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Keywords = acceleration environment (AE)

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34 pages, 2216 KiB  
Article
An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets
by Ahmad Salehiyan, Pardis Sadatian Moghaddam and Masoud Kaveh
Future Internet 2025, 17(7), 279; https://doi.org/10.3390/fi17070279 - 24 Jun 2025
Viewed by 490
Abstract
The rapid expansion of Edge and Industrial Internet of Things (IIoT) systems has intensified the risk and complexity of cyberattacks. Detecting advanced intrusions in these heterogeneous and high-dimensional environments remains challenging. As the IIoT becomes integral to critical infrastructure, ensuring security is crucial [...] Read more.
The rapid expansion of Edge and Industrial Internet of Things (IIoT) systems has intensified the risk and complexity of cyberattacks. Detecting advanced intrusions in these heterogeneous and high-dimensional environments remains challenging. As the IIoT becomes integral to critical infrastructure, ensuring security is crucial to prevent disruptions and data breaches. Traditional IDS approaches often fall short against evolving threats, highlighting the need for intelligent and adaptive solutions. While deep learning (DL) offers strong capabilities for pattern recognition, single-model architectures often lack robustness. Thus, hybrid and optimized DL models are increasingly necessary to improve detection performance and address data imbalance and noise. In this study, we propose an optimized hybrid DL framework that combines a transformer, generative adversarial network (GAN), and autoencoder (AE) components, referred to as Transformer–GAN–AE, for robust intrusion detection in Edge and IIoT environments. To enhance the training and convergence of the GAN component, we integrate an improved chimp optimization algorithm (IChOA) for hyperparameter tuning and feature refinement. The proposed method is evaluated using three recent and comprehensive benchmark datasets, WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT, widely recognized as standard testbeds for IIoT intrusion detection research. Extensive experiments are conducted to assess the model’s performance compared to several state-of-the-art techniques, including standard GAN, convolutional neural network (CNN), deep belief network (DBN), time-series transformer (TST), bidirectional encoder representations from transformers (BERT), and extreme gradient boosting (XGBoost). Evaluation metrics include accuracy, recall, AUC, and run time. Results demonstrate that the proposed Transformer–GAN–AE framework outperforms all baseline methods, achieving a best accuracy of 98.92%, along with superior recall and AUC values. The integration of IChOA enhances GAN stability and accelerates training by optimizing hyperparameters. Together with the transformer for temporal feature extraction and the AE for denoising, the hybrid architecture effectively addresses complex, imbalanced intrusion data. The proposed optimized Transformer–GAN–AE model demonstrates high accuracy and robustness, offering a scalable solution for real-world Edge and IIoT intrusion detection. Full article
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27 pages, 892 KiB  
Article
A Blockchain Solution for the Internet of Vehicles with Better Filtering and Adaptive Capabilities
by Xueli Shen and Runyu Ma
Sensors 2025, 25(4), 1030; https://doi.org/10.3390/s25041030 - 9 Feb 2025
Viewed by 988
Abstract
The traditional consensus algorithm based on the Internet of Vehicles (IoV) system has the disadvantages of high latency, low reliability, and weak fault tolerance, and it cannot make real-time adjustments according to the actual environment, making the system vulnerable to malicious control, inefficiency, [...] Read more.
