A system design for surveillance systems protecting critical infrastructures

Critical infrastructures are attractive targets for attacks by intruders with different hostile aims. Modern information and sensor technology provides abilities to detect such attacks. The objective of this work is to outline a system design for surveillance systems aimed at protection of critical infrastructures, with the focus on early threat detection at the perimeter of critical infrastructures. The outline of the system design is based on an assessment of stakeholder needs. The needs were identified from interviews with domain experts and system operators. The system design of the surveillance system and the user requirements in terms of capabilities were then determined. The result consists of the system design for surveillance systems, comprising the systems capabilities, the systems structure, and the systems process. The outcome of the work will have an impact on the implementation of the surveillance systems with respect to the sensors utilized, the sensor data algorithms and the fusion techniques.     

A Dempster-Shafer theory and uninorm-based framework of reasoning and multiattribute decision-making for surveillance system

Closed-circuit television and sensor-based intelligent surveillance systems have attracted considerable attentions in the field of public security affairs. To provide real-time reaction in the case of a huge volume of the surveillance data, researchers have proposed event-reasoning frameworks for modeling and inferring events of interest. However, they do not support decision-making, which is very important for surveillance operators. To this end, this paper incorporate a function of decision-making in an event-reasoning framework, so that our model not only can perform event-reasoning but also can predict, rank, and alarm threats according to uncertain information from multiple heterogeneous sources. In particular, we propose a multiattribute decision-making model, in which an object being watched is modeled as a multiattribute event, where each attribute corresponds to a specific source, and the information from each source can be used to elicit a local threat degree of different malicious situations with respect to the corresponding attribute. Moreover, to assess an overall threat degree of an object being observed, we also propose a method to fuse the conflict threat degrees regarding all the relevant attributes. Finally, we demonstrate the effectiveness of our framework by an airport security surveillance scenario.     

机载系统安保风险评估方法

针对影响民用飞机机载系统安全的信息安保威胁问题,通过研究ISO27005和航空工业标准,提出了一种适用于机载系统的安保风险评估方法。该方法基于威胁条件和威胁场景进行系统脆弱性分析,并结合传统的飞机安全性分析方法与安保风险评估方法,提出一套可量化的风险值计算方法。通过关系矩阵在安全性与安保等级间建立了相关性,为系统需求和架构设计提供了依据。实例验证结果表明,该方法能提供正确与可信的机载系统安保风险评估数据。     

散货物流信息集成

通过对系统的层次结构、逻辑结构和物理结构的分析和设计，构建港口散货物流综合信息集成平台．采用数据挖掘、分布式数据库和信息集成等技术，实现散货物流供应链上的资源共享、信息透明和决策支持．系统的应用可改善港口散货物流的作业组织，加速车船周转，提高港口通过能力和经营效益，有效地减少压船压港现象.     

基于开源工具集的大数据网络安全态势感知及预警架构

对信息系统安全防护而言,大数据是一把双刃剑。信息量的巨增使得数据价值密度更小,给APT等攻击行为提供了更好的藏身环境;但大数据处理技术对海量数据的聚合、挖掘和分析又使得准确检测及预测攻击威胁成为可能。为增强信息系统的威胁感知与攻击预警能力,构建大数据威胁处理平台势在必行。基于最新的开源大数据组件集,构建了集数据收集整理、数据存储、离线分析发现、实时关联检测、威胁预警和态势呈现等功能于一体的、支持全流程安全事件处理过程的、完整的网络安全态势感知及预警架构,与现有同类平台架构相比,其具有高可用、可扩展、易部署等特点,且能较好地支持威胁情报的引入。     

面向世博的危险源监测应急系统的设计与实现

有效的危险源监测与突发事件应急系统是世博会安全保障体系的重要组成部分。该文介绍以上海市减灾综合信息系统为基础平台,架构面向世博的危险源监测应急系统的一般方法,从危险源的监测、数据的卫星传输、现场信息的分析预判与预案启动等方面对系统进行深入分析。该系统可以实时监测世博场馆及周边地区危险源,具有多源信息获取和快速应急反应能力,能预防城市重大危险源灾害并降低其可能造成的损失,推动其他部门利用这些信息提升各自的应急管理水平。     

Cooperative management of a net of intelligent surveillance agent sensors

The use of distributed artificial intelligence (DAI) techniques, particularly the multiagent systems theory, in a decentralized architecture, is proposed to manage cooperatively, all sensor tasks in a network of (air) surveillance radars with capabilities for autonomous operation. At the multisensor data fusion (DF) center, the fusion agent will periodically deliver to sensor agents a list with the system‐level tasks that need to be fulfilled. For each system task, indications about its system‐level priority are included (inferred global necessity of fulfilling the task) as well as the performance objectives that are required, expressed in different terms depending on the type of task (sector surveillance, target tracking, target identification, etc.). Periodically, the local manager at each sensor (the sensor agent) will decide on the list of sensor‐level tasks to be executed by its sensor, providing also the sensor‐level priority and performance objectives for each task. The problem of sensor(s)‐to‐task(s) assignment (including decomposition of system‐level tasks into sensor‐level tasks and translation of system‐level performance requirements to sensor‐level performance objectives) is the result of a negotiation process performed among sensor agents, initiated with the information sent to them by the fusion agent. With types of agents, a symbolic bottom‐up fuzzy reasoning process is performed that considers the available fused or local target tracks, surveillance sectors data, and (external) intelligence information. As a result of these reasoning processes, performed at each agent planning level, the priorities of system‐level and sensor‐level tasks will be inferred and applied during the negation process. © 2003 Wiley Periodicals, Inc.     

