Lightweight Cryptographic Algorithms Research Articles

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

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

DATA SECURITY IN IOT DEVICES AND SENSOR NETWORKS FOR ROBUST THREAT DETECTION AND PRIVACY PROTECTION

The rapid proliferation of Internet of Things (IoT) devices and sensor networks has revolutionized various industries by enhancing automation, connectivity, and operational efficiency. However, these advancements have also introduced significant security challenges due to the resource constraints and decentralized nature of IoT environments. This paper provides a systematic review of IoT security solutions, focusing on encryption techniques, authentication protocols, and machine learning-based anomaly detection methods. A total of 55 peer-reviewed articles were analyzed following the PRISMA guidelines. The findings reveal that while lightweight cryptographic algorithms, such as elliptic curve cryptography (ECC), offer robust security with low energy consumption, scalability across large IoT networks remains a challenge. Blockchain-based authentication has emerged as a promising decentralized solution, but issues related to energy consumption and latency hinder its widespread adoption. Machine learning techniques have shown high accuracy in detecting threats in real-time, but their resource-intensive nature limits their application in low-power IoT devices. This review underscores the need for multi-layered, integrated security frameworks and highlights gaps in research on quantum-resistant cryptography and interoperable security standards. Future research must focus on developing scalable, energy-efficient security solutions to ensure data integrity and privacy in expanding IoT ecosystems.

Advanced Encryption Techniques in Healthcare IoT: Securing Patient Data in Connected Medical Devices

As a result of the fast development of Internet of Things (IoT) technology, the healthcare sector has undergone a transformation. This transformation has been brought about by the deployment of linked medical devices that provide immediate monitoring and data collecting. Despite the fact that these innovations promise to bring about considerable gains in patient care and operational efficiency, they also bring about major security issues, especially with regard to the protection of personally identifiable information about patients. Within the context of the Internet of Things (IoT) ecosystem for healthcare, this study investigates sophisticated encryption approaches that are aimed to protect patient data stored in linked medical equipment. One of the first things that the research does is investigate the specific security needs and risks that are linked with Internet of Things (IoT) devices in the healthcare industry. These include concerns around data privacy, integrity, and authentication. Advanced Encryption Standard (AES), Elliptic Curve Cryptography (ECC), and Quantum Key Distribution (QKD) are some of the encryption standards and protocols that are often used in the process of protecting Internet of Things (IoT) connections. This article presents a complete examination of these encryption standards and protocols. Following that, it digs into sophisticated encryption approaches that are especially targeted to the limits and needs of healthcare IoT systems. These techniques include lightweight cryptographic algorithms, key management strategies, and secure multi-party computing (MPC) frameworks.

QIULEA: Quantum-inspired ultra-lightweight encryption algorithm for IOT devices

AbstractThis paper introduces a quantum-inspired ultra-lightweight encryption algorithm tailored for Internet of things devices with limited resources. The proposed algorithm excels in processing speed, memory usage, and energy efficiency, significantly outperforming existing lightweight cryptographic algorithms. With a processing speed of 12.4 ms, memory usage of 3.2 kilobytes, and energy consumption of 0.7 milli-Joules per kilobyte, the proposed algorithm stands out for its robust security and potential to enhance the security of Internet of things devices across various applications. This paper explores the methodology behind the proposed algorithm, comparing its performance metrics with conventional S-box generation approaches, and demonstrates its superiority in both theoretical and practical aspects.

