Existing Encryption Techniques Research Articles

Analyzing the Impact of Quantum Computing on Current Encryption Techniques

As the field of quantum computing progresses, the disruption to traditional encryption methods, which secure vast amounts of sensitive data, becomes an imminent threat, and conventional encryption techniques, primarily based on mathematical complexity, may no longer suffice in the era of quantum supremacy. This research systematically analyzes the vulnerabilities of current encryption standards in the face of advanced quantum computing capabilities, focusing specifically on widely-used cryptographic protocols such as RSA and AES, which are foundational to modern cybersecurity. Employing the SmartPLS method, the study models the interaction between quantum computing power and the robustness of existing encryption techniques, involving simulating quantum attacks on sample cryptographic algorithms to evaluate their quantum resistance. The findings reveal that quantum computing possesses the capacity to significantly compromise traditional encryption methods within the next few decades, with RSA encryption showing substantial vulnerabilities while AES requires considerably larger key sizes to maintain security. This study underscores the urgency for the development of quantum-resistant encryption techniques, critical to safeguarding future digital communication and data integrity, and advocates for a paradigm shift in cryptographic research and practice, emphasizing the need for 'quantum-proof' algorithms. It also contributes to the strategic planning for cybersecurity in the quantum age and provides a methodological framework using SmartPLS for further exploration into the impact of emerging technologies on existing security protocols.

Polar code-based cryptosystem: comparative study and analysis of efficiency

<p><span>This review paper aims to examine the use of polar codes in public key cryptosystems, providing a comprehensive overview of the state-of-the-art in this field at present. This study thoroughly searches databases such as IEEE Xplore, Scopus, and the ACM digital library to locate relevant research articles. In this study, we demonstrate the use of polar codes in public key cryptography and provide valuable insights for researchers interested in this field of research. The paper identifies several areas for further research and development, such as improved security and reliability of polar code-based cryptosystems. An analysis of the review highlights the major challenges and open research questions in this area, including the need for efficient key generation algorithms and the trade-offs between security and performance. An analysis of various existing encryption techniques as well as their security proofs is provided in the tables.</span></p>

Efficient and Privacy-Preserving Similar Patients Query Scheme Over Outsourced Genomic Data

Over the past decade, genomic data has grown exponentially and is widely used in promising medical and health-related applications, which opens up new opportunities for the field of medicine. Similar patients query (SPQ), which can help physicians formulate an optimal therapy, is one of such popular applications. Despite its popularity, since human genomes are usually highly sensitive, a series of policies have been launched by the government to strictly control its acquisitions and utilization. Thus, how to prevent privacy disclosure becomes of great importance to the flourish of SPQ services. In this paper, aiming at the above challenge, we first design a novel genetic BK-tree (GBK-tree) for a genomic database. Then, combined with a random sorting mechanism and some existing encryption techniques, we propose an efficient and privacy-preserving similar patients query scheme over encrypted cloud data, named CASPER. With CASPER, a medical institution can securely outsource its private genomic database to a cloud server, and physicians can request SPQ services from the cloud server while keeping her/his query secret. Detailed security analysis shows that CASPER can preserve privacy in the presence of different threats. Furthermore, extensive performance evaluations demonstrate the high accuracy and efficiency of our proposed scheme.

Triple Encryption of Images based on RC4, Zigzag, and Elliptic Curve Algorithms for Enhanced Security

The security of digital images is of paramount importance in today's digital world. Encryption is a technique used to secure digital images from unauthorized access. The encryption technique transforms the original image into a scrambled form, which is unreadable to anyone without the proper decryption key. Several encryption techniques have been proposed to secure digital images, including DES, AES, RSA, and ECC. These methods, however, are susceptible to side-channel and brute-force attacks. Hence, new encryption methods that offer more security are required. The new multi-encryption algorithm for secure digital image encryption is presented in this research. The suggested approach combines the RC4, Zigzag transformation, and Elliptic Curve Cryptography (ECC) algorithms to increase the security of picture encryption. Data is encrypted using the RC4 stream cipher, image data is scrambled using the Zigzag method, and the key used in the transformation is encrypted using the ECC technique. The proposed algorithm was tested using several standard metrics, and the results show that it outperforms existing encryption techniques in terms of security.

