Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

SSD Real-Time Illegal Parking Detection Based on Contextual Information Transmission

With the improvement of the national economic level,the number of vehicles is still increasing year by year.According to the statistics of National Bureau of Statics,the number is approximately up to 327 million in China by the end of 2018,which makes urban traffic pressure continues to rise so that the negative impact of urban traffic order is growing.Illegal parking-the common problem in the field of transportation security is urgent to be solved and traditional methods to address it are mainly based on ground loop and manual supervision,which may miss detection and cost much manpower.Due to the rapidly developing deep learning sweeping the world in recent years,object detection methods relying on background segmentation cannot meet the requirements of complex and various scenes on speed and precision.Thus,an improved Single Shot MultiBox Detector(SSD)based on deep learning is proposed in our study,we introduce attention mechanism by spatial transformer module which gives neural networks the ability to actively spatially transform feature maps and add contextual information transmission in specified layer.Finally,we found out the best connection layer in the detection model by repeated experiments especially for small objects and increased the precision by 1.5%than the baseline SSD without extra training cost.Meanwhile,we designed an illegal parking vehicle detection method by the improved SSD,reaching a high precision up to 97.3%and achieving a speed of 40FPS,superior to most of vehicle detection methods,will make contributions to relieving the negative impact of illegal parking.

Bolzano Traffic: An Example of Open ITS Deployment for Advanced Traveller Information Services

This paper aims to present the experience gathered in the Italian alpine city of Bolzano within the project“Bolzano Traffic”whose goal is the introduction of an experimental open ITS platform for local service providers,fostering the diffusion of advanced traveller information services and the future deployment of cooperative mobility systems in the region.Several end-users applications targeted to the needs of different user groups have been developed in collaboration with local companies and research centers;a partnership with the EU Co-Cities project has been activated as well.The implemented services rely on real-time travel and traffic information collected by urban traffic monitoring systems or published by local stakeholders(e.g.public transportation operators).An active involvement of end-users,who have recently started testing these demo applications for free,is actually on-going.

High Resolution Radar Real-Time Signal and Information Processing

Radar is an electronic device that uses radio waves to determine the range, angle, or velocity of objects. Real-time signal and information processor is an important module for real-time positioning, imaging, detection and recognition of targets. With the development of ultra-wideband technology, synthetic aperture technology, signal and information processing technology, the radar coverage, detection accuracy and resolution have been greatly improved, especially in terms of one-dimensional(1D) high-resolution radar detection, tracking, recognition, and two-dimensional(2D) synthetic aperture radar imaging technology. Meanwhile, for the application of radar detection and remote sensing with high resolution and wide swath, the amount of data has been greatly increased. Therefore, the radar is required to have low-latency and real-time processing capability under the constraints of size, weight and power consumption. This paper systematically introduces the new technology of high resolution radar and real-time signal and information processing. The key problems and solutions are discussed, including the detection and tracking of 1D high-resolution radar, the accurate signal modeling and wide-swath imaging for geosynchronous orbit synthetic aperture radar, and real-time signal and information processing architecture and efficient algorithms. Finally, the latest research progress and representative results are presented, and the development trends are prospected.

Effects of real-time traffic information systems on traffic performance under different network structures

The effects of real-time traffic information system(RTTIS)on traffic performance under parallel,grid and ring networks were investigated.The simulation results show that the effects of the proportion of RTTIS usage depend on the road network structures.For traffic on a parallel network,the performance of groups with and without RTTIS level is improved when the proportion of vehicles using RTTIS is greater than 0 and less than 30%,and a proportion of RTTIS usage higher than 90%would actually deteriorate the performance.For both grid and ring networks,a higher proportion of RTTIS usage always improves the performance of groups with and without RTTIS.For all three network structures,vehicles without RTTIS benefit from some proportion of RTTIS usage in a system.

Research and application of real-time monitoring and early warning thresholds for multi-temporal agricultural products information

Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.

