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Towards improving detection performance for malware with a correntropy-based deep learning method

Digital Communications and Networks 2021年第4期7卷 570-579页

作者： Xiong Luo Jianyuan Li Weiping Wang Yang Gao Wenbing Zhao School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China Beijing Intelligent Logistics System Collaborative Innovation Center Beijing101149China China Information Technology Security Evaluation Center Beijing100085China Department of Electrical Engineering and Computer Science Cleveland State UniversityClevelandOH44115USA

With the rapid development of Internet of Things(IoT)technologies,the detection and analysis of malware have become a matter of concern in the industrial application of Cyber-Physical system(CPS)that provides various services using the IoT ***,many advanced machine learning methods such as deep learning are popular in the research of malware detection and analysis,and some achievements have been made so ***,there are also some *** example,considering the noise and outliers in the existing datasets of malware,some methods are not robust ***,the accuracy of malware classification still needs to be *** at this issue,we propose a novel method that combines the correntropy and the deep learning *** our proposed method for malware detection and analysis,given the success of the mixture correntropy as an effective similarity measure in addressing complex datasets with noise,it is therefore incorporated into a popular deep learning model,i.e.,Convolutional Neural Network(CNN),to reconstruct its loss function,with the purpose of further detecting the features of *** present the detailed design process of our ***,the proposed method is tested both on a real-world malware dataset and a popular benchmark dataset to verify its learning performance.

关键词： Malware detection Mixture correntropy Deep learning Convolutional neural network(CNN)

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A Triboelectric Tactile Sensor with Flower-Shaped Holes for Texture Recognition

SSRN

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SSRN 2023年

作者： Xing, Pengcheng An, Shanshan Wu, Yihan Li, Gui Liu, Sizhao Wang, Jian Cheng, Yuling Zhang, Yangsong Pu, Xianjie Department of Applied Physics State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials Chongqing University Chongqing400044 China School of Computer Science and Technology Laboratory for Brain Science and Medical Artificial Intelligence Southwest University of Science and Technology Mianyang621010 China

Touch is one of the important ways to perceive the surrounding environment. The surface texture is an essential character of an object. Here, we propose a dual-layer shielding triboelectric tactile sensor with patterned flower-shaped holes. The object surface to be measured is able to rub against the tribo-layer through the flower-shaped holes to produce a signal output. The patterned design of the tactile sensor is evolved from the contact state of the fingertips during human finger touch. In addition, two shielding layers were designed. The inner-shielding layer is used to shield the influence of the human body potential on the output signal, in order to achieve more accurate identification. The outer-shielding layer enables the flower-shaped holes to play their structural role. The proposed tactile sensor has the advantage of a single channel, resulting in a smaller amount of data collection and processing than the multi-channel scheme. With a designed convolutional neural network model, the recognition accuracy reaches 96.03% when recognizing 7 objects with designed different surface textures. The tactile sensing module can be easily integrated into intelligent haptic prosthesis and play an important role in future human-machine interfaces. © 2023, The Authors. All rights reserved.

关键词： Textures

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Reliability Evaluation and Improvement of Islanded Microgrid Considering Operation Failures of Power Electronic Equipment

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Journal of Modern Power systems and Clean Energy 2020年第1期8卷 111-123页

作者： Wen Zhong Lingfeng Wang Zhaoxi Liu Shiying Hou State Key Laboratory of Power Transmission Equipment&System Security and New Technology College of Electrical EngineeringChongqing UniversityChongqingChina Laboratory of Trustworthy Cyber-Physical Systems and Infrastructures Department of Electrical Engineering and Computer ScienceUniversity of Wisconsin-MilwaukeeMilwaukeeUSA

With the high integration of power electronic technologies in microgrids,the reliability assessment considering power electronic devices has become a hot ***,so far no research has considered the impact of the operation failure probability of power electronic equipment on the overall reliability of the *** paper aims to construct a holistic operation failure rate model of power electronic systems based on the overall reliability assessment of islanded microgrid with high penetration of renewable energy sources(RESs).In addition,to improve the reliability of islanded microgrid,the conventional battery energy storage system(BESS)is replaced by the hybrid energy storage system(HESS).Based on the proposed model,the operation failure models for the power electronic modules in microgrid are built and tested,and then the sensitivity analysis is performed for exploring the influence of various factors on the reliability of the microgrid.