Dual-server certificateless public key encryption with authorized equality test for outsourced IoT data

The Internet of Things (IoT) devices with restricted storage and computing sources are unable to store and handle massive data at local. A promising method is to engage some cloud server for maintaining outsourced encrypted IoT data and responding user request, in the meantime, the privacy of outsourced data can be protected. Existing encryption techniques with equality test allow the authorized cloud server to compare encrypted data and perform data classification. However, these schemes in the single server model cannot resist internal keyword guessing attacks. Also, the existing schemes in public key setting confront the burden of maintaining public key certificates, and the ones in identity-based setting face the key escrow problem. To address these issues, this paper proposes a dual-server certificateless public key encryption scheme supporting authorized equality test (DS-CL-AET) in bilinear groups. Security analysis indicates that the proposed DS-CL-AET scheme offers confidentiality protection for outsourced ciphertext and authentication tokens. Performance analysis demonstrates the practicality of our DS-CL-AET scheme in securing outsourced IoT data in clouds.

2D Lorentz Chaotic Model Coupled with Logistic Chaotic Model for Medical Image Encryption: Towards Ensuring Security for Teleradiology

Medical images play pivotal role in health care sector for disease diagnosis and therapeutic planning. Encryption algorithms are widely used in medical image processing for ensuring privacy in data transfer. This research work proposes a hybrid chaotic model, 2D Lorentz Chaotic model coupled with the Logistic chaotic model for the encryption/decryption of medical DICOM CT images. Prior to encryption, preprocessing was done by the median filter. The hybrid chaotic model scrambles the rows and columns of the image and bitwise XOR operation is carried out to generate the encrypted image. The performance metrics reveals the proficiency of the approach utilized in this research work, the mean PSNR value was 73.45, mean NPCR value was 99.99 and mean UACI value was 26.03. The hybrid encryption model outperforms the existing encryption techniques and paves the way towards the teleradiology applications. The encrypted image can be transferred through the cloud network and the receiver side node can decrypt the image. The decrypted image equality was found to be proficient for healthcare applications.

CryptoCliqIn: Graph-Theoretic Cryptography Using Clique Injection

Because encryption is a fundamental security building block, existing encryption techniques like AES, Twofish, Blowfish, and Triple DES are constantly under the threat of being compromised. We introduce a simple graph-theoretic encryption method named CryptoCliqIn using clique injection and prove that the decryption of this encryption without the appropriate key is #P-complete. We have shown that the proposed model does not introduce delays in encryption and decryption times and provides a more secure mechanism compared to some of the existing encryption mechanisms. Finally, an adaptation of CryptoCliqIn in an intelligent system is discussed under the setup of intelligent and smart building.

Pop-Crypt: Identification and Management of Popular Words for Enhancing Lifetime of EnCrypted Nonvolatile Main Memories

Emerging nonvolatile memories (NVMs) are considered as potential replacements of the traditional DRAM-based main memories. However, the nonvolatility feature of the NVMs may lead to the stealing of sensitive data stored in NVMs due to their prolonged data retention. Memory encryption turns out to be a viable option to provide data security. However, the existing encryption techniques, on account of the diffusion property, increase the number of bit-flips in the NVM cells, thus leading to their early wear out. Therefore, security and lifetime issues of the NVMs are difficult to go hand in hand. In this article, we identify words that are repeated in several memory blocks and term them as popular words. The proposal is to avoid the encryption of the popular words by maintaining them in a reference table. In our proposal, Pop-Crypt, every block to be written to the memory gets partially encrypted in which the popular words are replaced with pointers to the reference table, and other words get encrypted. The partially encrypted blocks (PEBs) reduce the number of bit-flips in PCM, thereby improving its lifetime significantly. Experimental results show that Pop-Crypt considerably improves lifetime, energy consumption, and system performance over baseline and a state-of-the-art technique.