Advancing cryptography: a novel hybrid cipher design merging Feistel and SPN structures

In the dynamic field of cryptography, lightweight ciphers play a pivotal role in overcoming resource constraints in modern applications. This paper introduces a lightweight cryptographic algorithm by seamlessly merging the proven characteristics of the Feistel cipher CLEFIA with the advanced substitution-permutation network (SPN) framework of RECTANGLE for key generation. The algorithm incorporates a specially optimized feather S-box, balancing efficiency and security in both CLEFIA and RECTANGLE components. The RECTANGLE key generation, vital for the proposed lightweight technique, enhances overall cryptographic security and efficiency. Meticulous consideration of resource limitations maintains the algorithm's lightweight nature, making it well-suited for applications with restricted computational resources. To validate the efficacy of the lightweight algorithm, extensive evaluation on encrypted data is conducted using National Institute of Standards and Technology (NIST) tools, known for assessing cryptographic algorithm quality. Results reveal a high degree of randomness, indicative of robust resistance against cryptographic attacks. This manuscript provides a comprehensive examination of the lightweight algorithm, emphasizing key attributes, security enhancements, and successful integration of the optimized feather S-box. Rigorous testing, particularly NIST tool-based randomness analysis, offers empirical evidence of the algorithm's resilience against attacks, establishing its suitability for secure data encryption in resource-limited environments.<p> </p>

Symmetry Analysis in Construction Two Dynamic Lightweight S-Boxes Based on the 2D Tinkerbell Map and the 2D Duffing Map

The lack of an S-Box in some lightweight cryptography algorithms, like Speck and Tiny Encryption Algorithm, or the presence of a fixed S-Box in others, like Advanced Encryption Standard, makes them more vulnerable to attacks. This proposal presents a novel approach to creating two dynamic 8-bit S-Boxes (16 × 16). The generation process for each S-Box consists of two phases. Initially, the number initialization phase involves generating sequence numbers 1, sequence numbers 2, and shift values for S-Box1 using the 2D Tinkerbell map. Additionally, sequence numbers 3, sequence numbers 4, and shift values for S-Box2 are generated using the 2D Duffing map. Subsequently, the S-Box construction phase involves the construction of S-Box1 and S-Box2. The effectiveness of the newly proposed S-Boxes was evaluated based on various criteria, including the bijective property, balance, fixed points, and strict avalanche criteria. It was observed that S-Box1 achieved a remarkable linear and differential branch number of 4, surpassing any previous studies. Furthermore, it exhibited a non-linearity of 105.50, a differential uniformity of 12, and an algebraic degree of 7. Similarly, S-Box2 also achieved a linear and differential branch number of 4, a non-linearity of 105.25, a differential uniformity of 14, and an algebraic degree of 7. Moreover, the reduction in the number of linear and nonlinear operations for both S-Boxes makes them suitable for lightweight algorithms. The architecture of the proposed S-Boxes demonstrates robustness, with a total of 3.35 × 10504 possible S-Boxes, providing protection against algebraic attacks.

Novel optimized implementations for the Piccolo cipher based on field‐programmable gate arrays

AbstractIn the era of the highly pervasive Internet of Things (IoT), the optimized implementation of lightweight cryptographic algorithms for protecting data security has extensively received attention, for instance, the Piccolo cipher. Piccolo is an ultra‐lightweight block cipher designed for extremely resource‐constrained devices. Currently, many optimized implementations of Piccolo have been proposed; however, these implementations are heavily rely on optimizing different architectures. Actually, these implementation schemes have all neglected the optimization of the core components. How to achieve the new optimized implementation of the Piccolo cipher (via both the architectures and the core components) appears to be an interesting problem. In this article, new circuit structures for components (key schedules and round functions) of the Piccolo are first proposed using fewer logic gates. Based on these circuit structures, three architectures (iterative, integrated iterative, and scalar) are proposed to maximize implementation performances. To demonstrate their effectiveness and practicality, these architectures are simulated and synthesized on different field‐programmable gate arrays (FPGA) devices. Compared with the existing architectures of Piccolo, the results indicate that the iterative architectures and the integrated iterative architecture provide a better trade‐off between area and throughput, and the scalar architectures provide the highest throughput. Especially for Piccolo‐128, the area of its iterative architecture is 30 look‐up tables (LUTs) and 22 slices less than the best known implementation; the throughput and efficiency are 68.56% higher and twice higher than the best known implementation, respectively. Compared with other block ciphers, the efficiency and area‐delay product of the Piccolo‐128 iterative architecture outperform PRESENT, GIFT, SIMON, Midori, SIMON, and SIMECK. Compared with the best results, its encryption efficiency has increased by 31.53%, and the area‐delay product has decreased by 44.63%.

