Asymmetric Encryption Research Articles

Adaptive Deep Ant Colony Optimization–Asymmetric Strategy Network Twin Delayed Deep Deterministic Policy Gradient Algorithm: Path Planning for Mobile Robots in Dynamic Environments

Path planning is one of the main focal points and challenges in mobile robotics research. Traditional ant colony optimization (ACO) algorithms encounter issues such as low efficiency, slow convergence, and a tendency to become stuck in local optima and search stagnation when applied to complex dynamic environments. Addressing these challenges, this study introduces an adaptive deep ant colony optimization (ADACO) algorithm, which significantly improves efficiency and convergence speed through enhanced pheromone diffusion mechanisms and updating strategies, applied to global path planning. To adapt to dynamically changing environments and achieve more precise local path planning, an asymmetric strategy network TD3 algorithm (ATD3) is further proposed, which utilizes global path planning information within the strategy network only, creating a new hierarchical path planning algorithm—ADACO-ATD3. Simulation experiments demonstrate that the proposed algorithm significantly outperforms in terms of path length and number of iterations, effectively enhancing the mobile robot’s path planning performance in complex dynamic environments.

An Enhanced Learning with Error-Based Cryptosystem: A Lightweight Quantum-Secure Cryptography Method

Quantum-secure cryptography is a dynamic field due to its crucial role in various domains. This field aligns with the ongoing efforts in data security. Post-quantum encryption (PQE) aims to counter the threats posed by future quantum computers, highlighting the need for further improvement. Based on the learning with error (LWE) system, this paper introduces a novel asymmetric encryption technique that encrypts entire messages of n bits rather than just 1 bit. This technique offers several advantages including an additive homomorphic cryptosystem. The robustness of the proposed lightweight public key encryption method, which is based on a new version of LWE, ensures that private keys remain secure and that original data cannot be recovered by an attacker from the ciphertext. By improving encryption and decryption execution time—which achieve speeds of 0.0427 ms and 0.0320 ms, respectively—and decreasing ciphertext size to 708 bits for 128-bit security, the obtained results are very promising.

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.

Asymmetric Spatiotemporal Online Learning for Deep Spiking Neural Networks

Although the precise symmetric forward and feedback connections between neurons are thought to be impossible in the brain, most existing deep spiking neural networks (SNNs) spatio-temporal learning algorithms still require such a strong architectural constraint to complete tasks. Besides that, as an expected feature for specialized neuromorphic hardware to be deployed, effective online learning of deep SNNs for training spatio-temporal data are still lacking. To address these issues, an effective biologically plausible asymmetric spatio-temporal online learning algorithm called ASTOL is proposed for training deep SNNs in real-time. ASTOL could learn the spatial and temporal features simultaneously in real-time, without the precise weights symmetric backpropagation and the need to know the duration of spatio-temporal data in advance. Experimental results show that the proposed ASTOL algorithm achieves comparable performance in real-time learning on the rate coding MNIST dataset and the temporal coding music MedleyDB dataset and speech TIDIGITS dataset with other state-of-the-art algorithms with simpler learning mechanism way as it avoids transport of synaptic weights. Besides that, the experiment on MNIST datasets also shows that ASTOL can use simpler network structures to achieve good performance faster.

Precisely regulation of photochromism via absorption-induced photoreaction attenuation and light intensity dependence for time-resolved asymmetric encryption

With the growing need for secure information storage, encryption materials are required to be designed with high information capacity, easy to prepare, and hard to decode. Here, donor–acceptor Stenhouse adducts (DASAs), known for their straightforward synthesis, are used to develop a new time-resolved asymmetric encryption strategy, enhancing information capacity. The photoswitching property of DASAs is regulated by the intensity of initial absorbance and the intensity of light irritation. Besides, we recognize the relationship between the intensity of initial absorbance and photoswitching rate constant is caused by the absorption-induced photoreaction attenuation (AIPA). By rationally regulating the photo-bleching time of DASAs, the information can be sequentially revealed (colored state) or concealed (bleached state) in the desired temporal order. As a result, a quick response (QR) code label for practical application and a multi-level encoding scheme for sophisticated asymmetric encryption have been proposed. Specifically, the advanced asymmetric encryption technique employs layer sequence and light intensity as private keys, diverging from traditional public key systems. Information is sequentially displayed over time. The accurate information can only be revealed at the correct temporal dimension (layer sequence) and the appropriate decoding parameter (light intensity), both of which are precisely controlled by AIPA. This study not only unveils an approach to time-resolved asymmetric encryption using DASAs, enhancing the security and capacity of information storage, but also paves the way for the development of high-security encryption materials that are both highly efficient and resistant to unauthorized decoding efforts.