The traditional consensus algorithm based on the Internet of Vehicles (IoV) system has the disadvantages of high latency, low reliability, and weak fault tolerance, and it cannot make real-time adjustments according to the actual environment, making the system vulnerable to malicious control, inefficiency, and poor environmental adaptability. To solve this problem, we propose a gradually accelerating environment adaptive consensus algorithm, AE-PBFT, that can be applied to IoV. It includes a trust management model that achieves gradual acceleration by recording the historical continuous behavior of nodes, thereby improving the efficiency of screening nodes with different intentions, accelerating the consensus process, and reducing latency. At the same time, we introduce a dynamic consensus group division mechanism based on environmental adaptive changes, which can adaptively adjust the number of nodes participating in the consensus process according to the needs of the operating environment, to deal with extreme situations, thereby improving the reliability and fault tolerance of the system. Experiments confirm that the performance of our proposed solution is superior to current solutions in terms of consensus latency and fault tolerance and is more suitable for the operating environment of IoV. Full article
(This article belongs to the Section Internet of Things)
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22 pages, 2002 KiB  
Article
Characterization of the Pearl Millet Cultivation Environments in India: Status and Perspectives Enabled by Expanded Data Analytics and Digital Tools
by Vincent Garin, Sunita Choudhary, Tharanya Murugesan, Sivasakthi Kaliamoorthy, Madina Diancumba, Amir Hajjarpoor, Tara Satyavathi Chellapilla, Shashi Kumar Gupta and Jana Kholovà
Agronomy 2023, 13(6), 1607; https://doi.org/10.3390/agronomy13061607 - 14 Jun 2023
Cited by 5 | Viewed by 4747
Abstract
The cultivation of pearl millet in India is experiencing important transformations. Here, we propose a new characterization of the pearl millet production environment using the latest available district level data (1998–2017), principal component analysis, and large-scale crop model simulations. Pearl millet cultivation environment [...] Read more.
The cultivation of pearl millet in India is experiencing important transformations. Here, we propose a new characterization of the pearl millet production environment using the latest available district level data (1998–2017), principal component analysis, and large-scale crop model simulations. Pearl millet cultivation environment can be divided in up to five environments (TPEs). The eastern part of the country (Rajasthan, Haryana, Uttar Pradesh) emerges as the only region where pearl millet cultivation has grown (+0.4 Kha/year), with important yield increase (+51 kg/ha/year), and potential surplus that are likely exported. Important reductions of pearl millet cultivated area in Gujarat (−4.5 Kha/year), Maharashtra and Karnataka (−4 Kha/year) are potentially due to economy-driven transition to other more profitable crops, such as cotton or maize. The potential rain increase could also accelerate this transition. With R2 [0.15–0.61], the tested crop models reflected reasonably well the pearl millet production system in the A1 (North Radjasthan) and AE1 (South Rajastan and Haryana) TPEs covering the largest area (66%) and production share (59%), especially after the use of a new strategy for environment and management parameters calibration. Those results set the base for in silico system design and optimization in future climatic scenarios. Full article
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18 pages, 2039 KiB  
Article
DITES: A Lightweight and Flexible Dual-Core Isolated Trusted Execution SoC Based on RISC-V
by Yuehai Chen, Huarun Chen, Shaozhen Chen, Chao Han, Wujian Ye, Yijun Liu and Huihui Zhou
Sensors 2022, 22(16), 5981; https://doi.org/10.3390/s22165981 - 10 Aug 2022
Cited by 4 | Viewed by 3803
Abstract
A Trusted Execution Environment (TEE) is an efficient way to secure information. To obtain higher efficiency, the building of a dual-core system-on-chip (SoC) with TEE security capabilities is the hottest topic. However, TEE SoCs currently commonly use complex processor cores such as Rocket, [...] Read more.
