Symmetric Key Research Articles

Split-n-Swap: A New Modification of the Twofish Block Cipher Algorithm

Securing digital data from unauthorized access throughout its entire lifecycle has been always a critical concern. A robust data security system should protect the information assets of any organization against cybercriminal activities. The Twofish algorithm is one of the well-known symmetric key block cipher cryptographic algorithms and has been known for its rapid convergence. But when it comes to security, it is not the preferred cryptographic algorithm to use compared to other algorithms that have shown better security. Many applications and social platforms have adopted other symmetric key block cipher cryptographic algorithms such as the Advanced Encryption Standard (AES) algorithm to construct their main security wall. In this paper, a new modification for the original Twofish algorithm is proposed to strengthen its security and to take advantage of its fast convergence. The new algorithm has been named Split-n-Swap (SnS). Performance analysis of the new modification algorithm has been performed using different measurement metrics. The experimental results show that the complexity of the SnS algorithm exceeds that of the original Twofish algorithm while maintaining reasonable values for encryption and decryption times as well as memory utilization. A detailed analysis is given with the strength and limitation aspects of the proposed algorithm.

Securing textual information with an image in the image using a visual cryptography AES algorithm.

Now a day‟s the uses of devices such as computer, mobile and many more other device for communication as well as for data storage and transmission has increases. As a result there is increase in no of user‟s also there is increase in no of unauthorized user‟s which are trying to access a data by unfair means. This arises the problem of data security. To solve this problem a data is stored or transmitted in the encrypted format. This encrypted data is unreadable to the unauthorized user. Cryptography is a science of information security which secures the data while the data is being transmitted and stored. There are two types of cryptographic mechanisms: symmetric key cryptography in which the same key is use for encryption and decryption. In case of asymmetric key cryptography two different keys are used for encryption and decryption. Symmetric key algorithm is much faster and easier to implement and required less processing power as compare to asymmetric key algorithm. The Advanced Encryption Standard (AES) was published by the National Institute of Standards and Technology (NIST) in 2001. This types of cryptography relies on two different keys for encryption and decryption. Finally, cryptographic hash function using no key instead key it is mixed the data.

TWo-IN-one-SSE: Fast, Scalable and Storage-Efficient Searchable Symmetric Encryption for Conjunctive and Disjunctive Boolean Queries

Searchable Symmetric Encryption (SSE) supports efficient yet secure query processing over outsourced symmetrically encrypted databases without the need for decryption. A longstanding open question has been the following: can we design a fast, scalable, linear storage and low-leakage SSE scheme that efficiently supports arbitrary Boolean queries over encrypted databases? In this paper, we present the design, analysis and prototype implementation of the first SSE scheme that efficiently supports conjunctive, disjunctive and more general Boolean queries (in both the conjunctive and disjunctive normal forms) while scaling smoothly to extremely large encrypted databases, and while incurring linear storage overheads and supporting extremely fast query processing in practice. We quantify the leakage of our proposal via a rigorous cryptographic analysis and argue that it achieves security against a well-known class of leakage-abuse and volume analysis attacks. Finally, we demonstrate the storage-efficiency and scalability of our proposed scheme by presenting experimental results of a prototype implementation of our scheme over large real-world databases.

A Lightweight and Efficient Remote Data Authentication Protocol Over Cloud Storage Environment

Cloud storage services need cost-effective, independent, and scalable functionality to manage data. Cloud repositories provide an opportunity to manage and access essential data conveniently. This article proposes a secure authentication protocol to resolve these issues. To add a convenient sharing of data controlled by a data delegator, we use symmetric encryption and decryption algorithms in which cloud servers encrypt and decrypt the data to control the accessibility of the user. Furthermore, informal security analysis demonstrates that our devised protocol is robust enough to resist various attacks. We present the formal analysis of security using the Random Oracle Model (ROM) to evaluate and prove the security strength of the devised protocol. The proposed and related protocols have been implemented on an online cloud server named PythonAnywhere with PyCrypto and Time libraries using Python with the help of a system that has predefined specifications to compare the performance. The results show that our scheme has feasible computation, storage, communication, and energy efficiency compared to various related protocols.

