Comparative Performance Analysis of Lightweight Cryptography Algorithms for IoT Sensor Nodes

In the rapidly developing world of the Internet of Things (IoT), data security has become increasingly important since massive personal data are collected. IoT devices have resource constraints, which makes traditional cryptographic algorithms ineffective for securing IoT devices. To overcome resource limitations, lightweight cryptographic algorithms are needed. To identify research trends and patterns in IoT security, it is crucial to analyze existing works, keywords, authors, journals, and citations. We conducted a bibliometric analysis using performance mapping, science mapping, and enrichment techniques to collect the necessary information. Our analysis included 979 Scopus articles, 214 WOS articles, and 144 IEEE Xplore articles published during 2015–2023, and duplicates were removed. We analyzed and visualized the bibliometric data using R version 4.3.1, VOSviewer version 1.6.19, and the bibliometrix library. We discovered that India is the leading country for this type of research. Archarya and Bansod are the most relevant authors; lightweight cryptography and cryptography are the most relevant terms; and IEEE Access is the most significant journal. Research on lightweight cryptographic algorithms for IoT devices (Raspberry Pi) has been identified as an important area for future research.

The Internet of Things (IoT) is becoming an increasingly growing topic. IoT encompasses everything connected to the internet. IoT requires multi-facet security solutions where the communication is secured with confidentiality, integrity, and service availability. However, IoT Sensor Node has the requirement to minimize power usage and computational power due to the requirement to be miniature. Therefore, the challenge of implementing security in the IoT Sensor Node must be addressed. Even if the IoT Sensor Node is protected with encryption and authentication, the protection is not comprehensive to sustain a Denial of Service (DoS) attack. The DoS attack is considered one of the security threats that may affect IoT network's quality service and reduce IoT Sensor Node's lifespan. Hence, mitigation shall be needed to secure IoT Sensor Node. This paper aims to propose a lightweight Denial of Service (DoS) Detection Systems algorithm to secure IoT Sensor Node. The approach uses data from previous experiments and translated it to develop mitigation to secure IoT Sensor Node, thus increasing IoT Sensor Node's lifespan.

Since the Internet of Things (IoT) will be entwined with everything we use in our daily life, the consequence of security flaws escalates. Smart objects will govern most of the home appliances and car engines yielding potential disaster scenarios. In this context, successful attacks could lead to chaos and scary scenarios (www.darkreading.com). Unprotected personal information may expose sensitive and embarrassing data to the public and attacks may threaten not only our computers and smart devices, but our intimacy and perhaps our lives too. Because persons and objects will be bonded with each other, user consent becomes critical. Therefore, thing, object, and user Identity will be the focus of future IoT security solutions, yielding a Trust, Security, and Privacy (TSP) paradigm, which may constitute the Achilles' heel of IoT. While security issues are quite straightforward, mainly from background knowledge, privacy issues are far more complex. Privacy constitutes a rather challenging task, even for the m...

