Elliptic Curve Cryptography Algorithm Research Articles

Performance Evaluation of AES, ECC and Logistic Chaotic Map Algorithms in Image Encryption

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 n these days of technology, the usage of images has become increasingly high especially now that almost everyone has access to internet. Also, image helps us to learn, grabs our attention, explains complicated concepts as well as inspires us. Sharing these images is essential and therefore image encryption algorithms are proposed to secure the transmission of these image from many types of attacks such as Man-in-the-middle attack (MITM). In this paper, we proposed a hybrid security system that consist of Elliptic Curve Cryptography (ECC) and Advanced Encryption System (AES). Where ECC is used to generate private/public keys and AES is for encryption and decryption of the image using the ECC generated keys. The system works as follows; it begins by inserting the image to be encrypted which is “lena.png” of size 256*256 and passing it to AES Algorithm along with the generated public key. Then, in AES algorithm, the public key is hashed then used to encrypt the image with AES encryption algorithm. On the other hand, the decryption algorithm works as follows; inserting the encrypted image then calculating the decryption key to use it to decrypt the image using AES decryption algorithm. Finally, our experimental results shows that the National Institute of Standards and Technology (NIST) test shows that the ECC generated keys have better randomness than using only AES generated keys. Also, the encrypted image histogram show that the image pixels values are well distributed across all three channels R, G and B. This shows that the hybrid system is a step further to get a more secure image encryption system against attacks with the generated ECC keys. To get further, Logistic chaotic map has been used to encrypt images for comparison purposes with AES and ECC generated images in terms of randomness, security and histogram

FPGA Implementation for Elliptic Curve Cryptography Algorithm and Circuit with High Efficiency and Low Delay for IoT Applications.

The Internet of Things requires greater attention to the security and privacy of the network. Compared to other public-key cryptosystems, elliptic curve cryptography can provide better security and lower latency with shorter keys, rendering it more suitable for IoT security. This paper presents a high-efficiency and low-delay elliptic curve cryptographic architecture based on the NIST-p256 prime field for IoT security applications. A modular square unit utilizes a fast partial Montgomery reduction algorithm, demanding just a mere four clock cycles to complete a modular square operation. The modular square unit can be computed simultaneously with the modular multiplication unit, consequently improving the speed of point multiplication operations. Synthesized on the Xilinx Virtex-7 FPGA platform, the proposed architecture completes one PM operation in 0.08 ms using 23.1 k LUTs at 105.3 MHz. These results show significantly better performance compared to that in previous works.

Iot Based Alzheimer’s Disease Diagnosis Model for Providing Security Using Light Weight Hybrid Cryptography

Security in the Internet of things (IoT) is a broad yet active research area that focuses on securing the sensitive data being circulated in the network. The data involved in the IoT network comes from various organizations, hospitals, etc., that require a higher range of security from attacks and breaches. The common solution for security attacks is using traditional cryptographic algorithms that can protect the content through encryption and decryption operations. The existing solutions are suffering from major drawbacks, including computational complexities, time and space complexities, slower encryption, etc. Therefore, to overcome such drawbacks, this paper introduces an efficient light weight cryptographic mechanism to secure the images of Alzheimer’s disease (AD) being transmitted in the network. The mechanism involves major stages such as edge detection, key generation, encryption, and decryption. In the case of edge detection, the edge maps are detected using the Prewitt edge detection technique. Then the hybrid elliptic curve cryptography (HECC) algorithm is proposed to encrypt and secure the images being transmitted in the network. For encryption, the HECC algorithm combines blowfish with the elliptic curve algorithm to attain a higher range of security. Another significant advantage of the proposed method is selecting the ideal private key, which is achieved using the enhanced seagull optimization (ESO) algorithm. The proposed work has been tested in the Python tool, and the performance is evaluated with the Alzheimer’s dataset, and the outcomes proved its efficacy over the compared methods.