Research on Fault Attacks of Lightweight Cryptographic Algorithms

Fault attacks exploit fault injection techniques to compromise cryptographic systems, compromising device operations and leaking secret keys. Lightweight block cipher algorithms are suitable for resource-constrained environments, ensuring security while reducing hardware and software overhead. This paper summarizes the current research status of fault attacks on some lightweight cryptographic algorithms, including block ciphers, stream ciphers, etc. These studies are crucial for addressing system vulnerabilities, protecting personal privacy, and enhancing the stability of embedded systems. The aim of this paper is to provide comprehensive references for cryptographers, assisting in selecting suitable algorithms and defense strategies.

Efficiency and Security Evaluation of Lightweight Cryptographic Algorithms for Resource-Constrained IoT Devices.

The IoT has become an integral part of the technological ecosystem that we all depend on. The increase in the number of IoT devices has also brought with it security concerns. Lightweight cryptography (LWC) has evolved to be a promising solution to improve the privacy and confidentiality aspect of IoT devices. The challenge is to choose the right algorithm from a plethora of choices. This work aims to compare three different LWC algorithms: AES-128, SPECK, and ASCON. The comparison is made by measuring various criteria such as execution time, memory utilization, latency, throughput, and security robustness of the algorithms in IoT boards with constrained computational capabilities and power. These metrics are crucial to determine the suitability and help in making informed decisions on choosing the right cryptographic algorithms to strike a balance between security and performance. Through the evaluation it is observed that SPECK exhibits better performance in resource-constrained IoT devices.

Machine learning cryptography methods for IoT in healthcare

BackgroundThe increased application of Internet of Things (IoT) in healthcare, has fueled concerns regarding the security and privacy of patient data. Lightweight Cryptography (LWC) algorithms can be seen as a potential solution to address this concern. Due to the high variation of LWC, the primary objective of this study was to identify a suitable yet effective algorithm for securing sensitive patient information on IoT devices.MethodsThis study evaluates the performance of eight LWC algorithms—AES, PRESENT, MSEA, LEA, XTEA, SIMON, PRINCE, and RECTANGLE—using machine learning models. Experiments were conducted on a Raspberry Pi 3 microcontroller using 16 KB to 2048 KB files. Machine learning models were trained and tested for each LWC algorithm and their performance was evaluated based using precision, recall, F1-score, and accuracy metrics.ResultsThe study analyzed the encryption/decryption execution time, energy consumption, memory usage, and throughput of eight LWC algorithms. The RECTANGLE algorithm was identified as the most suitable and efficient LWC algorithm for IoT in healthcare due to its speed, efficiency, simplicity, and flexibility.ConclusionsThis research addresses security and privacy concerns in IoT healthcare and identifies key performance factors of LWC algorithms utilizing the SLR research methodology. Furthermore, the study provides insights into the optimal choice of LWC algorithm for enhancing privacy and security in IoT healthcare environments.

An Efficient Lightweight Crypto Security Module for Protecting Data Transmission Through IOT Based Electronic Sensors