A Concentrated Energy Consumption Wireless Sensor Network by Symmetric Encryption and Attribute Based Encryption Technique

Wireless sensor networks (WSNs) are increasingly used in a wide variety of settings, including defence, industry, healthcare, and education. Hundreds or even thousands of sensor nodes are spread out across a given area and linked to a central Base Station (BS) in order to keep tabs on the environment. The BS then sends the data out to the users over the internet. The sensor network's adaptability, portability, dependability, and quickness are driving its widespread use across industries. The suggested SHS evaluates the efficiency of well-established symmetric algorithms to see where it stands in the spectrum of security. The Blowfish encryption algorithm was proven to require the least amount of processing power after extensive benchmarking. Therefore, the Blowfish algorithm is selected to protect sensitive medical information. The medical database receives the encrypted health records. Only those with proper permissions should be able to access them. Therefore, the CP-ABE is implemented to regulate access to patient records. The SHS's results on the dataset are compared to those of other existing systems. With SHS, health data may be transmitted to doctors rapidly and securely because it requires less computing time and energy. In addition to these benefits, SHS also offers privacy, authentication, and authorization.

EFPB: Efficient Fair Payment Based on Blockchain for Outsourcing Services in Cloud Computing

Despite the maturity of cloud services (e.g., outsourcing of computational tasks), a number of operational challenges remain. For example, how do we ensure trust between outsourcers and workers in a zero-trust environment? While a number of blockchain-based solutions that eliminate the reliance on trusted third parties have been presented, many of these existing approaches do not achieve robust fairness and/or support compatibility with other systems. In this paper, we propose an efficient fair payment system using blockchain (EFPB), designed to achieve robust fairness and compatibility. Specifically, EFPB comprises a number of cryptographic building blocks, mainly: one-way accumulator (RSA-based construction), stealth address and symmetric encryption. We then evaluate the performance of EFPB to demonstrate that it is more efficient and low-cost than other competing schemes, as well as presenting a comparative summary of functionalities.

More secure on the symmetric encryption schemes based on triple vertex path graph

A triple vertex (TV) and triple vertex path (TVP) graph are defined as new concepts. These concepts consider the main point of this work to modify the symmetric encryption (SE) schemes and increase the security level in comparison with the previous ES schemes. In proposed ES schemes, the ciphertexts of the plaintexts are sent to the receiver entity as the TVP graph. Two study cases of the proposed TVPG-SE schemes are presented as new experimental results. The security issues of the proposed TVPG-SE schemes have been determined. The TVPG-SE schemes consider new insights for more secure communications.

Ensuring the security of web applications operating on the basis of the SSL/TLS protocol

SSL/TLS (Secure Socket Layer/Transport Layer Security)-enabled web applications are designed to provide authentication based on a public key certificate, as well as generating a secure session key and traffic privacy based on a symmetric key. Today, a large number of e-commerce applications such as stock trading, banking, shopping and gaming rely on the robustness of the SSL/TLS protocol. Recently, a potential threat known as a Man-in-the-Middle or main-in-the-middle (MITM) attack has been used by attackers to attack SSL/TLS-enabled web applications, especially when users want to connect to an SSL/TLS-enabled web server. SSL/TLS. The current article discusses the Man-in-the-Middle attack threat for SSL/TLS-enabled web applications. The existing solution space for countering a MITM attack on SSL/TLS-enabled applications is also considered, and an effective solution is proposed that can resist a MITM attack on SSL/TLS-enabled applications. The proposed solution uses a soft token approach for user authentication in addition to SSL/TLS security features. The proposed solution is claimed to be safe, effective and user-friendly compared to similar approaches.

AI-Driven Innovations in Cryptography: Enhancing Key Generation and Security

In this paper, we introduce a novel approach for securing confidential data through a symmetric key cryptographic algorithm called the modified Hill Cipher by utilizing rhotrices. We provide a step-by-step procedure to implement this method and elucidate the process through an example. The modified Hill Cipher technique uses AI to generate key rhotrix and incorporates the use of rhotrices and rhotrix algebra to encrypt plain text and decrypt cipher text.

An Effective Hybrid Encryption Model using Biometric Key for Ensuring Data Security

Cybersecurity becomes a key concern in many applications as cybercrimes exploit system weaknesses. Cryptography helps protect sensitive data in everyday transactions and communications using passwords or tokens. However, the power of the encryption/decryption algorithms always depends on their ability to secure the data in any situation. This paper presents an effective hybrid encryption/decryption model that makes use of a biometric key along with an effective password to ensure data security. The biometric key utilised in the proposed model is generated from the fingerprint, which is a unique physical characteristic of an individual. The model initially encodes the data to be securely transmitted. The symmetric key encryption that makes use of a biometric key is applied over the encoded data. Another layer of defence is built by applying asymmetric key encryption to the encrypted data along with the details of the fingerprint. The Advanced Encryption Standard (AES) algorithm and Elgamal Encryption using Elliptical Curve Cryptography (E3C2) are used for symmetric and asymmetric encryptions. Experimental analysis is performed to analyse the model's computing speed and security and is compared with existing models and encoding/encryption techniques