Intrusion detection model using optimized quantum neural network and elliptical curve cryptography for data security

Secure data transmission in wireless mesh networks is a necessary attribute for machine learning-based intrusion detection systems (IDS). Numerous attacks may have an adverse effect on the system's computing efficiency. In order to accurately detect an attack and enable data protection, Whale with Cuckoo search optimization (WCSO) based quantum neural network (QNN) and elliptical curve cryptography (ECC) is presented. Whale optimization algorithm (WOA) is used to choose the features in the network data that aid in precisely detecting intrusions. To identify attacks, the optimized quantum network which combines the WOA approach with the feed-forward and backpropagation algorithms, is used. Sensitive data retrieving requires an encryption procedure that is enabled by the ECC algorithm, which could safely save the data files in the server, in order to, secure the documentation with security measures. In the event that the data owner maintains sensitive data on a server, the document is encrypted using the encryption method. To determine the best key optimized ECC is used. The QNN with WOA-based IDS framework is a solid option for real-time intrusion detection analysis with high accuracy of 98.5%. Thus, the study has demonstrated that the suggested effort will also provide better secure data storage, resolving security concerns.

ECC-Based Authenticated Key Agreement Protocol for Industrial Control System

Nowadays, Industrial Internet of Things (IIoT) technology has made a great progress and the industrial control systems (ICSs) have been used extensively, which has brought more and more serious information security threats to the ICS at the same time. The authenticated key agreement (AKA) protocol is a common method to ensure the communication security. This work proposes a lightweight AKA protocol based on the elliptic curve cryptography (ECC) algorithm to adapt to the resource-constrained environment. We only employ hash operation, XOR operation, and ECC algorithm to encrypt the data in the authentication and key agreement phase, and avoid involving the register center while proceeding the key agreement, to give consideration to both performance and security. The security analyses indicate that our protocol can meet nine critical security requirements, more than all of the existing protocols, and the performance analysis carried out indicates that our protocol has less computational and communication overheads in contrast to other corelative protocols.

Improving the IoT and Cloud Computing integration using Hybrid Encryption

Wireless Sensor Network (WSN) is an essential technology in many Internet of Things (IoT) applications, and since sensor nodes suffer from limited resources, it has become possible to overcome storage capacity problems using cloud computing, the integration of Internet of Things (IoT) with cloud computing (CC) seeks to achieve new levels of efficiency in service delivery. Security and privacy are key factors that slow down the rapid and widespread adoption and deployment of both IoT and cloud computing. In the proposed model, an integrated IoT system with cloud computing was developed starting from the analysis, and design, to the implementation to connect IoT devices with the cloud, the security is achieved by using a hybrid encryption mechanism which provides the performance advantages of symmetric and asymmetric encryption algorithms. Where the Elliptic Curve Cryptography (ECC) algorithm is used for key generation and AES (Advanced Encryption Standard) algorithm is used for encryption and decryption of the sensors' data to provide a reliable computing environment. We have implemented the proposed system and showed the results of using CONTIKI COOJA 3.0 that connected with the cloud service provider, Evaluate a set of performance metrics such as power consumption, packet delivery ratio, and the algorithm execution time, in addition to verifying network immunity against the black hole attack.

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.

Hybrid Security Model for Medical Image Protection in Cloud

A cloud computing environment provides a cost-effective way for end-users to remotely store and retrieve private data through an internet connection anytime and anywhere. The security of these data cannot always be guaranteed because they can only be accessed by the end-user through a third-party interface, making them vulnerable to potential breaches of authentication and data integrity. This paper presents a secure hybrid approach for a medical image stored in the cloud that prioritizes data security and integrity. The suggested model employs a combination of Elliptic Curve Cryptography (ECC) and Advanced Encryption Standard (AES) algorithms to ensure authentication and data integrity. The results demonstrate its superiority over existing methods making the proposed model compliant with regulations of sensitive data stored in the cloud, such as the Health Insurance Portability and Accountability Act (HIPAA) and General Data Protection Regulation (GDPR) that dictate how personal information must be handled, stored, and processed. By contrast with traditional and other hybrid systems, this paper can conclude that this is one of the best methods to guarantee the security of medical images in the cloud.