The Internet of Things (IoT) devices are advanced nanoelectronics devices which has recently witnessed an explosive expansion in the field of communication and electronics, becoming ubiquitous in various applications. However, the rapid growth of IoT applications makes them prone to security threats and data breaches. Hence, cryptographic techniques are developed to ensure data confidentiality and integrity in IoT and many of the applications from optoelectronics. However, the existing cryptographic algorithms face challenges in securing the data from threats during transmission, as they lack effective key management. Therefore, we proposed a novel optimized lightweight cryptography (LWC) to resolve this challenge using the combined benefits of Grey Wolf Optimization and Hyper Elliptic Curve Cryptography (GW-HECC). The proposed LWC algorithm protects the data from attacks during data exchange by optimizing the key management process and aims to deliver greater Quality of Service (QoS) in IoT networks. An IoT network was initially created with multiple sensor devices, IoT gateways, and data aggregators. The proposed framework includes a Quantum Neural Network (QNN)-based attack prediction module to predict the malicious data entry in the IoT network. The QNN learns the attack patterns from the historical IoT data and prevents incoming malicious data entries, ensuring that only normal data is transmitted to the cloud. For secure data transmission, the sensed data from the IoT network are encrypted using the proposed GW-HECC. The presented work was designed and implemented in Python software; the experimental results demonstrate that the proposed method offers greater data confidentiality of 97.9%, improved attack prediction accuracy of 99.8%, and a reduced delay of 0.37 s. Furthermore, a comparative analysis was made with existing cryptographic algorithms, manifesting that the proposed algorithm acquired improved results.

Design and Implementation of Low Power and High Data Rate Edge Coded Signaling Architecture for IoT Devices

Abstract Edge coded signaling (ECS) is a recently introduced communication protocol designed for single-channel signaling among constrained internet of things (IoT) nodes. This study aims to enhance the data rate of ECS, without increasing the clock frequency or power consumption. The goal is to develop an improved protocol that maintains the inherent advantages of ECS while achieving a higher data rate. The proposed solution, double data rate ECS (DDR-ECS), leverages both pulse edges of the ECS pulse stream for information encoding, drawing an analogy to DDR memory systems. The study presents a detailed design of low-power architecture for the DDR-ECS transceiver. This design was synthesized using a 65 nm ASIC process to evaluate its performance in terms of power consumption, gate count, and data rate. The synthesis results demonstrate that the DDR-ECS transceiver preserves the key features of ECS, including tolerance to clock frequency variations and compatibility with lightweight cryptographic algorithms. It effectively doubles the dynamic data rate to the range of 12–73.5 Mb/s while consuming an equivalent power of 13 μW and occupying a compact form factor of only 1,755 gates. The introduction of DDR-ECS represents a significant advancement in the ECS protocol, offering a novel approach to doubling the data rate without increasing the clock frequency or power envelope. This innovation retains the simplicity and efficiency of ECS, providing an enhanced communication solution for constrained IoT nodes.

Improved differential fault analysis of Grain128-AEAD

The number of smart devices connected to the Internet has been constantly increasing, and as a result, lightweight cryptography (LWC) has become more important in the past decade. The Lightweight Cryptography (LWC) Project is an initiative taken by the National Institute of Standards and Technology (NIST) to standardize such LWC algorithms. Grain128-AEAD, which was submitted to the NIST LWC project, is an encryption algorithm that provides both confidentiality and integrity assurance. Third-party security analysis of the submitted ciphers is an important aspect of the evaluation of the submission to the NIST LWC project. Although several pieces of existing research, such as the bit-flipping attack, random fault attack, and deterministic random fault attack, have examined the security of Grain128-AEAD, there is still room for improvement in the fault attack models of these studies. This work aims to fill this research gap by analyzing the security margin of Grain128-AEAD against a series of improved differential fault attacks. In this study, we developed a probabilistic random fault attack and applied it to Grain128-AEAD. As an improvement of the existing research, a probabilistic approach can be applied to a more relaxed moderate control attack model. The existing moderate control model assumes the fault to be injected within any bit of a given byte, whereas the faults in our improved approach can be injected within any bits of a two-byte/four-byte segment, thereby relaxing the fault precision. The results indicate that the improved moderate control requires 388 keystreams for the two-byte model and 279 for the four-byte model to identify the target fault locations for implementing a state recovery attack. The relaxed fault attack models presented in this work are more practical to implement; hence, the findings of this research have improved the existing studies and narrowed the current research gap on the fault attack models of Grain128-AEAD. % To maintain consistency in terminology, "Grain-128AEAD" has been revised to "Grain128-AEAD" in both the abstract and the main text. Please confirm this revision.