Modeling and Statistical Properties Research on Online Real-Time Information Transmission Network

In this paper, the model of the online real-time information transmission network, such as wechat, micro-blog, and QQ network, is proposed and built, based on the connection properties between users of the online real-time information transmission network, and combined with the local world evolving characteristics in complex network, then the statistical topological properties of the network is obtained by numerical simulation. Furthermore, we simulated the process of information transmission on the network, according to the actual characteristics of the online real-time information transmission. Statistics show that the degree distribution presents the characteristics of scale free network, presenting power law distribution, while the average path length, the average clustering coefficient and the average size of the network also has a power-law relationship, moreover, the model parameters has no effect on power-law exponent. The spread of information on the network represents obvious fluctuation scaling, reflecting the characteristics that information transmission fluctuates over time.

Impact of the Real-time Bus Information on Bus Riders, an Evidence from Guangzhou

This paper evaluates impacts of the real-time information from the smartphone APP and the real-time information board at bus stops on bus users with survey data. Through the analysis of data with t-test and linear regression, it is found that the waiting time of bus riders with real-time information from the smartphone APP is much less than that of bus riders without the real-time information. As to the perceived waiting time of bus users, through the linear regression, the study finds that without the real-time information, bus riders’ perceived waiting time is greater than waiting time. At the same time, the perceived waiting time of bus users with real-time information is only slightly larger than their waiting time. Through regressing anxiety on real-time information, perceived waiting time and so on, it is found that real-time information reduces anxiety remarkably.

GE Fanuc—Proficy^TM Real-Time Information Portal 2．1版

GE Fanuc自动化美洲公司推出了全新的Proficy^TM Real-Time Information Portal 2．1版，能为企业提供全厂范围分析、可视化和报告，从而使用户能实时地从工厂数据中得到商务信息。

DuFNet:Dual Flow Network of Real-Time Semantic Segmentation for Unmanned Driving Application of Internet of Things

The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence technology.Image semantic segmentation can help the unmanned driving system by achieving road accessibility analysis.Semantic segmentation is also a challenging technology for image understanding and scene parsing.We focused on the challenging task of real-time semantic segmentation in this paper.In this paper,we proposed a novel fast architecture for real-time semantic segmentation named DuFNet.Starting from the existing work of Bilateral Segmentation Network(BiSeNet),DuFNet proposes a novel Semantic Information Flow(SIF)structure for context information and a novel Fringe Information Flow(FIF)structure for spatial information.We also proposed two kinds of SIF with cascaded and paralleled structures,respectively.The SIF encodes the input stage by stage in the ResNet18 backbone and provides context information for the feature fusionmodule.Features from previous stages usually contain rich low-level details but high-level semantics for later stages.Themultiple convolutions embed in Parallel SIF aggregate the corresponding features among different stages and generate a powerful global context representation with less computational cost.The FIF consists of a pooling layer and an upsampling operator followed by projection convolution layer.The concise component provides more spatial details for the network.Compared with BiSeNet,our work achieved faster speed and comparable performance with 72.34%mIoU accuracy and 78 FPS on Cityscapes Dataset based on the ResNet18 backbone.

Asymmetric Consortium Blockchain and Homomorphically Polynomial-Based PIR for Secured Smart Parking Systems

In crowded cities,searching for the availability of parking lots is a herculean task as it results in the wastage of drivers’time,increases air pollution,and traffic congestion.Smart parking systems facilitate the drivers to determine the information about the parking lot in real time and book them depending on the requirement.But the existing smart parking systems necessitate the drivers to reveal their sensitive information that includes their mobile number,personal identity,and desired destination.This disclosure of sensitive information makes the existing centralized smart parking systems more vulnerable to service providers’security breaches,single points of failure,and bottlenecks.In this paper,an Improved Asymmetric Consortium Blockchain and Homomorphically Computing Univariate Polynomial-based private information retrieval(IACB-HCUPPIR)scheme is proposed to ensure parking lots’availability with transparency security in a privacy-preserving smart parking system.In specific,an improved Asymmetric Consortium Blockchain is used for achieving secure transactions between different parties interacting in the smart parking environment.It further adopted the method of Homomorphically Computing Univariate Polynomial-based private information retrieval(HCUPPIR)scheme for preserving the location privacy of drivers.The results of IACB-HCUPPIR confirmed better results in terms of minimized computation and communication overload with throughput,latency,and response time with maximized drivers’privacy preservation.Moreover,the proposed fully homomorphic algorithm(FHE)was compared against partial-homomorphic encryption(PHE)and technique without encryption and found that the proposed model has quick communication in allocating the parking slots starting with 24.3 s,whereas PHE starts allocating from 24.7 s and the technique without encryption starts at 27.4 s.Thus,we ensure the proposed model performs well in allocating parking slots with less time and high security with privacy preservation.