A Trusted Execution Environment (TEE) is an efficient way to secure information. To obtain higher efficiency, the building of a dual-core system-on-chip (SoC) with TEE security capabilities is the hottest topic. However, TEE SoCs currently commonly use complex processor cores such as Rocket, resulting in high resource usage. More importantly, the cryptographic unit lacks flexibility and ignores secure communication in dual cores. To address the above problems, we propose DITES, a dual-core TEE SoC based on a Reduced Instruction Set Computer-V (RISC-V). At first, we designed a fully isolated multi-level bus architecture based on a lightweight RISC-V processor with an integrated crypto core supporting Secure Hashing Algorithm-1 (SHA1), Advanced Encryption Standard (AES), and Rivest–Shamir–Adleman (RSA), among which RSA can be configured to five key lengths. Then, we designed a secure boot based on Chain-of-Trust (CoT). Furthermore, we propose a hierarchical access policy to improve the security of inter-core communication. Finally, DITES is deployed on a Kintex 7 Field-Programmable-Gate-Array (FPGA) with a power consumption of 0.297 W, synthesized using TSMC 90 nm. From the results, the acceleration ratios of SHA1 and RSA1024 decryption/encryption can reach 75 and 1331/1493, respectively. Compared to exiting TEE SoCs, DITES has lower resource consumption, higher flexibility, and better security. Full article
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17 pages, 3571 KiB  
Article
Influence of Moisture Content and Wet Environment on the Fatigue Behaviour of High-Strength Concrete
by Mohamed Abubakar Ali, Christoph Tomann, Fadi Aldakheel, Markus Mahlbacher, Nima Noii, Nadja Oneschkow, Karl-Heinz Drake, Ludger Lohaus, Peter Wriggers and Michael Haist
Materials 2022, 15(3), 1025; https://doi.org/10.3390/ma15031025 - 28 Jan 2022
Cited by 24 | Viewed by 3410
Abstract
The influence of a wet environment on the fatigue behaviour of high-strength concrete has become more important in recent years with the expansion of offshore wind energy systems. According to the few investigations documented in the literature, the fatigue resistance of specimens submerged [...] Read more.
The influence of a wet environment on the fatigue behaviour of high-strength concrete has become more important in recent years with the expansion of offshore wind energy systems. According to the few investigations documented in the literature, the fatigue resistance of specimens submerged in water is significantly lower compared to that of specimens in dry conditions. However, it is still not clear how the wet environment and the moisture content in concrete influence its fatigue behaviour and which damage mechanisms are involved in the deterioration process. Here the results of a joint project are reported, in which the impact of moisture content in concrete on fatigue deterioration are investigated experimentally and numerically. Aside from the number of cycles to failure, the development of stiffness and acoustic emission (AE) hits are analysed as damage inductors and discussed along with results of microstructural investigations to provide insights into the degradation mechanisms. Subsequently, an efficient numeric modelling approach to water-induced fatigue damage is presented. The results of the fatigue tests show an accelerated degradation behaviour with increasing moisture content of the concrete. Further, it was found that the AE hits of specimens submerged in water occur exclusively close to the minimum stress level in contrast to specimens subjected to dry conditions, which means that additional damage mechanisms are acting with increasing moisture content in the concrete. Full article
(This article belongs to the Special Issue Cyclic Deterioration of Concrete)
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18 pages, 1727 KiB  
Article
Highly Efficient Implementation of Block Ciphers on Graphic Processing Units for Massively Large Data
by SangWoo An and Seog Chung Seo
Appl. Sci. 2020, 10(11), 3711; https://doi.org/10.3390/app10113711 - 27 May 2020
Cited by 21 | Viewed by 3986
Abstract
With the advent of IoT and Cloud computing service technology, the size of user data to be managed and file data to be transmitted has been significantly increased. To protect users’ personal information, it is necessary to encrypt it in secure and efficient [...] Read more.
