arduino Mega (ATmega2560) microcontrollers by using the Proteus simulation tool that employs a 64-bit temporal secret key and a 64-bit block cipher for encryption of data. Several experiments were conducted using payloads of varying sizes to record execution time, energy consumption, RAM usage, ROM usage and avalanche effect. The experiments demonstrated that for data sizes between 128-512 bytes, DLSEA requires 2.49-3.27 ms on the ATmega2560, which is 47% faster than a similar algorithm known as PRESENT. Additionally, DLSEA is 46% more energy-efficient, with RAM usage decreased by 41.81% and ROM usage decreased by 57.19% compared to PRESENT. Experimental results also show that DLSEA satisfies the plaintext sensitivity test, the key sensitivity test, and the rigorous avalanche criteria test (i.e., ~50%).

Applying Polynomials for Developing Post Quantum Cryptography Algorithms to Secure Online Information - An Initial Hypothesis

In the contemporary era, a vast array of applications employs encryption techniques to ensure the safeguarding and privacy of data. Quantum computers are expected to threaten conventional security methods and two existing approaches, namely Shor's and Grover's algorithms, are expediting the process of breaking both asymmetric and symmetric key classical algorithms. The objective of this article is to explore the possibilities of creating a new polynomial based encryption algorithm that can be both classically and quantum safe. Polynomial reconstruction problem is considered as a nondeterministic polynomial time hard problem (NP hard), and the degree of the polynomials provide the usage of scalable key lengths. The primary contribution of this study is the proposal of a novel encryption and decryption technique that employs polynomials and various polynomial interpolations, specifically designed for optimal performance in the context of a block cipher. This study also explores various root convergence techniques and provides algorithmic insights, working principles and the implementation of these techniques, which can potentially be utilized in the design of a proposed block-cipher symmetric cryptography algorithm. From the implementation, comparison and analysis of Durand Kernal, Laguerre and Aberth Ehrlich methods, it is evident that Laguerre method is performing better than other root finding approaches. The present study introduces a novel approach in the field of polynomial-based cryptography algorithms within the floating-point domain, thereby offering a promising solution for enhancing the security of future communication systems.

Development of the Combined Operations Method to Improve the Efficiency of Block Encryption

Real-time information protection requires the implementation of special methods aimed at providing reliable and fast encryption algorithms to protect personal and corporate information from unauthorized access. With the growth of data volumes and the speed of their processing, the importance of effective encryption methods increases significantly. One of the common, reliable and well-known encryption algorithms is AES (Advanced Encryption Standard), also known as Rijndael, which is a symmetric block cipher. AES has high efficiency and cryptoresistance and is suitable for processing large volumes of data. The reliability and speed of encryption and decryption using the AES algorithm depends on the size of the key and the data. This paper proposes to improve algorithm of symmetric block encryption AES to provide faster data processing. The possibility of combining mathematical operations that have a similar principle of processing elements is shown. This approach made it possible to reduce the processing time for data encryption and decryption compared to known implementations. A comparative analysis of the practical implementation of the standard and optimized AES cryptoalgorithms has been carried out. The general principles of the proposed method are to transform all two-dimensional arrays into one-dimensional arrays, add auxiliary tables for ShiftRows and MixColumns operations, and combine operations with similar element processing principles. The simulation results showed that the modified implementation of the AES algorithm demonstrates a reduction in processing time of up to 50% when encrypting and up to 75% when decrypting data compared to known results

Secure Framework Optimizes QAES Technique Used for Computing in the Cloud

Several consumers are concerned about the security of their data kept in the cloud, and many see local servers as a safer choice due to perceived control. However, cloud service companies frequently promise greater security procedures and employ dedicated security specialists, making data stored in the cloud potentially more secure. When the data holder expires, new files are saved in the cloud and encrypted with the QAES technology. The data owner then receives the encrypted data request. The sender and user both analyze data before sending encoded documents to the cloud. The key will be used to remove encryption from subsequent data. If users are unable to access the desired data, they should submit a fresh request. The most recent innovation focuses on combining an enhanced form of Quantum Key Distribution (QKD) with AES. This integration resulted in Quantum-AES (QAES), a novel quantum symmetric encryption scheme. QAES is based on the development of a quantum encryption key using dynamic quantum S-Boxes (DQS-Boxes), as opposed to the frequently utilized static S-Boxes. This strategy enhances security. Comparably, time is required to build files faster than they do now. This approach prevents brute force attacks since it uses the QAES algorithm, which provides additional security.