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.

Blockchain-based security-minded information-sharing in precast construction supply chain management with scalability, efficiency and privacy improvements

Blockchain and Interplanetary File System (IPFS) integration holds great promise for enhancing transparency and traceability in precast construction supply chain management (PCSCM). However, such integration faces challenges regarding unauthorized access to confidential data, which can lead to significant consequences, such as financial losses and legal issues. Regarding this gap, this paper proposes a hybrid privacy-preserving access control mechanism for securing blockchain-IPFS information-sharing in PCSCM with confidentiality considerations. Multiple privacy-preserving techniques (e.g., information-sharing channels, symmetric and asymmetric encryption, and lightweight proxy re-encryption) are leveraged. A prototype system demonstrates its feasibility and effectiveness, achieving demonstrably low network latency (millisecond level), efficient encryption (millisecond level), and robust data security within both blockchain and IPFS. This research contributes to a deeper understanding of blockchain-IPFS integration and provides a valuable reference point for future research and practical adoption.

Blockchain-Machine Learning Fusion for Enhanced Malicious Node Detection in Wireless Sensor Networks

In wireless sensor networks (WSNs), the presence of malicious nodes (MNs) poses significant challenges to data integrity, network stability, and system reliability. These issues are intensified by energy resource constraints and limitations within centralized authentication systems, necessitating an energy-efficient solution to ensure real-time responsiveness. Although artificial intelligence-driven approaches enhance detection capabilities, they overcome challenges related to data volume, coordination overhead, and latency in centralized control. This study introduces blockchain-machine learning (BC-ML), a novel hybrid model that seamlessly integrates blockchain and machine learning (ML) techniques to effectively identify MNs in WSNs. The model establishes an energy-efficient blockchain among cluster heads (CHs) for robust node authentication, incorporating a Schnorr-like zero-knowledge-proof technique to validate node data during communication initiation. Utilizing a hybrid lightweight approach with both symmetric and asymmetric ciphers enhances the security of node data transmission. A new proof-of-authority method is introduced, which leverages node digital certificates instead of conventional data transactions. This consensus mechanism reduces the processing overhead associated with larger data sizes in traditional proof-of-work methods, thereby improving both energy efficiency and scalability. To address dataset imbalances, the model employs a hybrid unsupervised ML technique, combining adaptive synthetic sampling with a convolutional neural network for efficient analysis of nodes and network features. The ML model, hosted on a robust data server, ensures ongoing oversight by updating CHs with security levels for detected MNs, thereby reducing storage and mitigating coordination challenges. Comprehensive analyses validate the effectiveness of the BC-ML model for detecting MNs, optimizing resource utilization, minimizing delays, and prolonging node and network lifetimes. Security analysis further confirms the ability of the model to mitigate diverse attacks and meet the stringent WSN security requirement.

Asymmetry index for data and its verification in dimensionality reduction and data visualization

We propose an asymmetry index as a measure of degree of asymmetry of a given dataset. It provides an additional information on a dataset allowing to guide and improve any further analysis. The index reflects the intensity of the asymmetric relationships among data resulting from hierarchical data structure. Using the information retrieved by our asymmetry index, one obtains a justification and explanation of the effectiveness of the subsequent asymmetric data analysis methods, as well as helpful preparation to asymmetrizing the tools for the further analysis. The asymmetry index is based on the k-nearest neighbors graph representing the considered data. Therefore, it uses the intrinsic geometry-based information on the data, in this way, providing an insight into the data structure. Our experiments on real data are designed to verify the usefulness of the asymmetry index and the correctness of its theoretical fundamentals. In our empirical validation, we employ the symmetric and asymmetric dimensionality reduction algorithms and evaluate their results on the basis of clustering in the 2-dimensional visualization space. We test, whether our index indeed predicts the level of superiority of the asymmetric methods over their symmetric counterparts.