With the advent of IoT and Cloud computing service technology, the size of user data to be managed and file data to be transmitted has been significantly increased. To protect users’ personal information, it is necessary to encrypt it in secure and efficient way. Since servers handling a number of clients or IoT devices have to encrypt a large amount of data without compromising service capabilities in real-time, Graphic Processing Units (GPUs) have been considered as a proper candidate for a crypto accelerator for processing a huge amount of data in this situation. In this paper, we present highly efficient implementations of block ciphers on NVIDIA GPUs (especially, Maxwell, Pascal, and Turing architectures) for environments using massively large data in IoT and Cloud computing applications. As block cipher algorithms, we choose AES, a representative standard block cipher algorithm; LEA, which was recently added in ISO/IEC 29192-2:2019 standard; and CHAM, a recently developed lightweight block cipher algorithm. To maximize the parallelism in the encryption process, we utilize Counter (CTR) mode of operation and customize it by using GPU’s characteristics. We applied several optimization techniques with respect to the characteristics of GPU architecture such as kernel parallelism, memory optimization, and CUDA stream. Furthermore, we optimized each target cipher by considering the algorithmic characteristics of each cipher by implementing the core part of each cipher with handcrafted inline PTX (Parallel Thread eXecution) codes, which are virtual assembly codes in CUDA platforms. With the application of our optimization techniques, in our implementation on RTX 2070 GPU, AES and LEA show up to 310 Gbps and 2.47 Tbps of throughput, respectively, which are 10.7% and 67% improved compared with the 279.86 Gbps and 1.47 Tbps of the previous best result. In the case of CHAM, this is the first optimized implementation on GPUs and it achieves 3.03 Tbps of throughput on RTX 2070 GPU. Full article
(This article belongs to the Special Issue Side Channel Attacks and Countermeasures)
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25 pages, 6955 KiB  
Article
Effect of High Temperature and Inclination Angle on Mechanical Properties and Fracture Behavior of Granite at Low Strain Rate
by Liang Chen, Xianbiao Mao and Peng Wu
Sustainability 2020, 12(3), 1255; https://doi.org/10.3390/su12031255 - 10 Feb 2020
Cited by 15 | Viewed by 3615
Abstract
Comprehensive understanding of the effects of temperature and inclination angle on mechanical properties and fracture modes of rock is essential for the design of rock engineering under complex loads, such as the construction of nuclear waste repository, geothermal energy development and stability assessment [...] Read more.
Comprehensive understanding of the effects of temperature and inclination angle on mechanical properties and fracture modes of rock is essential for the design of rock engineering under complex loads, such as the construction of nuclear waste repository, geothermal energy development and stability assessment of deep pillar. In this paper, a novel inclined uniaxial compression (inclined UCS) test system was introduced to carry out two series of inclined uniaxial compression tests on granite specimens under various inclination angles (0–20°) and treated temperatures (25–800 °C) at 5° inclination. Experimental results revealed that the peak compression stress and elastic modulus gradually decreased, while peak shear stress increased nonlinearly with the increasing inclination angle; the peak compression and shear stress as well as elastic modulus slightly increased from 25 to 200 °C, then gradually decreased onwards with the increasing temperature. The effect of temperature on peak axial strain was the same as that on peak shear displacement. Acoustic emission (AE) results suggested that the relationship between crack initiation stress, inclination angle and treated temperature followed a similar trend as that of the peak compression stress and elastic modulus. Particularly, the crack initiation (CI) stress threshold and shear stress corresponding to CI threshold under 800 °C were only 7.4% of that under 200 °C and revealed a severe heat damage phenomenon, which was consistent with the results of the scanning electron microscopy (SEM) with the appearance of a large number of thermal pores observed only under 800 °C. The failure modes tended to shear failure with the increasing inclination angle, indicating that the shear stress component can accelerate sliding instability of rocks. On the other hand, the failure patterns with different temperatures changed from combined splitting-shear failure (25–400 °C) to single shear failure (600 and 800 °C). The study results can provide an extremely important reference for underground thermal engineering construction under complex loading environment. Full article
(This article belongs to the Special Issue Sustainability Issues in Civil Engineering and Management)
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27 pages, 10587 KiB  
Article
Experimental Study on Physical-mechanical Properties and Fracture Behaviors of Saturated Yellow Sandstone Considering Coupling Effect of Freeze-Thaw and Specimen Inclination
by Liang Chen, Peng Wu, Yanlong Chen and Wei Zhang
Sustainability 2020, 12(3), 1029; https://doi.org/10.3390/su12031029 - 31 Jan 2020
Cited by 25 | Viewed by 3313
Abstract
The effect of freeze-thaw on the physical-mechanical properties and fracture behavior of rock under combined compression and shear loading was crucial for revealing the instability mechanism and optimizing the structure design of rock engineering in cold regions. However, there were few reports on [...] Read more.