VCSA: Verifiable and collusion-resistant secure aggregation for federated learning using symmetric homomorphic encryption

As a novel distributed learning framework for protecting personal data privacy, federated learning, (FL) has attained widespread attention through sharing gradients among users without collecting their data. However, an untrusted cloud server may infer users’ individual information from gradients and global model. In addition, it may even forge incorrect aggregated results to save resources. To deal with these issues, despite that the existing works can protect local model privacy and achieve verifiability of aggregated results, they are defective in protecting global model privacy, guaranteeing verifiability if collusion attacks occur, and suffer from high computation cost. To further tackle the above challenges, a verifiable and collusion-resistant secure aggregation scheme for FL is proposed, named VCSA. Concretely, we combine symmetric homomorphic encryption with single masking to protect model privacy. Meanwhile, we adopt verifiable multi-secret sharing and generalized Pedersen commitment to achieve verifiability and prevent users from uploading incorrect shares. Furthermore, high model accuracy can be ensured even if some users go offline. Security analysis illustrates that our VCSA enhances the security of FL, realizes verifiability despite collusion attacks and robustness to dropout. Performance evaluation displays that our VCSA can reduce at least 28.27% and 79.15% regarding computation cost compared to existing schemes.

Performance Analysis of symmetric and asymmetric Encryption Algorithms Based on File, Image and Video

The rapid evolution of digital technology has exponentially amplified the generation and sharing of diverse digital data, notably files, images, and videos, over the internet, intensifying the critical need for enhanced security measures to safeguard these prevalent data types. This research presents a comprehensive analysis of various encryption algorithms applied to different data types - files, images, and videos. The study categorizes encryption algorithms into symmetric and asymmetric types, with examples including AES, DES, Triple DES, RSA, Diffie-Hellman, and ECC. The paper further explores specific algorithms used for file, image, and video encryption. The objective is to identify the most efficient encryption algorithm for each data type, thereby enhancing data security in the digital age. The paper emphasizes that while encryption is a crucial tool for data security, it should be used in conjunction with other security measures for comprehensive protection.

SMedIR: secure medical image retrieval framework with ConvNeXt-based indexing and searchable encryption in the cloud

The security and privacy of medical images are crucial due to their sensitive nature and the potential for severe consequences from unauthorized modifications, including data breaches and inaccurate diagnoses. This paper introduces a method for lossless medical image retrieval from encrypted images stored on third-party clouds. The proposed approach employs a symmetric integrity-centric image encryption scheme, leveraging multiple chaotic maps and cryptographic hash techniques, to ensure lossless image reconstruction. Medical images are first encrypted by the image owners and converted into hashcodes encapsulating essential features using a deep hashing technique with the ConvNeXt network as the backbone in parallel. To ensure index privacy, these hashcodes are encrypted in a searchable manner. The encrypted medical images, along with a secure index, are subsequently uploaded to cloud storage. Authorized medical image users can request similar medical images for diagnostic purposes by submitting a query image, from which a search trapdoor is generated and sent to the cloud. The retrieval process involves a secure similar image search over the encrypted indexes, followed by decryption along with integrity verification of the retrieved images. The proposed method has been rigorously tested on three standard medical datasets, demonstrating an improvement of 5-20% in retrieval accuracy compared to standard baselines. Formal security analysis and experimental results indicate that the proposed scheme offers enhanced security and retrieval accuracy, making it an effective solution for the encrypted storage and secure retrieval of medical image data.