Research Article| March 01, 2016 The Internet of Geophysical Things: Raspberry Pi Enhanced REF TEK (RaPiER) System Integration and Evaluation Frank Sepulveda; Frank Sepulveda aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Search for other works by this author on: GSW Google Scholar Jay Pulliam Jay Pulliam aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Search for other works by this author on: GSW Google Scholar Author and Article Information Frank Sepulveda aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Jay Pulliam aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Publisher: Seismological Society of America First Online: 14 Jul 2017 Online Issn: 1938-2057 Print Issn: 0895-0695 © 2016 by the Seismological Society of America Seismological Research Letters (2016) 87 (2A): 345–357. https://doi.org/10.1785/0220150234 Article history First Online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Frank Sepulveda, Jay Pulliam; The Internet of Geophysical Things: Raspberry Pi Enhanced REF TEK (RaPiER) System Integration and Evaluation. Seismological Research Letters 2016;; 87 (2A): 345–357. doi: https://doi.org/10.1785/0220150234 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search ABSTRACT The proliferation of commercial Internet of Things (IoT) devices is raising consumers’ awareness of the benefits of enhancing everyday objects with the ability to communicate, sense, and process information. Commercial‐off‐the‐shelf (COTS) versions of the embedded technologies responsible for the rise of the IoT are easy‐to‐use, inexpensive, and relatively powerful. IoT Makers, technological do‐it‐yourself enthusiasts, utilize these technologies and the IoT ecosystem to create IoT devices that range from casual hobbyist to entrepreneurial in nature.In an effort to develop a “no‐engineer‐needed” Internet of Geophysical Things (IoGT) device, we integrated a COTS embedded computer with a geoscience‐related COTS data acquisition system (DAS). Using skills common to geoscientists, we integrated the Raspberry Pi System‐On‐Chip with the REF TEK (a Trimble brand) 130‐01 DAS. This Raspberry Pi enhanced REF TEK (RaPiER) provides IoGT Makers a platform for the development of geoscientific sensor node or network enhancements. IoGT Makers can use the RaPiER to tinker with IoT capabilities while simultaneously acquiring research‐quality data. Geoscientific (i.e., seismic) application areas that may benefit from RaPiER, particularly RaPiER nodal processing, include earthquake and engineering seismology.In this article, we discuss the emerging technologies that allow IoGT Makers to build their own IoGT device. We review our selection of the Raspberry Pi and REF TEK 130‐01 for IoGT device integration. We provide a RaPiER system integration guide and REF TEK interface software compiled for the Raspberry Pi ( available in the electronic supplement to this article). We present methods to expand RaPiER capabilities using the Raspberry Pi’s ecosystem. Last, we discuss our evaluation of RaPiER’s performance and its suitability for realistic field deployments. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Over the years, important breakthroughs have been made in protecting data at rest or in-transit. The emergence of the Internet of Things (IoT) and Cyber Physical Systems (CPS) has pose new challenges for protecting data in systems and devices tightly close to humans. Embedded systems with constrained computing capabilities are a central part in IoT and CPS, susceptible to different security attacks and vulnerabilities. Lightweight cryptography is the term used for grouping the different cryptographic algorithms and techniques tailored to observe the requirements for data security in such constrained applications. Nowadays, the potential emergence of quantum computing threatens these security solutions widely in use. Thus, novel cryptographic algorithms deemed to resist quantum attack models are being standardized by the National Institute of Standards and Technology (NIST) in the Post-Quantum Cryptography (PQC) Standardization process. In this paper, we present a study on how the advent of quantum computing might have a deep impact on the security of constrained applications in the IoT and CPS domains. We focused on the NIST PQC finalists, from the perspective of their use for securing embedded systems.

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.

Abstract: The swift development of the Internet of Things (IoT) is leading to the development of a multitude of intelligent devices, with profound implementation for security. In addition to their purported security level, IoT devices typically include limited resources, including minimal computational power, limited memory, and restricted battery capacity. Proposed within the context of IoT, lightweight cryptographic primitives aim to balance the trade-off between providing a high level of security and achieving good performance. One of the lightweight cryptography (LWC) algorithms is Ascon. Ascon has been selected as the primary recommendation for lightweight authentication encryption in the final round of The Competition for Authenticated Encryption: Security, Applicability, and Robustness (CAESAR) competition. Within this review, research papers have been explored that showcase diverse methodologies utilized in Ascon hardware implementation. To assess the research papers, the categorization is done according to the hardware design techniques utilized in prior research. This review study analyzes several works, analyzing them based on many factors, including the classification of methodologies employed for hardware implementation design and the evaluation of performance indicators. This review examines the potential areas for improvement by examining the research obstacles highlighted in the current literature, offering suggestions to researchers to enhance their work. After reviewing the conclusion can be made on which hardware implementation design can result in higher performance for lightweight encryption.