关键词： Reliability assessment reliability improvement operation failure rate power electronics islanded microgrid

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Resilience Assessment of Urban Power Network Considering Multi-Stage Electrical-Water Fault Propagation

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IEEE Transactions on Power systems 2024年

作者： Shi, Qingxin Yan, Yilu Liu, Wenxia Zeng, Bo Wang, Zhuning Li, Fangxing North China Electric Power University State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources Beijing102206 China State Grid Suzhou Electric Company Suzhou215000 China Beijing Municipal Institute of City Planning & Design Beijing100032 China The University of Tennessee Department of Electrical and Computer Engineering KnoxvilleTN37996 United States

Multi-voltage-level urban power network (UPN) is the basis for other infrastructure networks, especially water distribution network (WDN). Compared with other networks, UPN is more vulnerable to extreme events, including extreme weather events and deliberate attacks. The affection of UPN fault on WDN displays complex multi-stage characteristics. This paper first proposes a comprehensive tri-stage model of electrical-water fault propagation, including the electrical-water network connection model, the reduced-order hydraulic network model, and the water supply model of customers. Second, a scenario selection method and two resilience assessment indices are proposed. The indices measure the resistive capability of UPN considering the fault propagation effect. Finally, the proposed model and assessment method are verified by a simplified real-world urban power and water network based on the selected typical fault scenarios. The resilience assessment method helps electrical utilities to identify critical components of UPN and to make optimal decisions for long-term component hardening and short-term post-disaster restoration. © 2024 IEEE.

关键词： Power distribution networks

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Ultrahigh-coherence microcomb generation and low-noise amplification using integrated photonics

Ultrahigh-coherence microcomb generation and low-noise ampli...

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IEEE Photonics Conference (IPC)

作者： Xuguang Zhang Zixuan Zhou Yijun Guo Minxue Zhuang Warren Jin Bitao Shen Yujun Chen Jiahui Huang Weiwei Hu Haowen Shu John E. Bowers Xingjun Wang Lin Chang State Key Laboratory of Advanced Optical Communications System and Networks School of Electronics Peking University Beijing China Department of Electrical and Computer Engineering University of California Santa Barbara Santa Barbara CA USA Frontiers Science Center for Nano-Optoelectronics Peking University Beijing China

ISBN: (数字)9798350361957

ISBN: (纸本)9798350361964

We demonstrate a high-coherence parallel integrated light source utilizing a self-injection locked microcomb and injection locking amplification. Our strategy exhibits a record high on-chip gain of 60 dB, nearly 0 dB noise factor, which enable more than 30 highly coherent channels in integrated photonics whose linewidths down to 10 Hz, power exceeding 20 dBm per line and a wall plug efficiency of 19%.

关键词： Injection-locked oscillators Noise system-on-chip Gain Photonics Plugs Light sources

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Language-Queried Target Sound Extraction Without Parallel Training Data

Language-Queried Target Sound Extraction Without Parallel Tr...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hao Ma Zhiyuan Peng Xu Li Yukai Li Mingjie Shao Qiuqiang Kong Ju Liu School of Information Science and Engineering Shandong University Qingdao China Department of Computer Science North Carolina State University North Carolina USA ARC Lab Tencent PCG Key Laboratory of System and Control AMSS Chinese Academy of Sciences Beijing China The Chinese University of Hong Kong China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Language-queried target sound extraction (TSE) aims to extract specific sounds from mixtures based on language queries. Traditional fully-supervised training schemes require extensively annotated parallel audio-text data, which are labor-intensive. We introduce a parallel-data-free training scheme, requiring only unlabelled audio clips for TSE model training by utilizing the contrastive language-audio pre-trained model (CLAP). In a vanilla parallel-data-free training stage, target audio is encoded using the pre-trained CLAP audio encoder to form a condition embedding, while during testing, user language queries are encoded by CLAP text encoder as the condition embedding. This vanilla approach assumes perfect alignment between text and audio embeddings, which is unrealistic. Two major challenges arise from training-testing mismatch: the persistent modality gap between text and audio and the risk of overfitting due to the exposure of rich acoustic details in target audio embedding during training. To address this, we propose a retrieval-augmented strategy. Specifically, we create an embedding cache using audio captions generated by a large language model (LLM). During training, target audio embeddings retrieve text embeddings from this cache to use as condition embeddings, ensuring consistent modalities between training and testing and eliminating information leakage. Extensive experiment results show that our retrieval-augmented approach achieves consistent and notable performance improvements over existing state-of-the-art with better generalizability.

关键词： Training Large language models Training data Signal processing Information leakage Acoustics Data models Data mining Speech processing Overfitting

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Fully integrated hybrid microwave photonic receiver

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Photonics Research 2022年第6期10卷 1472-1483页