An Efficient Image Encryption Scheme for Medical Image Security

In the contemporary landscape of digital healthcare, the confidentiality and integrity of medical images have become paramount concerns, necessitating the development of robust security measures. This research endeavors to address these concerns by proposing an innovative image encryption scheme tailored specifically for enhancing medical image security. The proposed scheme integrates a sophisticated blend of symmetric and asymmetric encryption techniques, complemented by a novel key management system, to fortify the protection of medical image data against unauthorized access and malicious tampering. The proposed DNA-based encryption algorithm leverages the unique properties of DNA encoding to securely scramble image data, providing an added layer of protection. By utilizing DNA sequences in the encryption and decryption processes, the scheme achieves a high level of data confusion and diffusion, significantly enhancing security. The efficacy of the proposed encryption scheme is validated through comprehensive experimental evaluations, which demonstrate its proficiency in ensuring data security while maintaining computational efficiency. The scheme's compatibility with existing medical imaging systems is also examined, affirming its seamless integration into contemporary healthcare infrastructures. This research contributes to the advancement of medical image security by proposing an efficient encryption scheme that strikes a balance between stringent security requirements and practical implementation considerations. The primary contributions include the development of a DNA-based encryption algorithm and a novel key management system, both of which significantly enhance the security of medical images. This research contributes to the advancement of medical image security by proposing an efficient encryption scheme that strikes a balance between stringent security requirements and practical implementation considerations. By safeguarding the confidentiality and integrity of medical images, the proposed scheme empowers healthcare providers to uphold patient privacy and trust in the digital age. Experimental results show that this approach ensures robust encryption without compromising image quality, making it suitable for sensitive medical imaging applications.

Authentication communication by using visualization cryptography for UAV networks

Utilizing unmanned aerial vehicles (UAVs) to support V2X requirements leverages their versatility and line-of-sight communication. Our prior work explored a multi-agent learning approach for resource optimization, maximizing task offloading while maintaining QoS. This paper focuses on securing UAV communication, particularly authentication. Traditional methods are often unsuitable due to UAV limitations. We propose a novel authentication mechanism for a single ground control station (GCS) interacting with multiple UAVs across flight sessions. The system utilizes a key generation method based on chaotic maps to create unique flight session keys for each pre-defined flight plan. These keys, along with flight plans, are registered in a secure database. During flight, the GCS verifies UAV identity by employing the flight session key and corresponding flight plan for message authentication. This approach reduces computational and communication overhead compared to traditional certificate exchanges and asymmetric cryptography, which are energy-intensive for UAVs. While not a comprehensive security solution, this method provides an initial layer of protection for the UAV network.

The Enablers and Interdependencies of Blockchain Technology in Supply Chain Management: Evidence From Luxury Products

ABSTRACTBlockchain is a technology that combines a set of properties to guarantee network security, transparency, and visibility, including a decentralized structure, distributed notes and storage mechanism, consensus algorithm, intelligent contracts, and asymmetric encryption. Supply chain management activities, including supply chain management provenance, business process reengineering, and security enhancement, have enormous potential to be transformed by blockchain. This research uses the integrated interpretive structural modeling–cross‐impact matrix multiplication applied to classification (ISM‐MICMAC) technique to ascertain the hierarchical relationships and to comprehend the severity of interrelationships among various components in tackling our research questions. In MICMAC analysis, the enablers were classified into four categories based on their dependence and driving powers. The combined ISM‐MICMAC methodology employed for this study relies on experts’ individual evaluations and subjective assessments. Therefore, even with extreme caution, it is impossible to guarantee that the results are entirely devoid of personal biases. To further validate the linkages discovered in this study, we suggest employing more multiple‐criteria decision‐making (MCDM) methodologies and comparing the results with those of our research. Another method for confirming the results of the current study is to use an empirical research design based on survey methods.