The growing proliferation of the Internet of Things (IoT) necessitates lightweight cryptographic algorithms that balance security and efficiency f or r esource-constrained environments. Traditional cryptographic methods are often too resource-intensive for devices with limited processing power, memory, and energy capacity. Lightweight cryptography (LWC) addresses this by providing optimized solutions with minimal hardware over-head. One such candidate, the New Lightweight Cryptographic Algorithm (NLCA), a 128-bit symmetric block cipher. This paper introduces a modified version of NLCA, called ModNLCA, which replaces the original F-function with a dynamic S-Box generated from the secret key and round constants. This modification enhances resistance to linear attacks while potentially reducing computational complexity. The algorithm is implemented on ESP32 microcontrollers to simulate real-world IoT scenarios, where encryption and decryption processes are distributed across nodes via Wi-Fi communication. Experimental results show that while ModNLCA is slightly slower than PRESENT at small data sizes (e.g., 32 bits), it outperforms both NLCA and PRESENT significantly at l arger sizes. At 256 bits, ModNLCA a chieves up to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{5 3 \%}$</tex> faster encryption and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{3 8 \%}$</tex> faster decryption compared to PRESENT, while also using memory more efficiently. Moreover, ModNLCA demonstrates a strong diffusion effect, achieving an avalanche effect rate of 25.34 %. These findings s uggest that ModNLCA is a promising candidate for secure and efficient encryption in resource-constrained systems.

The concept of the Internet of Things (IoT) has received much attention over the last five years. It is predicted that the IoT will influence every aspect of our lifestyles in the near future. Wireless Sensor Networks are one of the key enablers of the operation of IoTs, allowing data to be collected from the surrounding environment. However, due to limited resources, nature of deployment and unattended operation, a WSN is vulnerable to various types of attack. Security is paramount for reliable and safe communication between IoT embedded devices, but it does, however, come at a cost to resources. Nodes are usually equipped with small batteries, which makes energy conservation crucial to IoT devices. Nevertheless, security cost in terms of energy consumption has not been studied sufficiently. Previous research has used a security specification of 802.15.4 for IoT applications, but the energy cost of each security level and the impact on quality of services (QoS) parameters remain unknown. This research focuses on the cost of security at the IoT media access control (MAC) layer. It begins by studying the energy consumption of IEEE 802.15.4 security levels, which is followed by an evaluation for the impact of security on data latency and throughput, and then presents the impact of transmission power on security overhead, and finally shows the effects of security on memory footprint. The results show that security overhead in terms of energy consumption with a payload of 24 bytes fluctuates between 31.5% at minimum level over non-secure packets and 60.4% at the top security level of 802.15.4 security specification. Also, it shows that security cost has less impact at longer packet lengths, and more with smaller packet size. In addition, the results depicts a significant impact on data latency and throughput. Overall, maximum authentication length decreases throughput by almost 53%, and encryption and authentication together by almost 62%.

In the recent past internet of things (IoT) has become promising technology due which it has grabbed the attention of the research community, industry, and end-user. Energy management is one of the massive constraints with an IoT sensor node because sensor nodes are often battery operated. In India, cremation centers are located within the city premises, due to the continuous emission of harmful gases such as carbon monoxide (CO), ammonia (NH3), it will deteriorate the people's health those who are closely located. In this paper, we have designed an energy-efficient Mobile Air Quality Monitoring System (MAQMS) and installed it in the cremation center in Hyderabad, India. MAQMS can measure harmful pollutants released into the environment during the cremation process. The proposed system measures the five different gases, such as carbon monoxide (CO), particulate matter 2.5, particulate matter 10, ammonia (NH3), and nitrogen dioxide (NO2). To reduce the power consumption of MAQMS, we proposed an algorithm that allows MAQMS to operate in a hybrid model that is a combination of two modes, namely hibernation and active mode. For every one minute, we allowed the system to switch between a hibernation mode and active mode with adaptive sampling to ensure data quality with efficient power consumption. The experimental results show that the power consumption by MAQMS per day before applying the hybrid model is 613.72A, whereas after applying the hybrid model, power consumption has a dropdown to 289.58A.