Enhancing Cloud Forensic Investigation System in Distributed Cloud Computing Using DK-CP-ECC Algorithm and EK-ANFIS

The investigation as well as recovery of data gathered as of digital devices associated with computer crime is involved in Digital Forensics (DF). In a distributed Cloud Server (CS), DF investigation is more complicated (during collecting, preserving, and reporting the evidence) as well as insecure during gathering evidence as of the cloud sources. Centered on the DF investigation system, numerous works were performed. However, lots of challenges still remain that bring about cybercrime. The work developed a robust cloud forensic investigation system centered upon distributed Cloud Computing (CC) for conquering the challenges. It is framed into the ‘3’ phase (i.e.) originally, Group Key Generation (GKG) phase that enables the authorized user to upload or download the evidence for maintaining the evidence’s trustworthiness. Distributed Key Cipher Policy Elliptic Curve Cryptography (DK-CP-ECC) algorithm performed the Secure Data Transfer (SDT) phase. It aids in maintaining the evidence’s privacy together with confidentiality. Exponential Membership Function Adaptive Neuro-Fuzzy Interference System (EK-ANFIS) carries out the CS selection with the aid of a deer hunting genetic algorithm that evades the reporting issues and renders secure evidence storage. 97% Security Level (SL) is obtained by the proposed work that is better analogized to the prevailing frameworks.

A security model to protect the isolation of medical data in the cloud using hybrid cryptography

A cloud computing platform delivers a cost-efficient path for cloud users to store and access data privately over remote storage via an Internet connection. Medical data is stored in the cloud since it is scalable, secure, reliable, provides ubiquitous access, and is highly available. It is required to be isolated in terms of physical, network, and operational for protecting data from internal threats or external cyber-attacks. It can be achievable through hybrid cryptography in which symmetric, as well as asymmetric cryptosystem, is being utilized. To assure the confidentiality and integrity of medical data, an improved Robust S-box-based Advanced Encryption Standard (IRS-AES) is proposed with Runge-Kutta Optimization (RKO) algorithm. RKO generates an enhanced and secured RS-box through the computation of the Mackey-Glass equation. Initially, the medical data are compressed using Improved Huffman Coding (IHC). The Deoxyribonucleic Acid (DNA)-based Modified Elliptic Curve Cryptography (MECC) algorithm is introduced for key generation, and the best key is selected with Bald Eagle Search optimization (BES) algorithm. Finally, the medical data are encrypted IRS-AES algorithm and stored in the cloud. The proposed RS-box security strength is evaluated using non-linearity, Strict Avalanche Criterion (SAC), Differential Probability (DP), Bit Independence Criterion (BIC), and Linear Probability (LP) parameters. The efficiency of the proposed algorithm is evaluated with image, audio, and video dataset. The evaluation metrics such as communication overhead, file upload time, computational cost, Mean Square Error (MSE), encryption and decryption time, Peak Signal-to-Noise Ratio (PSNR), key generation time, and Signal-to-Noise Ratio (SNR) are used for validating the proposed approach. The performance of the proposed approach is enhanced with the communication overhead of 11.51 for the image dataset. MSE and PSNR obtained are 16.2 and 8.465 for an audio dataset, 75.21 and 3.5 for the video dataset.

Logistic Regression with Elliptical Curve Cryptography to Establish Secure IoT

Nowadays, Wireless Sensor Network (WSN) is a modern technology with a wide range of applications and greatly attractive benefits, for example, self-governing, low expenditure on execution and data communication, long-term function, and unsupervised access to the network. The Internet of Things (IoT) is an attractive, exciting paradigm. By applying communication technologies in sensors and supervising features, WSNs have initiated communication between the IoT devices. Though IoT offers access to the highest amount of information collected through WSNs, it leads to privacy management problems. Hence, this paper provides a Logistic Regression machine learning with the Elliptical Curve Cryptography technique (LRECC) to establish a secure IoT structure for preventing, detecting, and mitigating threats. This approach uses the Elliptical Curve Cryptography (ECC) algorithm to generate and distribute security keys. ECC algorithm is a light weight key; thus, it minimizes the routing overhead. Furthermore, the Logistic Regression machine learning technique selects the transmitter based on intelligent results. The main application of this approach is smart cities. This approach provides continuing reliable routing paths with small overheads. In addition, route nodes cooperate with IoT, and it handles the resources proficiently and minimizes the 29.95% delay.

