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检索条件"机构=Signal/Image Processing Laboratory"

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Efficient RNN Models for IOT Intrusion Detection System

Efficient RNN Models for IOT Intrusion Detection System

引用

2024 International Conference on Control, Automation and Diagnosis, ICCAD 2024

作者： Jablaoui, Rahma Liouane, Noureddine University of Monastir Laboratory of Automatic Signal and Image Processing Monastir Tunisia

ISBN: (纸本)9798350361025

Due to the growing number of network devices, traffics and services, designing robust Intrusion Detection System (IDS) become a crucial need in the face of complex and various network attacks as a protective measure from hackers and cybercriminals. However, the traditional Machine Learning (ML) approach shows success in many research topics but with the increase in the amount of data and the diversification of network threats methods, it seems to lack reliability and accuracy. Therefore, considering a large amount of real-world cyber traffic, Deep Learning (DL) may be able to extract big data features more effectively. In this paper, we suggest an intrusion detection system for the Internet of Things (IoT) network based on Deep Learning to recognize various assault types for both binary and multiclass classification using two variants of Recurrent Neural Network (RNN) models long short-term memory (LSTM) and Bidirectional LSTM (BiLSTM). We have experimented the models with CSE-CIC-IDS2018, which is the newest comprehensive network traffic dataset. Accuracy, precision, recall, and F1 score are a few performance criteria where the suggested approach clearly excels. After comparison, we can infer that Bi-directional LSTM outperforms LSTM and other existing efforts in the literature. The accuracy of the experimental results was high, coming in at 98.62%. © 2024 IEEE.

关键词： Computer crime

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An effective deep CNN-LSTM based intrusion detection system for network security

An effective deep CNN-LSTM based intrusion detection system ...

引用

2024 International Conference on Control, Automation and Diagnosis, ICCAD 2024

作者： Jablaoui, Rahma Liouane, Noureddine University of Monastir Laboratory of Automatic Signal and Image Processing Monastir Tunisia

ISBN: (纸本)9798350361025

Deep learning (DL) models have become prevalent and consistently exhibit outstanding performance across diverse domains, particularly in information security. As a subset of machine learning (ML), DL has proven adept at handling complex, unstructured, and large-scale data, making it well-suited to tackle the evolving challenges of cybersecurity. By leveraging DL techniques, we can develop robust intrusion detection systems (IDS) to counter a wide range of network attacks, serving as a crucial defense against hackers and cybercriminals. The integration of DL into IDS holds immense potential for significantly enhancing network security and mitigating cyber risks in various real-world scenarios. This work proposes an IDS architecture that integrates Convolutional Neural Network (CNN) for spatial feature extraction and Long Short-Term Memory (LSTM) for temporal feature extraction and sequential analysis to predict and classify malicious cyberattacks in IoT network traffic. Our experiments with the CSE-CIC-IDS2018 dataset, the latest comprehensive network traffic dataset, demonstrate the superiority of our approach in terms of accuracy, precision, recall, and F1 score. Our model achieves an unprecedented accuracy of over 99% in both binary and multiclass classification, surpassing existing efforts in the literature. © 2024 IEEE.

关键词： Long short-term memory

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Robust Adaptive Sliding Mode Control of Upper-Limb Rehabilitation Exoskeleton System with Uncertainties

Robust Adaptive Sliding Mode Control of Upper-Limb Rehabilit...

引用

2024 International Conference on Control, Automation and Diagnosis, ICCAD 2024

作者： Hassen, Mouna Dali Jouirou, Raghda Bouguila, Nasreddine University of Monastir Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir 5019 Tunisia National School of Engineers of Monastir Laboratory of Automatic Signal and Image Processing 5019 Tunisia

ISBN: (纸本)9798350361025

Uncertain robotic manipulator systems, known for their high nonlinearities, unmodeled dynamics, and uncertainties, are the subject of this paper. Based on the terminal sliding mode control algorithm and its nonsingular design method, a new robust control scheme is introduced to ensure fast and finite time convergence to the desired state. The upper bounds of unknown system uncertainties are estimated using adaptive control. The stability of the proposed control strategy is confirmed by the Lyapunov theory, and its effectiveness is tested on a two-degrees-of-freedom robotic manipulator. Robustness and rapid convergence, as well as reducing the controller's high-frequency commutation effect, are proved. © 2024 IEEE.