An asymmetric key encryption and decryption model incorporating optimization techniques for enhanced security and efficiency

An asymmetric key encryption and decryption model incorporating optimization techniques for enhanced security and efficiency

Extended version—to be, or not to be stateful: post-quantum secure boot using hash-based signatures

AbstractWhile research in PQC has gained significant momentum, its adoption in real-world products is slow. This is largely due to concerns about practicability and maturity. The secure boot process of embedded devices is one scenario where such restraints can result in fundamental security problems. In this work, we present a flexible hardware/software co-design for HBS schemes which enables the transition to a post-quantum secure boot today. These signature schemes stand out due to their straightforward security proofs and are on the fast track to standardisation. Unlike previous work, we exploit the performance intensive similarities of the stateful LMS and XMSS schemes as well as the stateless $$\text {SPHINCS}^{+}$$ SPHINCS + scheme. Thus, we enable designers to use a stateful or stateless scheme depending on the constraints of each individual application. To demonstrate the feasibility of our approach, we compare our results with hardware accelerated implementations of classical asymmetric algorithms. Further, we outline the use of different HBS schemes during the boot process. We compare different schemes, show the importance of parameter choices, and demonstrate the performance gain with different levels of hardware acceleration.

An efficient blockchain-based framework for file sharing

File sharing, being the foundation of the Internet, has traditionally relied on a centralized service architecture resulting in significant maintenance costs. Moreover, due to the lack of an effective file management system, instances of sensitive information going out of control and loss of confidentiality in file sharing have occurred frequently. In order to address the difficulty of tamper detection and the lack of supervision in the entire process of file transfer in the current Internet environment, this paper designs a blockchain-based system architecture for secure sharing of electronic documents. An efficient blockchain model is used in our framework, and with the help of distributed storage system and asymmetric encryption technology, file sharing can be controlled, reliable and traceable in the transfer process. Referring to existing consensus mechanisms, e.g., Delegated Proof of Stake (DPoS) and Practical Byzantine Fault Tolerance (PBFT), we propose a new consensus for efficient and secure file sharing. Our experimental results show that our framework can maintain a higher throughput than existing schemes

Exploring the Feasibility of Quantum-Based Secure Communications for Nuclear Applications

Recent advancements in reactor designs could offer new revolutionary capabilities, including remote monitoring, increased flexibility, and reduced operation and maintenance costs. Embracing new digital technologies would allow for operational concepts such as semiautonomous or near-autonomous control, and two-way communications for real-time integration with the upcoming smart electric grid. However, such continuous data transmission from and toward a reactor site could potentially introduce new challenges and vulnerabilities, necessitating the prioritization of cybersecurity. Conventional information technology–based encryption schemes, which rely mostly on computational complexity, have been shown to be vulnerable to cyberattacks. With the advent of quantum computing, practically any asymmetric encryption could be potentially compromised. For example, it has been shown that a RSA-2048 bit key could be broken in 8 h. To address this challenge, we explore the feasibility of quantum key distribution (QKD) to secure communications. QKD is a physical layer security scheme relying on the laws of quantum mechanics instead of mathematical complexity. QKD promises not only unconditional security but also detection of potential intrusion, as it allows the communication parties to become aware of eavesdropping. To test the proposed hypothesis, a novel simulation tool (NuQKD) was developed to allow for real-time simulation of the BB84 QKD protocol between two remote terminals. A reference scenario is proposed, generic enough to cover various internal and external communication links to a reactor site. Using NuQKD, the internal and external data links were modeled, and receiver operating characteristic curves were calculated for various QKD configurations. A performance analysis was conducted, demonstrating that QKD can provide adequate secret key rates with low false alarms and has the potential of addressing the nuclear industry’s high standards of confidentiality for distance lengths up to 75 km of fiberoptics. Using a conservative estimation, QKD can provide up to 21.5 kbps of secret key rate for a distance of 1 km and 14.4 kbps at 10 km. The target secret key rates for the corresponding links were estimated at 16 kbps and 80 bps, respectively, based on the analysis of real data from a PUR-1 fully digital reactor. Consequently, QKD is shown to be compatible with existing and future point-to-point reactor communication architectures. These results motivate further study of quantum communications for nuclear reactors.