A Flexible Architecture for Cryptographic Applications: ECC and PRESENT

This work presents a flexible/unified hardware architecture of Elliptic-curve Cryptography (ECC) and PRESENT for cryptographic applications. The features of the proposed work are (i) computation of only the point multiplication operation of ECC over for a 163-bit key generation, (ii) execution of only the variant of an 80-bit PRESENT block cipher for data encryption & decryption and (iii) execution of point multiplication operation (ECC algorithm) along with the data encryption and decryption (PRESENT algorithm). To establish an area overhead for the flexible design, dedicated hardware architectures of ECC and PRESENT are implemented in the first step, and a sum of their hardware area is computed. Then, the implementation of the proposed flexible architecture for ECC and PRESENT algorithms is presented. Implementation results regarding the area, clock cycles, latency, clock frequency, and power after the place-and-route level on Xilinx Virtex-5, Virtex-6, and Virtex-7 FPGA devices are presented. Hence, the implementation results and comparisons show that the proposed architecture suits applications demanding flexible implementation of cryptographic applications.

BSDCE-IoV: Blockchain-Based Secure Data Collection and Exchange Scheme for IoV in 5G Environment

The Internet of Vehicles (IoV) is a network that connects vehicles and their environment: in-built devices, pedestrians, and infrastructure through the Internet using heterogeneous access technologies. During communication between vehicles, roadside units, and control rooms, data confidentiality and privacy are critical issues that require effective measures. Several works have been proposed for securing IoV environments based on vehicles-to-infrastructure authentication; However, some schemes have security vulnerabilities, while others have shown efficiency issues. Due to its decentralization, stability, and transaction tracking capabilities, Blockchain as an emerging technology presents a potential solution for IoV security. This article provides an in-depth examination of the benefits of blockchain for a 5G-based IoV environment. In particular, we propose and evaluate a novel blockchain-based secure data exchange (BSDCE-IoV) scheme based on Elliptic Curve Cryptography algorithm. Our solution is designed to eliminate several potential attacks that pose a threat to the IoV environment. Deep examination using the Real-or-Random oracle model and Scyther tool, in addition to the informal security analysis, validates the scheme regarding security and privacy. The Multi-precision Integer and Rational Arithmetic Cryptographic Library (MIRACL) assesses the computational and communication overhead. Computational and communicative overheads were also evaluated using the Multi-precision Integer and Rational Arithmetic Cryptographic Library (MIRACL). BSDCE-IoV shows higher performance in terms of security, functionality, and time delay than a number of recent selective work in IoV security.