Library's industrial technology information service in science parks—Taking NSL's practice as an example

Purpose:The purpose of this paper is to explore how libraries can develop service and product strategies and the service support mechanism to provide industrial technology information service in science parks.Design/methodology/approach:The analysis is based on a case study of a large Chinese research library,National Science Library(NSL),the Chinese Academy of Sciences(CAS),in serving high-tech companies in Zhongguancun Science Park(Z-Park).Findings:NSL’s practices suggested that in serving business clients,libraries’ product and service strategies should be based on the understanding of users’ needs.Aside from those services that have been recognized by clients such as document retrieval & delivery and novelty search,libraries may expand their service and provide in-depth information analysis and consultation for some key clients.Moreover,a service and product development system should be established,which differentiates the libraries’ products and services from those of their competitors.In providing industrial technology information service,libraries need to construct the service support mechanism,publicize their service and learn to cooperate with clients to meet their demands for knowledge management and innovation.Research limitations:The generalizability of the findings is limited because they are based on an individual case study.Practical implications:Our service practices provide useful information for other libraries to expand their information service to high-tech companies in the new information environment.Originality/value:Z-Park is the first and one of the largest science and technology parks in China.Hence NSL’s practices in serving high-tech companies in Z-Park can be valuable to other libraries that intend to take up the similar service.

Modeling commuters' route choice behavior under pre-trip information system

Research about the auto commuter＇s pre-trip route choice behavior ignores the combined influence of the real-time information and all respondents＇ historical information in the existing documents.To overcome this shortcoming,an approach to describing the pre-trip route choice behavior with the incorporation of the real-time and historical information is proposed.Two types of real-time information are investigated,which are quantitative information and prescriptive information.By using the bounded rationality theory,the influence of historical information on the real-time information reference process is examined first.Estimation results show that the historical information has a significant influence on the quantitative information reference process,but not on the prescriptive information reference process.Then the route choice behavior is modeled.A comparison is also made among three route choice models,one of which does not incorporate the real-time information reference process,while the others do.Estimation results show that the route choice behavior is better described with the consideration of the reference process of both quantitative and prescriptive information.

Data network traffic analysis and optimization strategy of real-time power grid dynamic monitoring system for wide-frequency measurements

The application and development of a wide-area measurement system(WAMS)has enabled many applications and led to several requirements based on dynamic measurement data.Such data are transmitted as big data information flow.To ensure effective transmission of wide-frequency electrical information by the communication protocol of a WAMS,this study performs real-time traffic monitoring and analysis of the data network of a power information system,and establishes corresponding network optimization strategies to solve existing transmission problems.This study utilizes the traffic analysis results obtained using the current real-time dynamic monitoring system to design an optimization strategy,covering the optimization in three progressive levels:the underlying communication protocol,source data,and transmission process.Optimization of the system structure and scheduling optimization of data information are validated to be feasible and practical via tests.

A Text Categorization System with Soft Real-Time Guarantee

In order to provide predictable runtime performante for text categorization （TC） systems, an innovative system design method is proposed for soft real time TC systems. An analyzable mathematical model is established to approximately describe the nonlinear and time-varying TC systems. According to this mathematical model, the feedback control theory is adopted to prove the system＇s stableness and zero steady state error. The experiments result shows that the error of deadline satisfied ratio in the system is kept within 4 of the desired value. And the number of classifiers can be dynamically adjusted by the system itself to save the computa tion resources. The proposed methodology enables the theo retical analysis and evaluation to the TC systems, leading to a high-quality and low cost implementation approach.