Intelligent video surveillance system: 3-tier context-aware surveillance system with metadata

This paper presents an intelligent video surveillance system with the metadata rule for the exchange of analyzed information. We define the metadata rule for the exchange of analyzed information between intelligent video surveillance systems that automatically analyzes video data acquired from cameras. The metadata rule is to effectively index very large video surveillance databases and to unify searches and management between distributed or heterogeneous surveillance systems more efficiently. The system consists of low-level context-aware, high-level context-aware and intelligent services to generate metadata for the surveillance systems. Various contexts are acquired from physical sensors in monitoring areas for the low-level context-aware system. The situation is recognized in the high-level context-aware system by analyzing the context data collected in the low-level system. The system provides intelligent services to track moving objects in Fields Of View (FOVs) and to recognize human activities. Furthermore, the system supports real-time moving objects tracking with Panning, Tilting and Zooming (PTZ) cameras in overlapping and non-overlapping FOVs.     

基于局部对比度和全卷积网络的小空间碎片检测

近年来环绕地球轨道的空间碎片数量急剧增加，对在轨运行的航天器构成严重威胁。基于天基监视平台的空间碎片小目标快速检测对于航天器远距离规避具有重要意义，然而由于空间碎片小目标的快速相对运动和宇宙射线产生的噪声，空间碎片小目标快速检测极具挑战。提出了一种基于深度卷积神经网络的天基空间碎片小目标显著性检测方法，首先，使用局部对比度方法获得输入图像的空间对比度图；然后，通过全卷积网络结合上述对比度图捕获时空显著性信息；最后，基于仿真视频序列图像开展实验验证，可实现对最远距离为30km，最小为16像素的目标准确检测。通过设置不同的高斯白噪声方差参数模拟空间环境噪声，证明了在噪声背景条件下对空间碎片小目标检测的有效性和鲁棒性。     

IBM smart surveillance system (S3): event based video surveillance system with an open and extensible framework

The increasing need for sophisticated surveillance systems and the move to a digital infrastructure has transformed surveillance into a large scale data analysis and management challenge. Smart surveillance systems use automatic image understanding techniques to extract information from the surveillance data. While the majority of the research and commercial systems have focused on the information extraction aspect of the challenge, very few systems have explored the use of extracted information in the search, retrieval, data management and investigation context. The IBM smart surveillance system (S3) is one of the few advanced surveillance systems which provides not only the capability to automatically monitor a scene but also the capability to manage the surveillance data, perform event based retrieval, receive real time event alerts thru standard web infrastructure and extract long term statistical patterns of activity. The IBM S3 is easily customized to fit the requirements of different applications by using an open-standards based architecture for surveillance.     

一种改进的模糊粗糙集知识约简方法

针对模糊信息系统,通过分析R.Jensen所定义近似算子的松散性,构造了一种严格状态下的近似算子,该算子可以保证下近似随信息系统中属性个数的增加而单调递增;在此基础上,对模糊信息系统的相对约简概念进行了定义,应用所定义依赖度提出了一种模糊信息系统的启发式知识约简算法;将该方法应用于目标威胁等级评估信息系统的知识约简,计算结果验证了该方法的有效性。     

An intelligent agent-based collaborative information security framework

In this paper we proposed a framework for collaborative intelligent agents in a distributed environment to execute sound security strategies for protecting information resources. First, the intelligent agent-based Duty Reliable Center (DRC) in the model uses the group decision method to determine a global information threat level. With the threat level, local agent employs the Bayes’ decision procedure to calculate the expected loss of its all-possible actions, and then chooses an action among them with the minimum expected loss to protect its information resources. The proposed framework enables an agent to choose among alternatives in an optimal fashion, taking into account the worth of acquiring prior information to reduce uncertainty. Because system operations are distributed, hackers are unlikely to wreck the whole system. Thus, it is expected to yield information security cost-effective solutions.     

无人飞行器航迹方案的VIKOR择优评价

针对无人飞行器智能航迹规划算法导致的多航迹选择问题,构建基于多准则妥协解排序法(VIKOR)的航迹路线择优评价体系.为快速获得各威胁源的综合威胁信息,采用路线分割和极限的思想,建立综合威胁计算模型,并给出模型参数变化范围计算方法.以变异系数法确定指标权重,采用可最大化群体利益且弱化个体遗憾的VIKOR算法融合威胁信息,给出基于VIKOR算法的航迹方案择优评价方法和步骤.该评价方法可获得具有优先级别的妥协最优航迹方案,使评价结果更容易被决策者接受.实际航迹路线择优问题验证了所提出方法的有效性.     