Multi-Functional Resource-Constrained Elliptic Curve Cryptographic Processor

With the rising data evolution, the demand for secured communications over networks is rising immensely. Elliptic Curve Cryptography (ECC) provides an attractive solution to fulfill the requirements of modern network applications. Many proposals published over the year over different variants of ECC satisfied some of the issues. Nevertheless, modern network applications such as Internet-of-Thing (IoT) and Software-Defined Networking (SDN) put the requirements on various aspects and can only be solved by different ECC algorithms. Looking at this point of view, an efficient architecture that could combine multiple ECC algorithms becomes an urgent request. In addition, even though many investigations of ECC on Field-Programmable Gate Arrays (FPGA), an efficient architecture that could be well-deployed on Application-Specific Integrated Circuit (ASIC) needs to get more study. Therefore, this paper proposes an area-efficient ECC hardware design that could integrate multiple ECC algorithms. The proposed design is deployed on both ASIC and FPGA platforms. Four well-known ECC-based Digital Signature Algorithms (DSAs), which are the Edwards-curve Digital Signature Algorithm (EdDSA) with Curve25519, Elliptic Curve Digital Signature Algorithm (ECDSA) with National Institute of Standards and Technology (NIST) Curve P-256, P-384, and P-521, are implemented. Furthermore, the design supports all DSA schemes: public-key generation, signature generation, and verification. We also provide optimized calculation flows for modular multiplication, modular inversion, point addition, point doubling, and Elliptic Curve Point Multiplication (ECPM) for two different elliptic curves: the NIST curve and Edward curve, on a unique architecture. The calculation processes are designed in projective coordinates and optimized in time and space to achieve a high level of parallelism. The proposed ECC processor could run up to 102-MHz on ASIC 180-nm and 109.7-MHz on Xilinx Virtex-7. In terms of area, The processor occupies 377,471 gates with 4.87- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$mm^{2}$ </tex-math></inline-formula> on the ASIC platform and 11,401 slices on the FPGA platform. The experimental results show that our combinational design achieves area-efficient even when compared with other single-functional architecture on both ASIC and FPGA.

Cryptographic Algorithm for Enhancing Data Security in Wireless IoT Sensor Networks

Wireless IoT Sensor Network can handle audio, video, text, etc., through the interconnection of ubiquitous devices. The entertainment and application-centric network relies on its autonomous nodes for handling large streams of multimedia data. Security breaches and threats due to insider attacks reduce the data handling and distribution capacity of the nodes. For addressing the insider attacks problem, Session-Critical Distributed Authentication Method (SCDAM) is proposed. The proposed method relies on short-lived concealed authentication based on an improved elliptic curve cryptography (ECC) algorithm. In this authentication, the session time and the interrupts are accounted for, providing end-to-end authentication. The session keys are distributed before and after each interrupt from which the shared data is authenticated. This authentication process uses a linear hash process, ensuring non-repetition of keys in the consecutive sessions. This proposed authentication method is capable of providing improved sessions, less data distribution loss, and complexity.

File Encryption Application using Menezes-Vanstone Elliptic Curve Cryptography Based on Python

Humans have been affected by the advent of information technology in many different ways. Information can be sent freely as a result of the conveniences offered. However, unauthorized parties may take advantage of this to retrieve and utilize the information without the owner's consent. In this paper, the authors perform text, image, audio, and video data security using a modified version of the Menezes-Vanstone elliptic curve cryptography algorithm. The study implements Menezes-Vanstone Elliptic Curve Cryptography in a program for file text, image, audio, and video encryption and decryption, while also providing performance data for both our program and alternative approaches for comparison. The outcome demonstrates that the encrypted file size is smaller than alternative approaches. Nevertheless, our program might benefit from some enhancements in terms of encryption and decryption times.

Improvement of the Secure Integration of IoT and Cloud Computing using Hybrid Encryption

Wireless Sensor Network (WSN) is an essential technology in many Internet of Things (IoT) applications, and since sensor nodes suffer from limited resources, it has become possible to overcome storage capacity problems using cloud computing, the integration of Internet of Things (IoT) with cloud computing (CC) seeks to achieve new levels of efficiency in service delivery. Security and privacy are key factors that slow down the rapid and widespread adoption and deployment of both IoT and cloud computing. In the proposed model, an integrated IoT system with cloud computing was developed starting from the analysis, and design, to the implementation to connect IoT devices with the cloud, the security is achieved by using a hybrid encryption mechanism which provides the performance advantages of symmetric and asymmetric encryption algorithms. Where the Elliptic Curve Cryptography (ECC) algorithm is used for key generation and AES (Advanced Encryption Standard) algorithm is used for encryption and decryption of the sensors' data to provide a reliable computing environment. We have implemented the proposed system and showed the results of using CONTIKI COOJA 3.0 that connected with the cloud service provider, Evaluate a set of performance metrics such as power consumption, packet delivery ratio, and the algorithm execution time, in addition to verifying network immunity against the black hole attack.