关键词： Sliding mode control

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A Machine Learning-based Intelligent ID System for the Internet of Things

A Machine Learning-based Intelligent ID System for the Inter...

引用

2024 IEEE International Conference on Advanced Systems and Emergent Technologies, IC_ASET 2024

作者： Sawssen, Bacha Noureeddine, Liouane Laboratory of Automatic Signal and Image Processing National Engineering School of Monastir University of Monastir Tunisia

ISBN: (纸本)9798350384895

The Internet of Things, or loT, is a rapidly expanding field that has been integrated into numerous different industries. Thanks to this technology, devices may send, receive, and analyze data without the assistance of a human. loT security and privacy concerns continue to be a significant obstacle, despite the fact that it has gained widespread acceptance in a number of important domains due to its ability to simplify human life and enhance service quality. To protect loT networks from different attacks, an anomaly-based intrusion detection system (IDS) can be included as a security feature. In order to combat various cyberattacks in Internet of Things environments, this study suggests an anomaly-based intrusion detection system (IDS). The suggested approach makes use of in order to enhance anomaly identification performance and reduce the dimension of the data characteristics.. © 2024 IEEE.

关键词： Intrusion detection

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Ideal Behavior of Vernier and Flash TDCs Implemented in a Spartan-6 FPGA

Ideal Behavior of Vernier and Flash TDCs Implemented in a Sp...

引用

2023 International Conference on Advances in Electronics, Control and Communication Systems, ICAECCS 2023

作者： Chouial, Wafia Maamoun, Mountassar Signal Processing and Image Laboratory University of Blida 1 Blida Algeria

ISBN: (纸本)9781665463102

In this paper, we will illustrate the working principle of the most popular time-to-digital converter (TDC) architectures in both application specific integrated circuits (ASIC) and field programmable gate array (FPGA) applications - Vernier and tapped delay line (TDL) designs are used as a time interpolation method to yield a sub-clock period resolution. In order to understand their mechanism, Vernier and TDL-derived configurations are described first. Then, we propose a simulation work relying on fixing the finite propagation speed of each delay element of the delay chain to a delay equal to one or two clock cycles of the system clock period. That aims to assure the uniformity of the TDC binning and to eliminate the effect of process, voltage, and temperature (PVT) variations, which results in an ideal behavior of TDC that will be reflected in an ideal thermometer code. We have designed, implemented, and tested ideal TDCs in low-cost Spartan-6 FPGA, as well as by using the Xilinx ISIM tool. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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A High-Efficiency Doppler Frequency Parallel Acquisition Method Based on A-GPS

A High-Efficiency Doppler Frequency Parallel Acquisition Met...

引用

2025 International Technical Meeting of The Institute of Navigation, ITM 2025

作者： Jia, Qiongqiong Zhao, Yuchen China Civil Aviation University Tianjin Key Laboratory of Intelligent Signal and Image Processing Tianjin300000 China

ISBN: (纸本)9780936406404

Acquisition is a key step for Global Navigation Satellite System (GNSS) receivers to achieve positioning and other functions, and the acquisition speed directly affects the Time To First Fix (TTFF) of the receiver. The acquisition process typically involves generating local reference signals for all satellite signals and matching them with the received signals. For each satellite signal, this matching involves searching in the unknown Doppler frequency and code phase space. Traditional parallel acquisition methods can only perform parallel processing in either the Doppler frequency dimension or the code phase dimension, and still require linear search in the other dimension. To reduce the computational load and improve the acquisition efficiency, this paper proposes a high-efficiency parallel acquisition method based on A-GPS. This method utilizes the auxiliary information provided by the A-GPS base station to convert the linear search of visible star signals in Doppler frequency into a single parallel search in the Doppler search space, thereby reducing the computational load required for acquisition to 1/N of the conventional method, where N is the total number of frequency bands searched. The paper verifies through theoretical analysis and experimental results that the proposed method can significantly improve acquisition efficiency while ensuring acquisition performance. © 2025 Proceedings of the International Technical Meeting of The Institute of Navigation, ITM. All rights reserved.

关键词： Global positioning system

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Design of Dual-mode DPE Receiver Based on GPS L1/BDS B1C signals

Design of Dual-mode DPE Receiver Based on GPS L1/BDS B1C Sig...