作者： JIACHEN LI SIGANG YANG HONGWEI CHEN XINGJUN WANG MINGHUA CHEN WEIWEN ZOU Beijing National Research Center for Information Science and Technology(BNRist) Department of Electronic EngineeringTsinghua UniversityBeijing 100084China State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Microwave photonic receivers are a promising candidate in breaking the bandwidth limitation of traditional radio-frequency(RF)*** further balance the performance superiority with the requirements regarding size,weight,and power consumption(SWa P),the implementation of integrated microwave photonic microsystems has been considered an upgrade ***,up to now,to the best of our knowledge,chip-scale fully integrated microwave photonic receivers have not been reported due to the limitation of material *** this paper,we report a fully integrated hybrid microwave photonic receiver(FIH-MWPR)obtained by comprising the indium phosphide(In P)laser chip and the monolithic silicon-on-insulator(SOI)photonic circuit into the same substrate based on the low-coupling-loss micro-optics *** from the integration of all optoelectronic components,the packaged FIH-MWPR exhibits a compact volume of 6 cmand low power consumption of 1.2 *** FIH-MWPR supports a wide operation bandwidth from 2 to 18 ***,its RF-link performance to down-convert the RF signals to the intermediate frequency is experimentally characterized by measuring the link gain,the noise figure,and the spurious-free dynamic range metrics across the whole operation frequency ***,we have utilized it as a de-chirp receiver to process the broadband linear frequencymodulated(LFM)radar echo signals at different frequency bands(S-,C-,X-,and Ku-bands)and successfully demonstrated its high-resolution-ranging *** the best of our knowledge,this is the first realization of a chip-scale broadband fully integrated microwave photonic receiver,which is expected to be an important step in demonstrating the feasibility of all-integrated microwave photonic microsystems oriented to miniaturized application scenarios.

关键词： method microwave bands

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LotusMenu: a 3D menu using wrist and elbow rotation inspired by Chinese traditional symbol

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Science China(Information Sciences) 2021年第10期64卷 242-244页

作者： Fei LYU Yujie LIU Jin HUANG Zhaolin ZHANG School of Digital Media and Design Arts Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences

Three-dimensional rotation, including pitching, yawing and rolling, is an important gesture in 3D interaction, with the potential to extend the selection capability in large screen interaction system. For 3D rotation interaction, researchers indicated the design space of pen tilt [1] and wrist tilt as input modality [2, 3]. However, the combination of freehand 3D rotation gesture has not been fully utilized for menu control.

关键词： Information systems and Communication Service

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Prototype Guided Personalized Federated Intrusion Detection system

Prototype Guided Personalized Federated Intrusion Detection ...

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Smart World Congress (SWC), IEEE

作者： Long Cheng Huiru Yan Hanlin Zhou Ying Wang Haichuan Tang Fang Fang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing China Chinese Academy of Sciences Institute of Computing Technology Beijing China AI Lab of CRRC Academy Beijing China

ISBN: (数字)9798331520861

ISBN: (纸本)9798331520878

Preventing network attacks and protecting user privacy are consistently hot research topics in the Internet of Things (IoT) and edge computing fields. Recent advancements in Federated Learning (FL) have shown promise in addressing these challenges. FL allows various clients to collaboratively build an intrusion detection system (IDS) without sharing their private data. However, most existing methods train a single intrusion detection model for all clients and assume that the training and test data distribution are identical, leading to unsatisfactory detection accuracy and generalization abilities in practice. To overcome these challenges, this paper introduces a prototype-guided personalized FL approach named PG-FedIDS. We propose two novel mechanisms within this method. Firstly, we utilize class prototypes as auxiliary information carriers to generate personalized models for each client, rather than generating a single global model as in previous works. Secondly, we propose a prototype-guided ensemble learning strategy, which can leverage the global knowledge in prototypes to enhance detection accuracy and generalization abilities for each client. We conduct extensive experiments on two benchmark datasets with different evaluation test settings. The results demonstrate that our PG-FedIDS achieves promising detection accuracy and consistently outperforms other FL baselines.

关键词： Training Privacy Accuracy Federated learning Image edge detection Prototypes Intrusion detection Data models Ensemble learning Internet of Things

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LU2Net: A Lightweight Network for Real-time Underwater Image Enhancement

arXiv

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arXiv 2024年

作者： Yang, Haodong Xu, Jisheng Lin, Zhiliang He, Jianping The Department of Computer Science Shanghai Jiao Tong University China The Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China The School of Ocean and Civil Engineering Shanghai Jiao Tong University State Key Laboratory of Ocean Engineering Shanghai200240 China

computer vision techniques have empowered underwater robots to effectively undertake a multitude of tasks, including object tracking and path planning. However, underwater optical factors like light refraction and absorption present challenges to underwater vision, which cause degradation of underwater images. A variety of underwater image enhancement methods have been proposed to improve the effectiveness of underwater vision perception. Nevertheless, for real-time vision tasks on underwater robots, it is necessary to overcome the challenges associated with algorithmic efficiency and real-time capabilities. In this paper, we introduce Lightweight Underwater Unet (LU2Net), a novel U-shape network designed specifically for real-time enhancement of underwater images. The proposed model incorporates axial depthwise convolution and the channel attention module, enabling it to significantly reduce computational demands and model parameters, thereby improving processing speed. The extensive experiments conducted on the dataset and real-world underwater robots demonstrate the exceptional performance and speed of proposed model. It is capable of providing well-enhanced underwater images at a speed 8 times faster than the current state-of-the-art underwater image enhancement method. Moreover, LU2Net is able to handle real-time underwater video enhancement. Copyright © 2024, The Authors. All rights reserved.

关键词： Motion planning

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