A Novel Machine Learning Technique for Selecting Suitable Image Encryption Algorithms for IoT Applications

The Internet of Things connects billions of intelligent devices that can interact with one another without human intervention, and during communication, a large amount of data is exchanged between the devices. As a result, it is critical to secure digital data using an encryption technique that provides a suitable degree of security. Numerous existing encryption techniques do not offer sufficient security. Therefore, it is critical to figure out which encryption technique is most appropriate for a particular kind of data. When it comes to manually deciding which encryption technique to use, the process might take a long time. In this research, we present a novel technique for selecting Encryption Algorithms (EAs) based on a particular application using pattern recognition and machine learning techniques. To accomplish this goal, we also prepare a dataset. Several machine learning techniques, such as Support Vector Machines (SVMs), Linear Regression (LR), K -Nearest Neighbour (KNN), Naïve Bayes (NB), Decision Trees (DT), and Random Forests (RF), are evaluated. Based on the evaluation, the SVM has been chosen as the best option for the intended technique because its classification accuracy is 98.7%. The experimental results, including accuracy, precision, recall, and F1-score, are used to gauge the performance of the suggested technique. The proposed technique is also compared with the existing techniques to demonstrate its effectiveness.

An Improved Encryption Technique for Digital Imaging and Communications in Medicine (DICOM)

Secured transmission is the most important aspect of transmission in today’s world as existing encryption techniques are facing different issues in the last few years. There is a high need for efficient and highly secured encryption techniques for medical data. In this work, various studies have been done so far but due to highly complex data. It limits the security high so here the present study proposes hybrid methods combining segmentation technique with scan pattern approach, which uses qualities of Segmentation, Scan pattern, and XORing with keys for medical data. The proposed hybrid method is prepared more strongly and novelly by smearing various operations on the pixels of the image provisional on the outcome of the calculation of the segmentation. The results analysis of various security parameters with previously existing techniques is significant.

Improved Security of E-Healthcare Images Using Hybridized Robust Zero-Watermarking and Hyper-Chaotic System along with RSA

With the rapid advancements of the internet of things (IoT), several applications have evolved with completely dissimilar structures and requirements. However, the fifth generation of mobile cellular networks (5G) is unable to successfully support the dissimilar structures and requirements. The sixth generation of mobile cellular networks (6G) is likely to enable new and unidentified applications with varying requirements. Therefore, 6G not only provides 10 to 100 times the speed of 5G, but 6G can also provide dynamic services for advanced IoT applications. However, providing security to 6G networks is still a significant problem. Therefore, in this paper, a hybrid image encryption technique is proposed to secure multimedia data communication over 6G networks. Initially, multimedia data are encrypted by using the proposed model. Thereafter, the encrypted data are then transferred over the 6G networks. Extensive experiments are conducted by using various attacks and security measures. A comparative analysis reveals that the proposed model achieves remarkably good performance as compared to the existing encryption techniques.

Building a Privacy-Preserving Blockchain-Based Bidding System: A Crypto Approach

Blockchain-based bidding systems are becoming increasingly popular nowadays. Due to the properties of blockchain, bidding records are unchangeable. With existing encryption techniques, these bidding records can only be shared by the bidder and the seller. Although this scenario sounds secure, it does not consider a coercion case. A powerful coercer may force the bidding system to open the records stored on the blockchain, and the system loses privacy. To solve this problem, in this paper, we introduce a new encryption scheme called deniable matchmaking encryption (DME). This new encryption scheme provides deniability not only for the message, but also for the identities. We use the chameleon hash function to make fake message and fake identities indistinguishable from the real message and the real identities. Therefore, the bidding system can use fake information to answer the coercer, and user privacy is kept by the blockchain-based bidding system.

