The protection of smartphones, tablets, laptops, and the networks that they are connected to, from threats and vulnerabilities associated with wireless computing is known as mobile security.

E-commerce uses an electronic network to conduct buying and selling of goods and services for an organization or an individual.

The digital era has transformed the way organizations function, disrupting a significant number of business models, processes, technologies, and jobs. As digital data is exploding at a very rapid rate, companies are increasingly pressurized to focus on extracting value from data and implement strategies to make better business decisions. Engineering analytics technology is likely to play a significant role in transforming legacy industrial processes and automated industrial processes. Industries such as manufacturing, healthcare, automotive, transportation, energy, and utilities are some of the industries to embrace the changes. The inevitable need to do everything to reduce costs, increase productivity, enhance efficiency, and grow with the industrial evolution has stimulated the uptake of engineering analytics products and solutions. Deriving actionable intelligence from raw data collected from various internal and external sources is increasingly becoming a strategic priority in industry leadership teams. Engineering analytics solutions help enable this strategy. Engineering analytics services aid in the planning and deployment phases of adopting engineering analytics solutions. Sensor data thus is increasingly gaining huge focus and Technavio expects a high level of investment in this space. Engineering analytics services are predominantly addressable by IT service providers and are associated with the deployment of engineering analytics products. Industrial companies are investing heavily in engineering analytics services for their consulting, system integration, and custom development needs. Technavio expects increased spending on engineering analytics services from OEMs of industrial, energy and utility, and other industries (including transportation, aerospace, and healthcare).

Business analytics software uses tools and applications for collecting, managing, and analyzing both structured and unstructured data to improve business processes, achieve corporate goals, and enable better decision making. It includes EPM and analytical applications, business intelligence (BI) tools, and data warehouse platform software.

In organizations, BI solutions can analyze data from various channels or business activities and use them to improve business efficiency. Social media and social CRM generate an immense volume of data for organizations, and BI helps to compile and interpret this data to produce insights that can be used by the company’s marketing professionals and strategists. BI solutions, when integrated with analytics, are capable of handling a large amount of unstructured data to help identify and analyze business patterns. In most cases, BI collects data from data warehouses and uses technology, processes, and applications to analyze those data to help in decision support systems. Recent years have seen the evolution of self-service BI, which acts as a comprehensive and enterprise-wide platform for organizations. Self-service BI can be accessed by any user, not just IT professionals, and has a user-friendly interface that allows anyone to look up information and create reports.

Managed security services include services that are outsourced to third-party service providers to maintain information security and network security. MSSPs offer managed anti-virus; security monitoring; network boundary protection that includes managed services for firewalls, IDS, and VPN; content filtering; information security risk assessments; incident management that includes vulnerability assessment and penetration testing; emergency response and forensic analysis; and data archiving and restoration services. In addition, some MSSPs offer periodic vulnerability testing，patching, and escalation services. MSSPs can handle managed security services completely from an off-site location or may set up the necessary infrastructure on-site in the organization, leaving the security to be managed by the organization.

为解决现有约束处理方法可行解的适应度函数不包含约束条件的问题,提出了一种内部罚函数候选解筛选规则.该候选解筛选规则分别对可行解和不可行解采用内部罚函数和约束违反度进行筛选,从而达到平衡最小化目标函数和满足约束条件的目的.以进化策略算法为基础,给出了基于内部罚函数候选解筛选规则的进化算法的一个实现.进一步地,从理论和实验角度分别验证了内部罚函数候选解筛选规则的有效性:以(1+1)进化算法为例,从进化成功率方面验证了内部罚函数候选解筛选规则的理论有效性;通过13个测试问题的数值实验,从进化成功率、候选解后代是可行解的比例、进化步长和收敛速度方面验证了内部罚函数候选解筛选规则的实验有效性.