引用

2025 International Technical Meeting of The Institute of Navigation, ITM 2025

作者： Jia, Qiongqiong Guo, Qiqi Tianjin Key Laboratory of Intelligent Signal and Image Processing Civil Aviation University of China Tianjin300000 China

ISBN: (纸本)9780936406404

With the expanding applications of the Global Navigation Satellite System (GNSS), its operating environment has become increasingly complex, with challenges such as multipath effects, non-line-of-sight (NLOS) propagation, and signal attenuation caused by tall urban buildings and trees. This complexity poses additional challenges for traditional GNSS receivers. Direct Position Estimation (DPE) addresses some of the limitations of traditional receivers by accumulating signals from all visible satellites directly in the navigation domain. However, when severe obstructions result in a reduced number of visible satellites, DPE may fail to function properly. The introduction of multiconstellation satellite signals can help mitigate the issue of insufficient visible satellites in complex environments. Based on this, this paper designs a dual-mode DPE receiver utilizing Global Positioning System (GPS) L1 signals and BeiDou Navigation Satellite System (BDS) B1C signals. © 2025 Proceedings of the International Technical Meeting of The Institute of Navigation, ITM. All rights reserved.

关键词： Global positioning system

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Robust Fuzzy Terminal Sliding Mode Control for Passive Control of Upper-Limb Exoskeleton

Robust Fuzzy Terminal Sliding Mode Control for Passive Contr...

引用

2024 International Conference on Control, Automation and Diagnosis, ICCAD 2024

作者： Hassen, Mouna Dali Jouirou, Raghda Bouguila, Nasreddine University of Monastir Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir 5019 Tunisia

ISBN: (纸本)9798350361025

Uncertain robotic manipulator systems, known for their high nonlinearities, unmodeled dynamics, and uncertainties, are the subject of this paper. Based on the terminal sliding mode control algorithm and its nonsingular design method, a new robust fuzzy control scheme is introduced to ensure fast and finite time convergence to the desired state. The stability of the proposed control strategy is confirmed by the Lyapunov theory, and its effectiveness is tested on a two-degrees-of-freedom robotic manipulator. Robustness and rapid convergence, as well as reducing the controller's high-frequency commutation effect, are proved. © 2024 IEEE.

关键词： Sliding mode control

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An optimal nonlinear predictive control based on a decoupled ARX-Laguerre multimodel

An optimal nonlinear predictive control based on a decoupled...

引用

2024 International Conference on Control, Automation and Diagnosis, ICCAD 2024

作者： Adaily, Sameh Mbarek, Abdelkader Garna, Tarek University of Monastir Laboratory of Automatic Signal and Image Processing National Engineering School of Monastir 5019 Tunisia

ISBN: (纸本)9798350361025

This paper deals with the representation of invariant, causal and stable systems on orthogonal Laguerre bases by combining the multimodel approach with the output and the input filtering principle. This representation allows the modeling of a large class of nonlinear systems and guarantees a significant parametric reduction. The resulting model of this representation is entitled ARX-Laguerre multimodel where the output is written as a linear combination of Laguerre filters and the Fourier coefficients. Thus, a new control technique of nonlinear systems, is proposed based on decoupled ARX-Laguerre multimodel. © 2024 IEEE.

关键词： Nonlinear systems

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Geometric Algebra Based Kalman Filter Trajectory Prediction 3

Geometric Algebra Based Kalman Filter Trajectory Prediction

引用

3rd International Symposium on Aerospace Engineering and Systems, ISAES 2024

作者： Li, Taiyu Jiao, Weidong Civil Aviation University of China Tianjin Key Laboratory of Intelligent Signal and Image Processing Tianjin China

ISBN: (纸本)9798350350418

To improve the safety and efficiency of aviation operation, a Kalman filtered trajectory prediction algorithm based on geometric algebra is proposed in this space. Firstly, the Kalman filter equations for trajectory prediction in geometric algebraic space are given by taking position, velocity and acceleration as state variables and position, velocity and acceleration in a typical trajectory as observations. Secondly, the matrix operation in the geometric algebraic space is simplified to the matrix operation by establishing a composite geometric algebraic space. Then, the versor operator in the conformal geometric algebraic space is introduced into the Kalman filter, and the steps of geometric algebra-based Kalman filter trajectory prediction are given to improve the prediction rate and accuracy. The experimental results show that the proposed trajectory prediction algorithm has the highest accuracy and the operation efficiency is improved by 27.66% compared with the Kalman filter algorithm in Euclidean space and the DBSCAN clustering algorithm. © 2024 IEEE.

关键词： Trajectories

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