Estimation of the Impact of Traveler Information Apps on Urban Air Quality Improvement

With the rapid growth of vehicle population and vehicle miles traveled, automobile emission has become a severe issue in the metropolitan cities of China. There are policies that concentrate on the management of emission sources. However, improving the operation of the transportation system through apps on mobile devices, especially navigation apps, may have a unique role in promoting urban air quality. Real-time traveler information can not only help travelers avoid traffic congestion, hut also advise them to adjust their departure time, mode, or route, or even to cancel trips. Will such changes in personal travel patterns have a significant impact in decreasing emissions？ If so, to what extent will they impact urban air quality？ The aim of this study is to determine how urban traffic emission is affected by the use of navigation apps. With this work, we attempt to answer the question of whether the real-time traffic information provided by navigation apps can help to improve urban air quality. Some of these findings may provide references for the formulation of urban traffic and environmental policies.

We’ve Got the Power: A Framework for Real-Time Network Power Monitoring

The energy consumption of the information and communication technology sector has become a significant portion of the total global energy consumption, warranting research efforts to attempt to reduce it. The pre-requisite for effectual energy management is the availability of the current power consumption values from network devices. Previous works have attempted to estimate and model the consumption values or have measured it using intrusive approaches such as using an in-line power meter. Recent trends suggest that information models are being increasingly used in all aspects of network management. This paper presents a framework developed for enabling the collection of real-time power consumption information from the next generation of networking hardware non-intrusively by employing information models. The experiment results indicate that it is feasible to gather power consumption data using standardized IETF information models, or non-standard customized information models, or through abstracting and exposing the information in a uniform format when no support for the required information models exists. Functional validation of the proposed framework is performed and the results from this research could be leveraged to make energy-efficient network management decisions.

Research on Network Platform of Information Management and Security

With the rapid development and wide application of network technology, information security issues are increasingly highlighted, received more and more attention. This article introduces the present situation of network information security, discusses the connotation of network information security, and analyzes the main threat to the security of the network information. And we separately detailed description of the data monitoring platform architecture from the data layer, network layer and presentation layer three levels, focuses on the functional structure of intelligent database platform, and puts forward to measures that ensure the safety of the platform and the internal data security. Through the design of the platform to improve the information security system has certain significance.

基于地理信息技术的山地城市社区体育文化公园空间分布分析——以重庆市为例

社区体育文化公园作为居民身心健康发展的重要场域,研究其空间分布及影响因素具有重要意义。文章以具有典型山地城市特征的重庆市为例,运用核密度估算法、最小阻抗法、空间插值法和地理探测器对重庆92个社区体育文化公园进行深入分析。研究发现:重庆市社区体育文化公园主要分布在渝中、渝北、南岸、巴南西部临江一带,总体分布与城市发展具有耦合性,其空间分布主要受交通可达性、房价、人口密度和地势等因素影响,其中交通可达性和房价影响较大,人口密度和地势次之。文章提出以区域发展水平为着力点,建设多层级社区体育文化公园;秉持“以人为本”的核心理念,建设“亲民”社区体育文化公园;以山地城市独有的城市形态,丰富社区体育文化公园内部空间结构等优化配置建议,为社区体育文化公园的规划提供重要参考。

基于改进潜能模型的南康家具物流园区空间可达性分析

潜能模型作为测度空间可达性的重要模型,广泛应用于医疗教育、公园绿地等公共设施可达性分析中。以家具物流园为切入点,在物流园区占地面积影响因素的基础上加入物流企业数量因子,构建改进潜能模型测度其空间可达性。同时结合地理信息系统(GIS)插值方法进行可达性等级划分,并在出行时间测算中引入货车限行影响因子。以南康区为例进行家具物流园空间可达性验证分析。结果表明:南康家具物流园区潜能分布较为平衡,中部物流商贸城和红土地物流园作为成熟的物流园其潜能值最大,物流园区空间可达性分布差异不明显,大致呈现出中东部高、周边低的分布格局。