Ubiquitous sensing enabled networks have transformed the living chores into a modern living standard in which each move is automated. The dependency of humans on IoT is increasing every day, so the IoT networks must be efficient and secure. Secure communication in the Internet of Things (IoT) networks is a hotly debated research issue. Cryptography is one of the solutions for secure data transmission. In IoT networks, designing a cryptography algorithm is a major challenge for resource constraint environment. So, when we talk about cryptography in IoT, this term transforms into “lightweight cryptography.” This paper presents a review of lightweight cryptography algorithms in the form of a stream cipher, block cipher, symmetric encryption, and asymmetric encryption.

The Internet of Things (IoT) has become widely used in recent years in a wide range of applications, such as, weather condition monitoring, transportation, smart homes, smart cities, smart farm, etc. The ecosystem of the IoT is also vast, including from sensor and hardware devices up to cloud-computing. An approach that is getting more and more attention in the IoT ecosystem is the edge-computing and one of its fundamental pieces of equipment is the edge-computing gateway (GTW), which can working as a data-processing device nearer to the things and as a bridge to the Internet, as well. The most important features for these GTWs must be robustness and efficiency and a very popular solution is to use low-cost Raspberry Pi card-size computers. Considering protocol solution, Message Queue Telemetry Transport (MQTT) communication protocol has been considered one of the most applicable to IoT because of its low-power capability. In this context, this paper describes a study about the performance evaluation of a low-power member of the Raspberry Pi family, the Raspberry Pi Zero W, working as an IoT gateway and running MQTT. The experimental results show its performance using as metrics: the processor temperature, the CPU usage level, and rate of MQTT received messages under different Quality of Services (QoS).

The resource‐constrained characteristics of the Internet of Things (IoT) sensors lead to a pressing security requirement for developing lightweight cryptographic algorithms. This work introduces and analyzes a novel lightweight cryptographic algorithm for resource‐constrained devices. The algorithm is based on the Feistel structure in which the round function combines circular shifts, XOR, and key addition operation for data encryption and decryption. With a key size of 128 bits and a block size of 64 bits, the algorithm employs Linear Feedback Shift Registers (LFSR) for key generation. The algorithm's security is evaluated by examining its adherence to the avalanche criterion, a critical property for robust encryption. A comprehensive comparison is made between the proposed algorithm and a previously developed lightweight encryption algorithm, which also utilized LFSR for key generation in terms of avalanche effect, execution time and energy consumption. The proposed cipher is found to be significantly faster with an encryption time of 88 microseconds on Android Uno. The proposed cipher is also faster and consumed less energy in ESP 32, STM Nucleo, and Android Nano.

With increased Internet of Things (IoT) devices, complexity and protection are more challenging. Lightweight cryptographic algorithms are secure and suitable for limited-resource environments; however, their hash functions provide encrypted data but not integrity. Strong security features are available, but setup is difficult and expensive. Network security mechanisms increase power consumption and latency. As IoT networks grow, managing cryptographic keys and securely authenticating large numbers of devices become complex tasks. Efficient key management strategies are required to ensure the scalability required. Existing state-of-the-art solutions lack standardization, scalability, complex and costly. Thus, this research proposes a secure solution for IoT resource-constrained devices, combining strong data integrity and lightweight encryption, and is thus named a hybrid. This hybrid approach integrates SHA-512 and the present cipher in our proposed approach and thus ensuring higher security than state-of-the-art models. This intelligent combination not only enhances the algorithm’s resistance against cryptographic attacks but also improves its processing speed. The proposed approach is used to reduce the processing time for encryption in the IoT platform and to preserve the trade-off between security and efficiency. In terms of memory use, execution time, and precision, the proposed approach is compared with recent state-of-the-art research. The experimental results indicate that our approach is efficient using the avalanche, authentication success rate, collision events, and execution time. The efficiency is 53% to 65%, and the avalanche effect indicates sensitivity to input variations, suggesting moderate-to-considerable reactivity to small data changes. The experimental tests conducted across 10,000 and 80,000 runs reveal no collisions and found that the proposed approach is resilient in managing unique IDs. Moreover, our approach performs consistently, with an average execution time of 0.088246 s, ranging from 0.075954 to 0.094583 s. Finally, our approach provides a practical and scalable solution for securing IoT devices in resource-constrained environments, addressing practical problems for IoT devices.

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