IESCA: An efficient image encryption scheme using 2-D cellular automata

In the present era of Information Technology (IT), transfer of multimedia data is happening at a rapid pace. In many Internet-of-Things (IoT) based applications, sensor devices are sending information in the form of images. However, if the IoT applications are used in the information sensitive sectors like defense, healthcare, etc., the images must be encrypted before sending to the gateway fog nodes. Again, traditional encryption algorithms will not work in such scenarios due to the resource constraint nature of IoT devices. Here, Cellular Automata (CA) plays an important role. In this paper, a new secure and efficient image encryption technique is proposed using 2-D Moore Cellular Automata (MCA), called as IESCA which is lossless and easy to implement in hardware. Cellular Automata can generate random and chaotic sequence much faster than the existing chaotic sequence generators. It uses local transformations based on one bit state values of each of its neighbors. It makes CA implementation very easy and less resource consuming. Moreover, considering Moore convention has increased the key space more than the existing CA based image ciphering techniques. The randomness of the cipher images are evaluated using DIEHARD and NIST statistical test suites. Additionally, several security and performance analyses of the IESCA have proved its robustness and resistance against security attacks. Experimental results of the IESCA show its efficiency when compared to the existing encryption techniques. The proposed scheme has achieved 2.76% improvement in terms of execution time when compared with the state-of-the-arts. Moreover, the proposed scheme has achieved 5.02% improvement in terms of NPCR and 7.69% improvement in terms of UACI values when compared with the existing schemes.

Efficient Oblivious Data Structures for Database Services on the Cloud

Database-as-a-service (DBaaS) allows the client to store and manage structured data on the cloud remotely. Despite its merits, DBaaS also brings significant privacy issues. Existing encryption techniques (e.g., SQL-aware encryption) can mitigate privacy concerns, but they still leak information through access patterns, which are vulnerable to statistical inference attacks. Oblivious Random Access Machine (ORAM) can seal such leakages; however, the recent studies showed significant challenges on the integration of ORAM into databases. That is, the direct usage of ORAM on databases is not only costly but also permits very limited query functionalities. In this paper, we propose new oblivious data structures called Oblivious Matrix Structure (OMAT), which allow tree-based ORAM to be integrated into database systems in a more efficient manner with diverse query functionalities supported. OMAT provides special ORAM packaging strategies for table structures, which not only offers a significantly better performance but also enables a broad range of query types that may not be efficient in existing frameworks. On the other hand, OTREE allows oblivious conditional queries to be performed on tree-indexed databases more efficiently than existing techniques. We implemented our proposed techniques and evaluated their performance on a real cloud database with various metrics, compared with state-of-the-art counterparts.

Cellular Automata based Cryptography Model for Reliable Encryption Using State Transition in Wireless Network Optimizing Data Security

Authors propose a hardware based approach for reliable encryption in wireless network using Cellular Automata (CA). Distinct layers of encryption have been utilized in proposed model for enhancing data security. Transmitter and receiver modules are designed for performing state transition based encrypted activities. Transmitter module is required for capturing environmental turbulences (noise) from a specific geographical location and send encrypted signal to receiver module through wireless network. Receiver module analyses received signal after decryption for desired activities based on real time situations. Different hardware components are selected and compared based on market study targeting efficient construction of proposed modules. Time complexity and code break complexity are measured using different key lengths, keysets, and data sizes for proposed CA based encryption scheme achieving unique results in hardware based cryptography system. Encryption key length, index, and keyset are required for computing code break complexity in design model. Large data size is effectively managed to calculate protection ratio and reliability factor for realizing efficient protectiveness and accuracy. Comparative study between existing encryption technique and proposed CA based encryption technique is established based on time complexity and code break complexity.