Attack Detection for Networked Control Systems Using Event-Triggered Dynamic Watermarking

Dynamic watermarking schemes can enhance the cyber attack detection capability of networked control systems (NCSs). This paper presents a linear event-triggered solution to conventional dynamic watermarking (CDW) schemes. Firstly, the limitations of CDW schemes for event-triggered state estimation based NCSs are investigated. Secondly, a new event-triggered dynamic watermarking (ETDW) scheme is designed by treating watermarking as symmetric key encryption, based on the limit convergence theorem in probability. Its security property against the generalized replay attacks (GRAs) is also discussed in the form of bounded asymptotic attack power. Thirdly, finite sample ETDW tests are designed with matrix concentration inequalities. Finally, experimental results of a networked inverted pendulum system demonstrate the validity of our proposed scheme.

Modern symmetric searchable encryption technique for string classification in cloud technology

Modern symmetric searchable encryption technique for string classification in cloud technology

Development of the principles of parallelization of the symmetric AES encryption algorithm

This article delves into the potential of modern computational systems and technological advancements in refining encryption algorithms, with a particular focus on the Advanced Encryption Standard. The paper underscores the significance of understanding the intricate mechanics and primary processing stages of AES to harness its full potential for parallelization and acceleration. The research emphasizes the pivotal role of Graphics Processing Units in this optimization journey. Given their multi-threaded architecture, GPUs, when integrated with state-of-the-art parallel computing platforms like CUDA and OpenCL, can process vast data volumes with heightened efficiency. This integration not only speeds up the encryption process but also enhances its robustness. The article concludes with a forward-looking perspective, anticipating a deeper convergence between the realms of cryptography and parallel computing. Such a fusion is projected to usher in revolutionary enhancements in both the security and performance facets of encryption systems.

Research on Design of Chaotic Symmetrical Digital Image Encryption System

Research on Design of Chaotic Symmetrical Digital Image Encryption System

SetRkNN: Efficient and Privacy-Preserving Set Reverse kNN Query in Cloud

The advance of cloud computing has driven a new paradigm of outsourcing large-scale data and data-driven services to public clouds. Due to the increased awareness of privacy protection, many studies have focused on addressing security and privacy issues in outsourced query services. Although many privacy-preserving schemes have been proposed for various query types, the set reverse k nearest neighbors (RkNN) query is still an unexplored area. Even if some existing schemes can be adapted to achieve privacy-preserving set RkNN queries, they will suffer from linear search efficiency. As a steppingstone, in this paper, we propose an efficient and privacy-preserving set RkNN query scheme over encrypted data with sublinear query efficiency. Specifically, we first design an inverted prefix index to organize the set dataset and propose an algorithm to traverse the index with sublinear search efficiency. Then, we propose two oblivious data comparison protocols based on a symmetric homomorphic encryption (SHE) scheme and design the private filter/refinement protocols to preserve the privacy of index searching. After that, we propose an access pattern privacy-preserving set RkNN query scheme by using private filter/refinement protocols. Rigorous security analysis demonstrates that our scheme can protect data privacy and access pattern privacy. Experimental results indicate that our scheme is more efficient than the available naive solution in terms of computational costs and communication overheads.

An efficacy analysis of data encryption architecture for cloud platform

In recent times, cloud computing is being utilized largely for storage and information sharing purposes in several established commercial segments, particularly those where online businesses are prevalent, such as Google, Amazon, etc. Cloud system presents several benefits to users in terms of easy operations, low implementation, and maintenance expenses. However, significant risks are encountered in the data security procedures of cloud systems. Although the area is frequently being analyzed and reformed, the concern of cloud data protection and user reliability remains under uncertainty due to growing cyber-attack schemes as well as cloud storage system errors. To deal with this risk and contribute to the endeavor of providing optimal data security solutions in cloud data storage and retrieval system, this paper proposes a Symmetric Searchable Encryption influenced Machine Learning based cloud data encryption and retrieval model. The proposed model enhances data security and employs an effective keyword ranking approach by using an Artificial Neural Network. The comparative assessment of the proposed model against multiclass SVM and Naïve Bayes has established the better operational potentiality of the model. The effectiveness of the proposed work is justified by the association between high TPR and low FPR. Further, a low CCR of 0.6973 adds up to the success of the proposed work.