一种不确定信息条件下的威胁估计方法

未来复杂战场环境下信息具有高度不确定性,对于不同类型的目标很难客观地估计其威胁等级。针对该问题,采用粒计算的有关理论建立了可实时更新的威胁估计信息系统,基于决策逻辑语言提取出极小化的规则集,它反应了信息系统所包含的专家经验知识。通过分析知识的不确定性,并给出其不确定性表示,提出了相应的知识推理策略,从而可以对复杂情况下的不同类型多目标进行有效的威胁估计。     

基于跨域协同的网络空间威胁预警模式

网络空间威胁发展呈现出主动性、隐蔽性、泛在性的特点,向传统被动式、局域性、孤立化的网络防御模式提出了严峻挑战。针对大数据、人工智能与网络安全融合的新趋势,提出一种跨域协同的威胁预警模式,为网络空间安全防护赋能增效。首先,该模式从网络空间结构出发,通过划分安全威胁域、解析系统功能、设计共享机制,构建具有合纵连横作用的功能框架;其次,为提升威胁信息检测能力,设计了分层司职的协同化技术体系,阐述了威胁信息感知、处理、应用等关键技术;最后,借助应用场景,定性化描述了所提预警模式的能力增量。     

Storm brewing over ‘echelon’

Storm clouds are gathering in advance of a European Union-commissioned study of the joint US-British top secret communications surveillance system commonly referred to as ‘Echelon’. On 14 September 1998, following a glowing picture of EU-US relations painted by EU Commissioner Martin Bangemann, the European Parliament adopted a resolution endorsing the New Transatlantic Agenda agreed to at the 18 May 1998 London Summit. However, in its resolution, the Parliament issued an important proviso. While recognizing that it was important for US-EU “cooperation in the field of electronic surveillance for tracking down international criminal terrorists and drug traffickers but takes the view that protective measures concerning economic information and effective encryption should be taken to guard against abuse and threat to civil liberties posed by international telecommunications such as the ‘Echelon’ US system.”     

基于网络的数字监控系统设计

数字监控系统已经取代传统模拟监控系统成为当今监控行业的主流,随着视频压缩及IP网络技术的发展,基于网络的数字监控系统也逐渐得到应用。网络数字监控系统是集传统CCTV监控、多媒体、计算机网络和通信等多领域技术于一体的监控系统换代产品,将在信息科技高速发展的今天,更高水平地服务于人们的日常生活领域。     

An integrated highly synchronous,high resolution,real time eye tracking system for dynamic flight movement

Electronic surveillance systems are being used rapidly today, ranging from a simple video camera to a complex biometric surveillance system for facial patterns and intelligent computer vision based surveillance systems, which are applied in many fields such as home monitoring, security surveillance of important places and mission critical tasks like air traffic control surveillance. Such systems normally involve a computer system and a human surveillance operator, who looks at the dynamic display to perform his surveillance tasks. Exploitation of shared information between these physical heterogeneous data capture systems with human operated functions is one emerging aspect in electronic surveillance that has yet to be addressed deeply. Hence, an innovative interaction interface for such knowledge extraction and representation is required. Such an interface should establish a data activity register frame which captures information depicting various surveillance activities at a specified spatial and time reference.This paper presents a real time eye tracking system, which integrates two sets of activity data in a highly dynamic changing and synchronous manner in real-time with respect to both spatial and time frames, through the “Dynamic Data Alignment and Timestamp Synchronisation Model”. This model matches the timestamps of the two data streams, aligns them to the same spatial reference frame before fusing them together into a data activity register frame. The Air Traffic Control (ATC) domain is used to illustrate this model, where experiments are conducted under simulated radar traffic situations with participants and their radar input data. Test results revealed that this model is able to synchronise the timestamp of the eye and dynamic display data, align both of these data spatially, while taking into account dynamic changes in space and time on a simulated radar display. This system can also distinguish and show variations in the monitoring behaviour of participants. As such, new knowledge can be extracted and represented through this innovative interface, which can then be applied to other applications in the field of electronic surveillance to unearth monitoring behaviour of the human surveillance operator.     

针对自校准地面的学习监控跟踪模型

提出了一种新的多摄像机视觉监控系统的信息融合方法.信息融合在两个阶段进行.首先,根据相互独立的Cartesian参考坐标系统(设置在地平面上),对各个摄像机进行标定.然后,把所有的坐标系变换到一个坐标系统中.在视觉监控应用中,因为摄像机自定标和视觉数据配准技术将使监控设施安置变得更加容易,从而可以为公共场合发展更加适用的视觉监控工具.在解决监控数据的不完整性和不确定性方面,机器学习方法具有很好的效果.