The effect of freeze-thaw on the physical-mechanical properties and fracture behavior of rock under combined compression and shear loading was crucial for revealing the instability mechanism and optimizing the structure design of rock engineering in cold regions. However, there were few reports on the failure behavior of rock treated by freeze-thaw under combined compression and shear loading due to the lack of test equipment. In this work, a novel combined compression and shear test (C-CAST) system was introduced to carry out a series of uniaxial compression tests on saturated yellow sandstone under various inclination angles (θ = 0°, 5°, 10°, and 15°) and the number of freeze-thaw cycles (N = 0, 20, 40, and 60). The test results showed that the P-wave velocity dramatically decreased, while the rock quality and porosity increased gradually as N increased; the peak compression strength and elastic modulus obviously decreased with the increasing θ and N, while the peak shear stress increased gradually with the increasing θ and decreased with the increase of N, indicating that the shear stress component can accelerate the crack propagation and reduce its resistance to deformation. The acoustic emission (AE) results revealed that the change of crack initiation (CI) stress and crack damage (CD) stress with the θ and N had a similar trend as that of the peak compression strength and elastic modulus. Particularly, the CI and CD thresholds at 60 cycles were only 81.31% and 84.47% of that at 0° cycle and indicated a serious freeze-thaw damage phenomenon, which was consistent with the results of scanning electron microscopy (SEM) with the appearance of some large-size damage cracks. The fracture mode of sandstone was dependent on the inclination angle. The failure mode developed from both the tensile mode (0°) and combined tensile-shear mode (5°) to a pure shear failure (10°–15°) with the increasing inclination angle. Meanwhile, the freeze-thaw cycle only had an obvious effect on the failure mode of the specimen at a 5° inclination. Finally, a novel multivariate regression analysis method was used to predict the peak compression strength and elastic modulus based on the initial strength parameters (θ = 0°, N = 0). The study results can provide an important reference for the engineering design of rock subjected to a complex stress environment in cold regions. Full article
(This article belongs to the Special Issue Sustainability Issues in Civil Engineering and Management)
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18 pages, 4664 KiB  
Article
Ground Simulation Tests in Two-Dimensional Dynamic Acceleration Environment
by Yanbing Zhang, Tiehua Ma, Hongyan Zhang, Yaoyan Wu, Zhibo Wu and Junzhi Yu
Appl. Sci. 2020, 10(3), 910; https://doi.org/10.3390/app10030910 - 30 Jan 2020
Cited by 2 | Viewed by 2408
Abstract
Acceleration environment (AE) simulation tests have been widely applied in various areas such as aviation, space, environmental medicine, medical science, biomedicine, and materials. Most existing AE simulation test methods adopt impact and flight overload simulation separately, which cannot realize the synchronous controllable loading [...] Read more.
Acceleration environment (AE) simulation tests have been widely applied in various areas such as aviation, space, environmental medicine, medical science, biomedicine, and materials. Most existing AE simulation test methods adopt impact and flight overload simulation separately, which cannot realize the synchronous controllable loading of two-dimensional (2-D) dynamic acceleration. In this paper, we propose and implement an AE simulation test method using an air-cannon-started compound centrifugal turntable. Specifically, our method emphasizes two processes, i.e., orderly transition from impact overload to steady-state overload and synchronous loading of 2-D dynamic AE. To further facilitate the method verification in AE, we develop a specialized simulation test platform. During field tests, axial acceleration of the unit being tested reached 20 g in 0.12 s at the launching stage and radial acceleration raised from zero g to 40 g in 0.5 s at the flight stage, achieving simulation of the 2-D dynamic AE. The obtained results show the effectiveness of the proposed simulation method, shedding light on updated design and control of impact simulation tests on the structures of crystal oscillator circuit, acceleration sensors, and related instruments. Full article
(This article belongs to the Section Mechanical Engineering)
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