PGSim: Efficient and Privacy-Preserving Graph Similarity Query Over Encrypted Data in Cloud

The boom of cloud computing has stimulated the prevalence of outsourced query services, and privacy concerns further motivate extensive studies on privacy-preserving queries in the cloud. Graph similarity query is one critical query type, in which the similarity between two graphs is usually measured by graph edit distance (GED). Although many schemes have been proposed for GED computation/graph similarity query, they do not consider data privacy and are not applicable to the cloud computing scenario. To address this issue, in this paper, we propose the first efficient and privacy-preserving graph similarity query (PGSim) scheme in the filter and verification framework. Specifically, we first identify the pivot filter property of GED and use the property to design a pivot R-tree based filter algorithm, which can efficiently retrieve candidate graphs for graph similarity query. Then, we design a vertex mapping (VM) tree to index all vertex mappings between two graphs and develop a GED query verification algorithm to verify candidate graphs. After that, we design a suite of private algorithms based on a symmetric homomorphic encryption scheme and apply them to propose a pivot R-tree based filter predicate encryption (PRFilter) scheme and a private GED query verification (PGQVerify) algorithm. Based on the PRFilter scheme and the PGQVerify algorithm, we propose our PGSim scheme. Rigorous security analysis shows that our scheme is selectively secure. Performance evaluation also demonstrates the high efficiency of our scheme.

An Efficient Technique to Prevent Data Misuse with Matrix Cipher Encryption Algorithms

Many symmetric and asymmetric encryption algorithms have been developed in cloud computing to transmit data in a secure form. Cloud cryptography is a data encryption mechanism that consists of different steps and prevents the attacker from misusing the data. This paper has developed an efficient algorithm to protect the data from invaders and secure the data from misuse. If this algorithm is applied to the cloud network, the attacker will not be able to access the data. To encrypt the data, the values of the bytes have been obtained by converting the plain text to ASCII. A key has been generated using the Non-Deterministic Bit Generator (NRBG) mechanism, and the key is XNORed with plain text bits, and then Bit toggling has been implemented. After that, an efficient matrix cipher encryption algorithm has been developed, and this algorithm has been applied to this text. The capability of this algorithm is that with its help, a key has been obtained from the plain text, and only by using this key can the data be decrypted in the first steps. A plain text key will never be used for another plain text. The data has been secured by implementing different mechanisms in both stages, and after that, a ciphertext has been obtained. At the end of the article, the latest technique will be compared with different techniques. There will be a discussion on how the present technique is better than all the other techniques; then, the conclusion will be drawn based on comparative analysis.

Performance Analysis of Encryption Capabilities of ARM-based Single Board Microcomputers

In the few years since the Raspberry Pi was released in 2012, countless microcomputers based on the ARM architecture have been introduced.Their small size, high performance relative to their power consumption, and the ability to run the popular Linux operating system make them ideal for a wide range of tasks. Information security is an area of particular importance. Different encryption and encoding algorithms play an important role in almost all areas of information security. However, these algorithms are very computationally intensive, so it is important to investigate which microcomputers can be used for these tasks, and under which trade-offs. The performance of ten different microcomputers is investigated and presented for the application of common symmetric and public-key encryption and decryption, digest creation and message authentication protocols, such as RSA, AES, HMAC, MD5, SHA. Reliable encryption requires the generation of reliable (pseudo)random numbers (Cryptographically Secure Random Numbers, CSRN), and microcomputers based on ARM SoCs usually have hardware implemented (pseudo)random number generators. The applicability of the random number generat er generators. The applicability of the random number generators of different microcomputers are investigated and presented; test methoods are described , and recommendations are made.

Towards Efficient Verifiable Boolean Search Over Encrypted Cloud Data

Symmetric Searchable Encryption (SSE) schemes facilitate searching over encrypted data, and have been extensively explored to improve function, efficiency or security. There are, however, additional functions that we need to consider in a real-world setting. For example, forward and backward privacy are required to adequately secure newly added documents and deleted documents in Dynamic SSE (DSSE) schemes, and support boolean search (that allows users to search over encrypted data using basic boolean operations) to achieve improved efficiency and retrieval accuracy. Therefore, in this paper we first construct the Verifiable Boolean Search over encrypted data (VBS), and then improve VBS to achieve Forward and Backward privacy (VBS-FB). Finally, we formally prove the security of our proposed schemes, and evaluate their performance using real-world datasets.