Privacy-Aware Secure Routing through Elliptical Curve Cryptography with Optimal RSU Distribution in VANETs

Vehicular Ad-Hoc Networks (VANETs) are the backbone of the intelligent transportation system, which consists of high-speed vehicles with huge dynamic mobility. The communication takes place with a vehicle-to-vehicle, vehicle to infrastructure, with traffic signals. The major flaw of this kind of network is that due to high mobility in VANETs, the communication overhead is so high that it directly affects the efficiency of the network. Security is also holding a vital role in VANETs. The attackers can easily capture vehicle details of this type. To overcome this drawback, security should also need to get improved. This paper introduces Elliptical Curve Cryptography with Generic Algorithm based Privacy-Aware Secure Routing (ECC-GA-PASR), which is the combination of two methods such as optimal RSU distribution and elliptical curve cryptography (ECC) based authentication. RSU distribution is optimized by using the generic algorithm (GA) as well as to improve the authentication in trusted authority (TA) ECC algorithm is used. By using these two concepts, the proposed method reduced the communication overhead and increased the security of the network. The simulation is conducted throughput NS2 and SUMO. The performance analysis is performed concerning vehicle count, varying speed, and malicious activities. The parameters that are concentrated for this performance analysis are energy efficiency, packet delivery ratio, overhead, and packet loss. The performance of the proposed method is calculated and compared with earlier works such as S-AODV, ES-AODV, and ECC-ACO-AODV. Compared with the earlier works, the proposed ECC-GA-PASR produced 15% better efficiency, 12% better packet delivery ratio, 50% lower overhead, and 30% lower packet loss.

Speeding-Up Elliptic Curve Cryptography Algorithms

In recent decades there has been an increasing interest in Elliptic curve cryptography (ECC) and, especially, the Elliptic Curve Digital Signature Algorithm (ECDSA) in practice. The rather recent developments of emergent technologies, such as blockchain and the Internet of Things (IoT), have motivated researchers and developers to construct new cryptographic hardware accelerators for ECDSA. Different types of optimizations (either platform dependent or algorithmic) were presented in the literature. In this context, we turn our attention to ECC and propose a new method for generating ECDSA moduli with a predetermined portion that allows one to double the speed of Barrett’s algorithm. Moreover, we take advantage of the advancements in the Artificial Intelligence (AI) field and bring forward an AI-based approach that enhances Schoof’s algorithm for finding the number of points on an elliptic curve in terms of implementation efficiency. Our results represent algorithmic speed-ups exceeding the current paradigm as we are also preoccupied by other particular security environments meeting the needs of governmental organizations.

Throughput Analysis and Data Sharing Technique to Assess the Impact of Blockchain Technology using Cryptographic Algorithm

Blockchain is a data structure made up of chronologically ordered data blocks. Research revealed that traditional blockchains have constrained throughput. It is ideal for blockchain technology to achieve higher throughput by increasing the block size and lessening the block interval. The methodology used in this paper is of two parts. The first approach uses the cryptographic protocol to ensure the authenticity and integrity of the information using an Ethereum blockchain type. This means that transactions are recorded in write-only mode and contributes to transaction trust and transparency. Our methodology automates smart and secure evaluations and provides credentials using an Improved Elliptic Curve Cryptography Algorithm (IECCA). It is implemented using encryption and decryption algorithms and is demonstrated using analytical and content neutrality. We also demonstrate operation from back-end to end-users application including student and faculty members. The Level of security performance of the proposed scheme is compared with another scheme for a 20MB file size. The proposed schemes achieve 83% IECCA, 78 percent DES, 76% RSA, and 70% AES respectively. The second approach identifies the boundary for conventional block sizes and block intervals. Security of blockchain using stale block rate is identified in the network by conducting a realistic experiment. This enables the realization of optimal block parameters like size and interval. Results presents achieve a rate of transmission for a blockchain platform to be deployed in other activities beyond cryptocurrency, like electronic voting.