Lightweight Cryptography for Internet of Things: A Review

The paper examines the rising significance of security in Internet of Things (IoT) applications and emphasizes the need for lightweight cryptographic solutions to protect IoT devices. It acknowledges the growing prevalence of IoT in various fields, where sensors collect data, and computational systems process it for action by actuators. Due to IoT devices' resource limitations and networked nature, security is a concern. The article compares different lightweight cryptographic block cipher algorithms to determine the best approach for securing IoT devices. It also discusses the merits of hardware versus software solutions and explores potential security threats, including intrusion and manipulation. Additionally, the article outlines future work involving the implementation of the trusted Advanced Standard Encryption block cipher in IoT devices, including its use in quick-response (QR) code scanning and messaging platforms. It acknowledges existing drawbacks and suggests areas for improvement in IoT system performance and security.

A Lightweight Image Cryptosystem for Cloud-Assisted Internet of Things

Cloud computing and the increasing popularity of 5G have greatly increased the application of images on Internet of Things (IoT) devices. The storage of images on an untrusted cloud has high security and privacy risks. Several lightweight cryptosystems have been proposed in the literature as appropriate for resource-constrained IoT devices. These existing lightweight cryptosystems are, however, not only at the risk of compromising the integrity and security of the data but also, due to the use of substitution boxes (S-boxes), require more memory space for their implementation. In this paper, a secure lightweight cryptography algorithm, that eliminates the use of an S-box, has been proposed. An algorithm termed Enc, that accepts a block of size n divides the block into L n R bits of equal length and outputs the encrypted block as follows: E=L⨂R⨁R, where ⨂ and ⨁ are exclusive-or and concatenation operators, respectively, was created. A hash result, hasR=SHA256P⨁K, was obtained, where SHA256, P, and K are the Secure Hash Algorithm (SHA−256), the encryption key, and plain image, respectively. A seed, S, generated from enchash=Enchashenc,K, where hashenc is the first n bits of hasR, was used to generate a random image, Rim. An intermediate image, intimage=Rim⨂P, and cipher image, C=Encintimage,K, were obtained. The proposed scheme was evaluated for encryption quality, decryption quality, system sensitivity, and statistical analyses using various security metrics. The results of the evaluation showed that the proposed scheme has excellent encryption and decryption qualities that are very sensitive to changes in both key and plain images, and resistance to various statistical attacks alongside other security attacks. Based on the result of the security evaluation of the proposed cryptosystem termed Hash XOR Permutation (HXP), the study concluded that the security of the cryptography algorithm can still be maintained without the use of a substitution box.

Attack Analysis on Hybrid-SIMON-SPECKey Lightweight Cryptographic Algorithm for IoT Applications

Objective: To perform attack analysis on new developed hybrid-SIMON-SPECKey lightweight cryptographic algorithms and compare its strength with existing SIMON and SPECK Lightweight cryptographic algorithm. Methods: A hybrid-SIMON-SPECKey algorithm is the combination of round function of SIMON and key scheduling of SPECK algorithm. Both SIOMN & SPECK algorithm are used for securing resource constrained devices. In this research work, avalanche effect method is used to analyze attack resistance property of algorithm. Findings: Newly developed Hybrid algorithm shows better results in terms of execution time and memory consumption. As compared to SIMON, hybrid version of algorithm consumes 50% less time and 20% less memory, which makes it efficient. Strict Avalanche criteria for SIMON is 89%, that of SPECK is 90% and in case of hybrid algorithm, it is 90% at start position but when the character is flipped or changed at the end position of plain text then SAC is more (87%) in case of hybrid algorithm as compared as SIMON and SPECK algorithms. Hence, newly developed algorithm showed improved results with equally resistance to the attack as compared to SIMON & SPECK. Novelty and applications: The novelty lies in the creation of a hybrid lightweight cryptographic algorithm that combines the feistel structure of SIMON with the key scheduling function of SPECK. This hybrid approach aims to leverage the strengths of both algorithms, potentially providing a more robust and efficient solution for resource-constrained IoT devices. In section 3.1 comparative analysis is done which show that hybrid algorithm outperforms in term of time and memory consumption as well a strength of newly developed hybrid algorithm is evaluated using avalanche effect which shows that it is at par with base algorithms. Keywords: Attack Analysis, Cipher Code, Decryption, Encryption, Lightweight Cryptography, Iot Devices, And Resource Constraint Devices

