Edge computing, which achieves quick data processing by sinking data computing and storage to the network edge, has grown rapidly along with the Internet of things. The new network architecture of edge computing bring...
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Edge computing, which achieves quick data processing by sinking data computing and storage to the network edge, has grown rapidly along with the Internet of things. The new network architecture of edge computing brings new security challenges. Based on this, this paper investigates the edge computing security literature published in recent years and summarizes and analyzes research work on edge computing security from different attack surfaces. We start with the definition and architecture of edge computing. From the attack surface between device and edge server, as well as on edge servers, the research describes the security threats anddefense methods of edge computing. In addition, the cause of the attack and the pros and cons of defense methods is introduced. The challenges and future research directions of edge computing are given.
With the development of knowledge graphs, a series of applications based on knowledge graphs have emerged. The incompleteness of knowledge graphs makes the effect of the downstream applications affected by the quality...
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With the development of knowledge graphs, a series of applications based on knowledge graphs have emerged. The incompleteness of knowledge graphs makes the effect of the downstream applications affected by the quality of the knowledge graphs. To improve the quality of knowledge graphs, translation-based graph embeddings such as TransE, learn structural information by representing triples as low-dimensional dense vectors. However, it is difficult to generalize to the unseen entities that are not observedduring training but appearduring testing. Other methods use the powerful representational ability of pre-trained language models to learn entity descriptions and contextual representation of triples. Although they are robust to incompleteness, they need to calculate the score of all candidate entities for each triple during inference. We consider combining two models to enhance the robustness of unseen entities by semantic information, and prevent combined explosion by reducing inference overhead through structured information. We use a pre-training language model to code triples and learn the semantic information within them, and use a hyperbolic space-baseddistance model to learn structural information, then integrate the two types of information together. We evaluate our model by performing link prediction experiments on standarddatasets. The experimental results show that our model achieves better performances than state-of-the-art methods on two standarddatasets.
Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities orrelations in multi-modal knowledge graphs,thereby discovering more previously unknown *** to the continuous growth of data and knowledg...
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Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities orrelations in multi-modal knowledge graphs,thereby discovering more previously unknown *** to the continuous growth of data and knowledge and the limitations of data sources,the visual knowledge within the knowledge graphs is generally of low quality,and some entities suffer from the issue of missing visual ***,previous studies of MMKGC have primarily focused on how to facilitate modality interaction and fusion while neglecting the problems of low modality quality and modality *** this case,mainstream MMKGC models only use pre-trained visual encoders to extract features and transfer the semantic information to the joint embeddings through modal fusion,which inevitably suffers from problems such as error propagation and increased *** address these problems,we propose a Multi-modal knowledge graph Completion model based on Super-resolution anddetaileddescription Generation(MMCSd).Specifically,we leverage a pre-trainedresidual network to enhance the resolution and improve the quality of the visual ***,we design multi-level visual semantic extraction and entity description generation,thereby further extracting entity semantics from structural triples and visual ***,we train a variational multi-modal auto-encoder and utilize a pre-trained multi-modal language model to complement the missing visual *** conducted experiments on FB15K-237 anddB13K,and the results showed that MMCSd can effectively perform MMKGC and achieve state-of-the-art performance.
Adversarial distillation(Ad)has emerged as a potential solution to tackle the challenging optimization problem of loss with hard labels in adversarial ***,fixed sample-agnostic and student-egocentric attack strategies...
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Adversarial distillation(Ad)has emerged as a potential solution to tackle the challenging optimization problem of loss with hard labels in adversarial ***,fixed sample-agnostic and student-egocentric attack strategies are unsuitable for ***,the reliability of guidance from static teachers diminishes as target models become more *** paper proposes an Ad method called Learnable distillation Attack Strategies and Evolvable Teachers Adversarial distillation(LdAS&ET-Ad).Firstly,a learnable distillation attack strategies generating mechanism is developed to automatically generate sample-dependent attack strategies tailored fordistillation.A strategy model is introduced to produce attack strategies that enable adversarial examples(AEs)to be created in areas where the target model significantly diverges from the teachers by competing with the target model in minimizing or maximizing the Ad ***,a teacher evolution strategy is introduced to enhance the reliability and effectiveness of knowledge in improving the generalization performance of the target *** calculating the experimentally updated target model’s validation performance on both clean samples and AEs,the impact of distillation from each training sample and AE on the target model’s generalization androbustness abilities is assessed to serve as feedback to fine-tune standard androbust teachers *** evaluate the performance of LdAS&ET-Ad against different adversarial attacks on the CIFAr-10 and CIFAr-100 *** experimental results demonstrate that the proposed method achieves a robust precision of 45.39%and 42.63%against AutoAttack(AA)on the CIFAr-10 dataset forresNet-18 and MobileNet-V2,respectively,marking an improvement of 2.31%and 3.49%over the baseline *** comparison to state-of-the-art adversarial defense techniques,our method surpasses Introspective Adversarial distillation,the top-performing method in terms of robustne
Scientifc interpretation of paradigm. The concept and theory of paradigm were first proposed by Thomas Kuhn, a famous American science philosopher, and were systematically described in his book “The Structure of Scie...
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Scientifc interpretation of paradigm. The concept and theory of paradigm were first proposed by Thomas Kuhn, a famous American science philosopher, and were systematically described in his book “The Structure of Scientific revolutions” [1] published in 1962. He pointed out that a paradigm
Quite operation of home appliances is one of the most significant criteria used by customers, when they select the exact device among several devices with similar functionality. In such circumstances, even minor noise...
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Uncertain security threats caused by vulnerabilities and backdoors are the most serious anddifficult problem in *** paper analyzes the philosophical and technical causes of the existence of so-called"dark functi...
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Uncertain security threats caused by vulnerabilities and backdoors are the most serious anddifficult problem in *** paper analyzes the philosophical and technical causes of the existence of so-called"dark functions"such as system vulnerabilities and backdoors,and points out that endogenous security problems cannot be completely eliminated at the theoretical and engineering levels;rather,it is necessary to develop or utilize the endogenous security functions of the system architecture *** addition,this paper gives a definition for and lists the main technical characteristics of endogenous safety and security in cyberspace,introduces endogenous safety and security mechanisms and characteristics based on dynamic heterogeneous redundancy(dHr)architecture,anddescribes the theoretical implications of a coding channel based on dHr.
In this study, an alternative data sampling method is proposed fordeep learning models. In the suggested method, 3-stage sampling is done by using sequential frames. In the sampling process, a 5-minute 30 fps video i...
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In the context of smart cities, real-time vehicle speeddetection is a research area that can be examined under the categories of traditional and hybrid methods. Traditional methods encompass existing radar and Lidar ...
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In this paper a 1 to 4 time-delay power-divider was provided. The phase and amplitude relation between each port was simulated. The time-delay between the port was 0.016 ns in the x-direction and 0.16 ns in the x-dire...
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