Perancangan Aplikasi Enkripsi dan Dekripsi Gambar Cetak Biru Pada PT. Patco Elektronik Teknologi Menggunakan Algoritma RSA Berbasis Android

PT. Patco Elektronik Teknologi, a leading company in the Electronics industry, urgently needs to enhance the security of blueprint mold data in its Moldshop division. The process of mold repair using CNC machines requires secure access to the company's standard blueprint drawings. Hence, this study aims to develop an Android-based application for encrypting and decrypting blueprint images using the Rivest Shamir Adleman algorithm. It also addresses challenges such as budget constraints, Android device availability, and data security. The method chosen, Rivest Shamir Adleman, is renowned for its asymmetric cryptography and will be implemented in the Android application for securing blueprint images. The research successfully resulted in the creation, implementation, and testing of the Rivest Shamir Adleman Android application. Testing demonstrated that the program can efficiently encrypt and decrypt blueprint images, with encryption averaging 4 to 15 seconds and decryption 2 to 5 seconds using this method. By employing Rivest Shamir Adleman, the application ensures high-level security for blueprint image files.

Secure Routing Protocol Based on Junction Selection in VANETs (SERPROV)

Road safety has become a major issue over the last twenty years. The existing transportation system has become inefficient as the number of vehicles has increased remarkably, causing more accidents and other problems. To meet these challenges, the field of Intelligent Transport Systems (ITS) has been proposed. ITS, also known as intelligent transport, is based on vehicle ad hoc networks (VANETs), a subset of mobile ad hoc networks (MANETs) that use moving cars as nodes to create mobile networks. ITS includes various applications such as cooperative traffic monitoring, blind crossings, collision avoidance and traffic flow control. However, dynamic topology and secure communication remain major challenges due to the high mobility of nodes and the random speed of vehicles. This paper proposes a secure protocol called SERPROV (Secure Routing Protocol based on Junction Selection in VANETs) that combines routing and security using a junction selection mechanism and applies an asymmetric cryptography protocol. Simulation results show that SERPROV improves response time and packet delivery ratio compared to existing protocols for a number of vehicles less than or equal to 300. We plan to implement blockchain technology in the future to replace the public key register, thus making the protocol fully decentralized and further exploring the confidentiality of messages exchanged in the VANET environment.

IoT-based trusted wireless communication framework by machine learning approach

The traditional Radio-Frequency Systems (RFS) authentication methods, designed to ensure secure data transmission on the web, may not always effectively prevent adversaries from gaining access to concealed IDs or asymmetric cryptography through infiltrative, side-channel, training, and computer attacks. In contrast, Unaccounted Information (UAI) has the potential to exploit irregularities in production systems to automatically identify microchips, offering a highly robust and cost-effective security solution. This approach introduces RFS-UAI, a deep neural network-based system that efficiently manages wireless node identification by leveraging synthetic RFS characteristics of remote controls (Tx) learned through supervised methods in Wireless Sensor Networks (WSN). Unlike traditional methods that require the development of specialized transistors for UAI or semantic segmentation, this approach utilizes the existing asymmetrical RFS communication networks. Similar to the way the human brain processes information, Rx handles the entire device identification process at the gateway. According to test results, which include assessing process capability at a specified 65 nm threshold voltage and characteristics such as Local Oscillator (LO) misalignment and I-Q disparity using a probabilistic model with 52 hidden units, the system can distinguish up to 4800 transmitters with a remarkable 99.9 % accuracy under various channel conditions, all without the need for regular preambles. This recommended method can serve as a standalone security measure or be integrated into a biometric identification system.

BLOCKCHAIN TECHNOLOGY'S ROLE IN SECURING DATA AND PREVENTING CYBERATTACKS: A DETAILED REVIEW

This systematic review examines the role of blockchain technology in enhancing data security and preventing cyberattacks across various sectors. Blockchain's decentralized and immutable ledger system, secured through cryptographic mechanisms like cryptographic hashes and asymmetric encryption, offers robust protection against unauthorized access and data tampering. The study highlights blockchain's ability to maintain data integrity and immutability, essential for applications requiring high levels of trust, such as financial transactions and healthcare records. The review also emphasizes the significance of smart contracts, which automate and enforce contract terms, thereby reducing human error and fraud. Sector-specific applications in finance, healthcare, supply chain management, and the Internet of Things demonstrate blockchain's versatility in addressing diverse security challenges. However, significant challenges, including scalability issues, high energy consumption, and regulatory and legal hurdles, impede the widespread adoption of blockchain technology. Addressing these challenges is crucial for realizing blockchain's full potential in cybersecurity. This review underscores the need for continued research and development to overcome these obstacles and fully harness blockchain's capabilities in securing data and preventing cyberattacks.