A Survey on Lightweight Cryptographic Algorithms in IoT

Abstract The Internet of Things (IoT) will soon penetrate every aspect of human life. Several threats and vulnerabilities are present due to the different devices and protocols used in an IoT system. Conventional cryptographic primitives or algorithms cannot run efficiently and are unsuitable for resource-constrained devices in IoT. Hence, a recently developed area of cryptography, known as lightweight cryptography, has been introduced, and over the years, numerous lightweight algorithms have been suggested. This paper gives a comprehensive overview of the lightweight cryptography field and considers various popular lightweight cryptographic algorithms proposed and evaluated over the past years for analysis. Different taxonomies of the algorithms and other associated concepts were also provided, which helps new researchers gain a quick overview of the field. Finally, a set of 11 selected ultra-lightweight algorithms are analyzed based on the software implementations, and their evaluation is carried out using different metrics.

Improved 2-round collision attack on IoT hash standard ASCON-HASH

Lightweight cryptography algorithms are a class of ciphers designed to protect data generated and transmitted by the Internet of Things. They typically have low requirements in terms of storage space and power consumption, and are well-suited for resource-limited application scenarios such as embedded systems, actuators, and sensors. The NIST-approved competition for lightweight cryptography aims to identify lightweight cryptographic algorithms that can serve as standards. Its objective is to enhance data security in various scenarios. Among the chosen standards for lightweight cryptography, ASCON has been selected. ASCON-HASH is a hash function within the ASCON family. This paper presents a detailed analysis of the differential characteristics of ASCON-HASH, utilizing the quadratic S-box. Additionally, we employ message modification techniques and ultimately demonstrate a non-practical collision attack on the 2-round ASCON-HASH, requiring a time complexity of 298 hash function calls.

Securing large-scale data processing: Integrating lightweight cryptography in MapReduce

<p>In today’s rapidly evolving digital landscape, the imperative of data security stands paramount. With the proliferation of sensitive information being stored and transmitted online, the necessity for robust encryption algorithms has grown exponentially. However, the suitability of traditional encryption methods in resource-constrained settings, like mobile devices and cloud computing, remains a concern due to their computational intensity. To address this, researchers have introduced a novel category of encryption algorithms known as lightweight cryptography algorithms. These cryptographic solutions are designed to offer robust security while minimizing computational demands, thus striking a harmonious balance between security and efficiency. While lightweight cryptography algorithms present a promising solution, their adequacy for applications demanding exceptionally high security, particularly within Big Data environments, warrants careful consideration. In this study, we presented a novel approach involving the utilization of lightweight cryptography algorithms within the MapReduce framework. By subjecting these algorithms to rigorous experimentation, we assessed their performance using software-oriented metrics from various dimensions.</p>

Enhancing financial transaction security with lightweight cryptographic algorithms

The lightweight cryptographic algorithms used to increase the safety for financial transactions. The proposed lightweight cryptographic algorithms provide a middle ground, guaranteeing strong security with low computational overhead. Lightweight cryptography approaches being investigated for their potential in protecting private financial information during transactions. These algorithms are well-suited for real-time monetary transactions since they not only strengthen data integrity but also cut processing times through streamlined encryption and decryption processes. This paper focus into the planning, execution, and efficiency assessment of such lightweight cryptographic algorithms as they pertain to monetary systems. This study shows how successful they are at preventing common security threats like eavesdropping and data manipulation through extensive testing and analysis. Lightweight cryptographic algorithms have been shown to have the ability to dramatically improve the security of financial transactions, providing an efficient and cost-effective means of safeguarding sensitive financial data in today interconnected and potentially dangerous digital environment.