An efficient anonymous authentication and confidentiality preservation schemes for secure communications in wireless body area networks

Wireless body area network (WBAN) is utilized in various healthcare applications due to its ability to provide suitable medical services by exchanging the biological data between the patient and doctor through a network of implantable or wearable medical sensors connected in the patients’ body. The collected data are communicated to the medical personals through open wireless channels. Nevertheless, due to the open wireless nature of communication channels, WBAN is susceptible to security attacks by malicious users. For that reason, secure anonymous authentication and confidentiality preservation schemes are essential in WBAN. Authentication and confidentiality play a significant role while transfers, medical images securely across the network. Since medical images contain highly sensitive information, those images should be transferred securely from the patients to the doctor and vice versa. The proposed anonymous authentication technique helps to ensure the legitimacy of the patient and doctors without disclosing their privacy. Even though various cryptographic encryption techniques such as AES and DES are available to provide confidentiality, the key size and the key sharing are the main problems to provide a worthy level of security. Hence, an efficient affine cipher-based encryption technique is proposed in this paper to offer a high level of confidentiality with smaller key size compared to existing encryption techniques. The security strength of the proposed work against various harmful security attacks is proven in security analysis section to ensure that it provides better security. The storage cost, communication cost and computational cost of the proposed scheme are demonstrated in the performance analysis section elaborately. In connection to this, the computational complexity of the proposed scheme is reduced around 29% compared to the existing scheme.

IEVCA: An efficient image encryption technique for IoT applications using 2-D Von-Neumann cellular automata

Present era is marked by exponential growth in transfer of multimedia data through internet. Most of the Internet-of-Things(IoT) applications send images to cloud storages through internet. However, in sensitive applications such as healthcare, defense, etc., these images should be encrypted before transmission through insecure public channels to gateway fog nodes. Conventional encryption algorithms cannot be used there due to the resource constraint characters of IoT devices. Here, Cellular Automata (CA) based encryption algorithms can be used because of their inherent simplicity in implementation in hardware, without affecting the capability of generating highly random sequences. In this paper, a lightweight, robust and secure image encryption technique has been proposed using 2-D Von-Neumann Cellular Automata (VCA), called IEVCA, which is lossless, correlation immune and has all the essential properties of a good image cipher. Additionally, the proposed technique passes all the randomness tests of DIEHARD and NIST statistical test suites. Moreover, several security and performance analyses of the IEVCA proved its efficiency and resistance against security attacks. Experimental results of the IEVCA show its better performance when compared to the existing encryption techniques.

Survey on Security Performance of Fog Computing and Existing Encryption Techniques

Survey on Security Performance of Fog Computing and Existing Encryption Techniques

Packet Encryption for Securing Real-Time Mobile Cloud Applications

The evolution of smart devices has brought the most confidential data to mobile applications and cloud computing with its processing power is serving the huge processing requirements of these applications. However, these advancements has brought in serious data security concerns, as there is constant shuttling of data from devices to cloud and backforth, and encryption is the most commonly used technique for securing data in transmission. Every encryption technique is breakable, but its efficiency is calculated with the time it can withstand an attack. But in today’s world, as cloud computing comes with almost unlimited computing resources, the present day encryption techniques might become inadequate for securing confidential data in transmission and after transmission. Existing encryption techniques, encrypt the whole data packets in a session using the same session key. If a third party can decrypt a single packet during or after transmission, all the packets in that session can be compromised. This work proposes a packet encryption scheme, where a packet key once used will never be used throughout the session, with minimal latency and maximum security for real-time mobile cloud applications.

Fourier–Mellin moment-based intertwining map for image encryption

In this paper, a robust image encryption technique that utilizes Fourier–Mellin moments and intertwining logistic map is proposed. Fourier–Mellin moment-based intertwining logistic map has been designed to overcome the issue of low sensitivity of an input image. Multi-objective Non-Dominated Sorting Genetic Algorithm (NSGA-II) based on Reinforcement Learning (MNSGA-RL) has been used to optimize the required parameters of intertwining logistic map. Fourier–Mellin moments are used to make the secret keys more secure. Thereafter, permutation and diffusion operations are carried out on input image using secret keys. The performance of proposed image encryption technique has been evaluated on five well-known benchmark images and also compared with seven well-known existing encryption techniques. The experimental results reveal that the proposed technique outperforms others in terms of entropy, correlation analysis, a unified average changing intensity and the number of changing pixel rate. The simulation results reveal that the proposed technique provides high level of security and robustness against various types of attacks.