提出了一种三维六度环面Cayley图网络模型.针对该网络模型,给出了一种简单的三维节点编址方案,并利用该编址方案得到了任意两个节点间的最短距离公式;开发了一种简单的分布式最优路由算法,该算法可以运行于网络中的任意节点,可以建立任意两点之间的最短路由路径;基于陪集图(coset graph)理论,给出了一种新型的广播通信算法,并对该算法的效率进行了分析;给出了三维六度环绕网络模型直径的界限值.

传统的网络威胁态势评估方法主要是基于原始的警报信息,未结合目标网络的环境信息,使得方法的准确性受到很大的影响.提出了一种基于环境属性的网络威胁态势量化评估方法,该方法首先根据目标网络的环境属性对警报进行验证,判定引发警报的安全事件发生的可能性;然后,基于安全事件的风险级别及所针对的资产价值,分析安全事件发生后造成的损失;最后,基于安全事件发生的可能性及造成的损失量化评估网络的威胁态势.实例分析结果表明,该方法可以准确地量化评估网络的威胁态势. 

近年来,基于本体的智能信息检索系统已成为智能信息检索系统领域最为活跃的研究方向之一.如何利用本体进一步提高其检索性能和智能性,成为基于本体的智能信息检索系统的主要研究目标.从面向过程的角度,对近几年基于本体的智能信息检索系统的研究进展进行了综述,对其框架、所需本体知识的获取和使用、关键技术、性能评测等进行了前沿概括、比较和分析.最后,对基于本体的智能信息检索系统有待深入研究的难点和热点进行了展望.

Most communication in the modern era takes place over some type of cyber network, to include telecommunications, banking, public utilities, and health systems. Information gained from illegitimate network access can be used to create catastrophic effects at the individual, corporate, national, and even international levels, making cyber security a top priority. Cyber networks frequently encounter amounts of network traffic too large to process real-time threat detection efficiently. Reducing the amount of information necessary for a network monitor to determine the presence of a threat would likely aide in keeping networks more secure. This thesis uses network traffic data captured during the Department of Defense Cyber Defense Exercise to determine which features of network traffic are salient to detecting and classifying threats. After generating a set of 248 features from the capture data, feed-forward artificial neural networks were generated and signal-to-noise ratios were used to prune the feature set to 18 features while still achieving an accuracy ranging from 83% - 94%. The salient features primarily come from the transport layer section of the network traffic data and involve the client/server connection parameters, size of the initial data sent, and number of segments and/or bytes sent in the flow.

This chapter presents the concept of development and management of SOA applications within the configurable service platform which supports all phases starting from business process definition. The unique features of the platform include: business process compatibility, easy reconfiguration of composition schemes, visual support for requirements and service definition, QoS assessment (including communication services) and service execution control. Moreover, it illustrates how effective tools for SOA management may be developed within the SOA paradigm itself, and how this paradigm may be used to achieve their interoperability and flexibility.

With the advent of the Internet and Internet-connected devices, modern applications can experience very rapid growth of users from all parts of the world. A growing user base leads to greater usage and large data sizes, so scalable database systems capable of handling the great demands are critical for applications. With the emergence of cloud computing, a major movement in the industry, modern applications depend on distributed data stores for their scalable data management solutions. Many large-scale applications utilize NoSQL systems, such as distributed key-value stores, for their scalability and availability properties over traditional relational database systems.

NORC at the University of Chicago is pleased to submit this final report for Assessing the Status and Prospects of State and Local Health Department Information Technology Infrastructure, a project of the Assistant Secretary for Planning and Evaluation (ASPE) at the United States Department of Health and Human Services. NORC and ASPE worked in close partnership with the National Association of County and City Health Officials (NACCHO) and the Association of State and Territorial Health Officials (ASTHO). This report describes how state health agencies (SHAs) and local health departments (LHDs) use information technology systems to capture, manage, analyze, and report information. We assess trends in use of information technology (IT) among SHAs and LHDs following the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, the Patient Protection and Affordable Care Act (ACA) of 2010, recent work in public health informatics, and other factors. This project assumes that IT tools and resources should play a role in governmental public health practice. However, we also assume that rigorous assessments of public health goals should motivate IT projects and that stakeholders should design and implement IT in direct service of those goals.