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RISS 인기검색어
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- 저자 : Trung Huy Ngo(Trung Huy Ngo ) (검색결과 6 건)
- 무료
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PSI-rooted subgraph: A novel feature for IoT botnet detection using classifier algorithms
Huy-Trung Nguyen,Quoc-Dung Ngo,Doan-Hieu Nguyen,Van-Hoang Le 한국통신학회 2020 ICT Express Vol.6 No.2
It is obvious that IoT devices are widely used more and more in many areas. However, due to limited resources (e.g., memory, CPU), the security mechanisms on many IoT devices such as IP-Camera, router are low. Therefore, botnets are an emerging threat to compromise IoT devices recently. To tackle this, a novel method for IoT botnets detection plays a crucial role. In this paper, we have some contributions for IoT botnet detection: first, we present a novel high-level PSI-rooted subgraph-based feature for the detection of IoT botnets; second, we generate a limited number of features that have precise behavioral descriptions, which require smaller space and reduce processing time; third, The evaluation results show the effectiveness and robustness of PSI-rooted subgraph-based features, as with five machine classifiers consisting of Random Forest, Decision Tree, Bagging, k-Nearest Neighbor, and Support Vector Machine, each classifier achieves more than 97% detection rate and low time-consuming. Moreover, compared to other work, our proposed method obtains better performance. Finally, we publicize all our materials on Github, which will benefit future research (e.g., IoT botnet detection approach).
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A Vapor Sensor Based on a Porous Silicon Microcavity for the Determination of Solvent Solutions
Huy Bui,Thuy Van Nguyen,The Anh Nguyen,Thanh Binh Pham,Quoc Trung Dang,Thuy Chi Do,Quang Minh Ngo,Roberto Coisson,Van Hoi Pham 한국광학회 2014 Current Optics and Photonics Vol.18 No.4
A porous silicon microcavity (PSMC) sensor has been made for vapors of solvent solutions, and a method has been developed in order to obtain simultaneous determination of two volatile substances with different concentrations. In our work, the temperature of the solution and the velocity of the air stream flowing through the solution have been used to control the response of the sensor for ethanol and acetone solutions. We study the dependence of the cavity-resonant wavelength shift on solvent concentration, velocity of the airflow and solution temperature. The wavelength shift depends linearly on concentration and increases with solution temperature and velocity of the airflow. The dependence of the wavelength shift on the solution temperature in the measurement contains properties of the temperature dependence of the solvent vapor pressure, which characterizes each solvent. As a result, the dependence of the wavelength shift on the solution temperature discriminates between solutions of ethanol and acetone with different concentrations. This suggests a possibility for the simultaneous determination of the volatile substances and their concentrations.
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FGW-FER: Lightweight Facial Expression Recognition with Attention
Huy-Hoang Dinh,Hong-Quan Do,Trung-Tung Doan,Cuong Le,Ngo Xuan Bach,Tu Minh Phuong,Viet-Vu Vu 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.9
The field of facial expression recognition (FER) has been actively researched to improve human-computer interaction. In recent years, deep learning techniques have gained popularity for addressing FER, with numerous studies proposing end-to-end frameworks that stack or widen significant convolutional neural network layers. While this has led to improved performance, it has also resulted in larger model sizes and longer inference times. To overcome this challenge, our work introduces a novel lightweight model architecture. The architecture incorporates three key factors: Depth-wise Separable Convolution, Residual Block, and Attention Modules. By doing so, we aim to strike a balance between model size, inference speed, and accuracy in FER tasks. Through extensive experimentation on popular benchmark FER datasets, our proposed method has demonstrated promising results. Notably, it stands out due to its substantial reduction in parameter count and faster inference time, while maintaining accuracy levels comparable to other lightweight models discussed in the existing literature.
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Efficacy of Veronica incana for Treating Osteoarthritis Induced by Monosodium Iodoacetate in Rats
이진아,Trung Huy Ngo,신유옥,최정원,최혁재,남주원,노성수 한국식품영양과학회 2023 Journal of medicinal food Vol.26 No.6
The aim of this study is to investigate the efficacy and the underlying mechanism of Veronica incana in osteoarthritis (OA) induced by intraarticular injection of monosodium iodoacetate (MIA). The selected major four compounds (A–D) of V. incana were found from fractions 3 and 4. Its structure elucidation was determined by liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS) data analysis and nuclear magnetic resonance (NMR) data comparison with literature. MIA (50 μL with 80 mg/mL) for the animal experiment was injected into the right knee joint. The V. incana was administered orally every day to rats for 14 days from 7 days after MIA treatment. Finally, we confirmed the four compounds: (A) verproside; (B) catalposide; (C) 6-vanilloylcatapol; and (D) 6-isovanilloylcatapol. When we evaluated the effect of V. incana on the MIA injection-induced knee OA model, there were a noticeable initial decreased in hind paw weight-bearing distribution compared to the Normal group (P < .001), but V. incana supplementation resulted in a significant increase in the weight-bearing distribution to the treated knee (P < .001). Moreover, the V. incana treatment led to a decrease in the levels of liver function enzymes and tissue malondialdehyde (P < .05 and .01). The V. incana significantly suppressed the inflammatory factors through the nuclear factor-kappa B signaling pathway and downregulated the expression of matrix metalloproteinases, which are involved in the degradation of the extracellular matrix (P < .01 and .001). In addition, we confirmed the alleviation of cartilage degeneration through tissue stains. In conclusion, this study confirmed the major four compounds of V. incana and suggested that V. incana could serve as an anti-inflammatory candidate agent for patients with OA.
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A survey of IoT malware and detection methods based on static features
Quoc-Dung Ngo,Huy-Trung Nguyen,Van-Hoang Le,Doan-Hieu Nguyen 한국통신학회 2020 ICT Express Vol.6 No.4
Due to a lack of security design as well as the specific characteristics of IoT devices such as the heterogeneity of processor architecture, IoT malware detection has to deal with very unique challenges, especially on detecting cross-architecture IoT malware. Therefore, the IoT malware detection domain is the focus of research by the security community in recent years. There are many studies taking advantages of well-known dynamic or static analysis for detecting IoT malware; however, static-based methods are more effective when addressing the multi-architecture issue. In this paper, we give a thorough survey of static IoT malware detection. We first introduce the definition, evolution and security threats of IoT malware. Then, we summarize, compare and analyze existing IoT malware detection methods proposed in recent years. Finally, we carry out exactly the methods of existing studies based on the same IoT malware dataset and an experimental configuration to evaluate objectively and increasing the reliability of these studies in detecting IoT malware.
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