Dear Editor,Dummy attack(DA), a deep stealthy but impactful data integrity attack on power industrial control processes, is recently recognized as hiding the corrupted measurements in normal measurements. In this lett...
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Dear Editor,Dummy attack(DA), a deep stealthy but impactful data integrity attack on power industrial control processes, is recently recognized as hiding the corrupted measurements in normal measurements. In this letter, targeting a more practical case, we aim to detect the oneshot DA, with the purpose of revealing the DA once it is ***, we first formulate an optimization problem to generate one-shot DAs. Then, an unsupervised data-driven approach based on a modified local outlier factor(MLOF) is proposed to detect them.
Dear Editor,This letter is concerned with visual perception closely related to heterogeneous *** the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous...
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Dear Editor,This letter is concerned with visual perception closely related to heterogeneous *** the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous image knowledge,i.e.,the domain knowledge associated with specific vision tasks,to better address the corresponding visual perception problems.
Nonstationary time series are ubiquitous in almost all natural and engineering *** the time-varying signatures from nonstationary time series is still a challenging problem for data *** Time-Frequency Distribution(TFD...
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Nonstationary time series are ubiquitous in almost all natural and engineering *** the time-varying signatures from nonstationary time series is still a challenging problem for data *** Time-Frequency Distribution(TFD)provides a powerful tool to analyze these ***,they suffer from Cross-Term(CT)issues that impair the readability of ***,to achieve high-resolution and CT-free TFDs,an end-to-end architecture termed Quadratic TF-Net(QTFN)is proposed in this *** by classic TFD theory,the design of this deep learning architecture is heuristic,which firstly generates various basis functions through ***,more comprehensive TF features can be extracted by these basis ***,to balance the results of various basis functions adaptively,the Efficient Channel Attention(ECA)block is also embedded into ***,a new structure called Muti-scale Residual Encoder-Decoder(MRED)is also proposed to improve the learning ability of the model by highly integrating the multi-scale learning and encoder-decoder ***,although the model is only trained by synthetic signals,both synthetic and real-world signals are tested to validate the generalization capability and superiority of the proposed QTFN.
The globalization of hardware designs and supply chains,as well as the integration of third-party intellectual property(IP)cores,has led to an increased focus from malicious attackers on computing ***,existing defense...
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The globalization of hardware designs and supply chains,as well as the integration of third-party intellectual property(IP)cores,has led to an increased focus from malicious attackers on computing ***,existing defense or detection approaches often require additional circuitry to perform security verification,and are thus constrained by time and resource *** the scale of actual engineering tasks and tight project schedules,it is usually difficult to implement designs for all modules in field programmable gate array(FPGA)*** studies have pointed out that the failure of key modules tends to cause greater damage to the ***,under limited conditions,priority protection designs need to be made on key modules to improve protection *** have conducted research on FPGA designs including single FPGA systems and multi-FPGA systems,to identify key modules in FPGA *** the single FPGA designs,considering the topological structure,network characteristics,and directionality of FPGA designs,we propose a node importance evaluationmethod based on the technique for order preference by similarity to an ideal solution(TOPSIS)***,for the multi-FPGA designs,considering the influence of nodes in intra-layer and inter-layers,they are constructed into the interdependent network,and we propose a method based on connection strength to identify the important ***,we conduct empirical research using actual FPGA designs as *** results indicate that compared to other traditional indexes,node importance indexes proposed for different designs can better characterize the importance of nodes.
Recent incidents have shown the attacks against Industrial control System (ICS), which may result in failure or even catastrophe and prompt the studies of defense. Existing security systems are mostly based on network...
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Accurately detecting leaks in natural gas gathering pipelines cannot only help enterprises and governments timely cope with the safety management problems, but also maintain the reliable operation of pipelines. The da...
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ISBN:
(纸本)9798350368604
Accurately detecting leaks in natural gas gathering pipelines cannot only help enterprises and governments timely cope with the safety management problems, but also maintain the reliable operation of pipelines. The data-driven approaches for leak detection have become a preferred solution with the widely installation of sensors in pipeline network. However, these methods face challenges in achieving high identification accuracy due to the lack of labeled leak data and insufficient representation learning. To overcome this difficulty, an unsupervised leak detection method that leverages twin attention-based prediction models is proposed for these gathering pipelines in this article. First, attention-based point and sequence prediction approaches are designed by joint utilization of attention mechanism (AM) and the cascade of one-dimensional convolutional network (1D-CNN) and long short-term memory (LSTM) network, where the sequence one also employs the operation of sequence repetition and flipping for better prediction. Based on the designed attention-based point and sequence prediction approaches, an unsupervised twin attention-based prediction structure is then introduced to jointly establish the normal pipeline models. Specifically, the point prediction model is mainly used to learn the short-term dependency patterns whereas the sequence prediction model for the long-term ones from the multivariate time series. Next, a fusion strategy is presented to fuse the prediction errors generated from the twin attention-based models for the computing of overall leak scores as well as exploiting their complementary detection sensibility. To obtain clear status of pipelines without affected by abnormal points resulting from device anomalies or noises, the minimum covariance determinant (MCD) approach is adopted to attain the reliable leak scores of the fused errors. The experimental results on datasets derived from real-world gathering pipelines validate the effectiveness of
Massive streaming data is the most current technology for storing and manipulating large quantities of data. Processing the substantial amount of streaming data is still a challenging issue. The speed and throughput c...
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As one of the most effective techniques for finding software vulnerabilities,fuzzing has become a hot topic in software *** feeds potentially syntactically or semantically malformed test data to a target program to mi...
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As one of the most effective techniques for finding software vulnerabilities,fuzzing has become a hot topic in software *** feeds potentially syntactically or semantically malformed test data to a target program to mine vulnerabilities and crash the *** recent years,considerable efforts have been dedicated by researchers and practitioners towards improving fuzzing,so there aremore and more methods and forms,whichmake it difficult to have a comprehensive understanding of the *** paper conducts a thorough survey of fuzzing,focusing on its general process,classification,common application scenarios,and some state-of-the-art techniques that have been introduced to improve its ***,this paper puts forward key research challenges and proposes possible future research directions that may provide new insights for researchers.
This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological *** is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and *** foragin...
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This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological *** is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and *** foraging behavior prompts the bison to seek a richer food source for *** bison find a food source,they stick around for a while by bathing *** jousting behavior makes bison stand out in the population,then the winner gets the chance to produce offspring in the mating *** eliminating behavior causes the old or injured bison to be weeded out from the herd,thus maintaining the excellent *** above behaviors are translated into ABO by mathematical *** assess the reliability and performance of ABO,it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with *** findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.
Reliable and accurate short-term forecasting of residential load plays an important role in DSM. However, the high uncertainty inherent in single-user loads makes them difficult to forecast accurately. Various traditi...
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