A Combination of Attribute-Based Encryption and Blockchain Access Control Scheme in Smart Home Environment

In response to the problems of excessive decryption computation burden on users, inability to protect users' privacy information, and the inability of traditional cloud storage methods to meet users' faster file upload and download speed requirements and track malicious users, this paper proposes an attribute-based encryption and blockchain-based trusted data access control scheme for smart home environments. The scheme combines symmetric encryption algorithms and attribute-based encryption algorithms to achieve fine-grained access control of data. At the same time, it leverages edge computing technology to outsource most of the decryption and computation operations to edge computing nodes, reducing the user's decryption and computation burden. Furthermore, the introduction of blockchain technology enables the monitoring and auditing of users within the system, achieving full traceability of access control. Finally, the proposed scheme was analyzed and validated through simulation experiments, which showed that the scheme is safe and effective, protecting users' security and privacy, and enabling secure data sharing.

Implementing Grover’s on AES-based AEAD schemes

Extensive research is currently underway to determine the security of existing ciphers in light of the advancements in quantum computing. Against symmetric key cryptography, Grover’s search algorithm is a prominent attack, capable of reducing search costs to the square root. For using Grover’s algorithm, it is imperative to embed the target cipher into a quantum circuit. Even so, this area of research is relatively new; it has garnered significant attention from the research community. In this study, we provide the first estimation of the cost of Grover’s key search attack against the AES-based AEAD schemes Rocca-S, AEGIS-128, and Tiaoxin-346. Our analysis considers circuit depth restrictions specified in NIST’s PQC standardization process. Considering NIST’s maximum depth constraints, We present the overall cost of these attacks using gate count and depth-times-width metrics. We observed that for MAXDEPTH=240\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf{MAXDEPTH} = 2^{40}$$\\end{document}, Rocca-S, AEGIS-128, and Tiaoxin-346 can be retrieved using Grover’s search algorithm with gate count of 1.09 × 2253, 1.14 × 2124, and 1.22 × 2124 respectively. Concerning the current updated values by NIST, these ciphers are secure in terms of the cost of implementing Grover’s attack for key recovery. The quantum circuits of these ciphers are implemented using QISKIT, an open-source software development kit (SDK) designed for working with quantum computers running on the IBM Quantum Experience platform.

Reconstructing S-Boxes from Cryptographic Tables with Milp

Reconstructing an S-box from a cryptographic table such as difference distribution table (DDT), linear approximation table (LAT), differential-linear connectivity table (DLCT) or boomerang connectivity table (BCT) is one of the fundamental problems in symmetric-key cryptography. Till now, there are only very few known methods which can reconstruct an S-box from a given table: guess-and-determine algorithms of Boura et al. (DCC 2019) and Tian et al. (DCC 2020), sign determination algorithm of Dunkelman et al. (ToSC 2019) and STP based approach of Lu et al. (DCC 2022). In this paper we consider the reconstruction problem in an even more challenging setup where one needs to reconstruct S-boxes from a partial cryptographic table. We are able to reconstruct S-boxes when only a few number of rows of a cryptographic table is given. This problem has never been studied in the literature. We apply mixed integer linear programming (MILP) as the key tool for solving this problem. Needless to say that we can solve the reconstruction problem when the full table is given and this is the first ever application of MILP tool in solving such fundamental problems. As a further application of our method, we provide the generic MILP models which can search for S-boxes with a given cryptographic property such as differential uniformity, linearity, differential-linear uniformity or boomerang uniformity. Additionally, our method can recover a Boolean function from a given Walsh spectrum or a Boolean function with a given nonlinearity. We also introduce a new heuristic called Optimistic MILP objective that guides the model towards obtaining multiple S-boxes or Boolean functions with the same cryptographic property. We give detailed experimental results for up to 6-bit S-boxes showing the effectiveness of our technique.