提高静态缺陷检测精度方法

误报率和漏报率是静态缺陷检测的关键技术指标,提高分析精度是降低误报和漏报的主要手段.文中介绍了缺陷模式及其有限状态机描述,提出基于传统数据流分析的缺陷检测方法.采用变量抽象取值来近似地表示程序动态执行信息,通过状态条件中的变量抽象取值范围为空来判断不可达路径,以实现路径敏感分析;使用缺陷相关的函数摘要来表示缺陷检测所需函数调用信息,其中缺陷相关的函数摘要包括前置约束信息、后置约束信息和函数特征信息三部分,实现了上下文敏感的跨函数分析.文中方法已在缺陷检测系统DTS中实现,在大型开源软件分析中的实验结果表明,该方法能减少误报和漏报.     

基于协议分析的入侵检测技术研究

提出基于协议分析和命令解析的模式匹配入侵检测方法，根据各种协议的结构特点准确捕获入侵特征。实际测试表明，该方法大大提高了入侵检测系统性能，降低了漏报率和误报率。     

基于静态检测工具的源代码安全缺陷检测研究*

针对已有的使用单个静态检测工具进行源代码安全缺陷检测存在的漏报率和误报率很高的问题,提出了一种基于多种静态检测工具的检测方法。该方法通过对多种工具的检测结果进行统计分析,有效地降低了漏报率和误报率。设计和实现了一个可扩展的源代码静态分析工具平台,并通过实验表明,相对于单个工具的检测结果而言,该平台明显降低了漏报率和误报率。     

网页内容链接层次语义树的恶意网页检测方法

针对攻击者利用URL缩短服务导致仅依赖于URL特征的恶意网页检测失效的问题,及恶意网页检测中恶意与良性网页高度不均衡的问题,提出一种融合网页内容层次语义树特征的成本敏感学习的恶意网页检测方法。该方法通过构建网页内容链接层次语义树,提取基于语义树的特征,解决了URL缩短服务导致特征失效的问题;并通过构建成本敏感学习的检测模型,解决了数据类别不均衡的问题。实验结果表明,与现有的方法相比,提出的方法不仅能应对缩短服务的问题,还能在类别不均衡的恶意网页检测任务中表现出较低的漏报率2.1%和误报率3.3%。此外,在25万条无标签数据集上,该方法比反病毒工具VirusTotal的查全率提升了38.2%。     

基于数据融合的源代码静态分析漏洞检测技术

针对目前现有静态分析方法存在的漏报率和误报率较高的问题,提出一种基于数据融合的源代码静态分析漏洞检测技术.该技术通过对不同检测方法的分析结果进行解析和数据融合,有效地降低误报率和漏报率.设计与实现了一个可扩展的源代码静态分析工具原型,可通过用户的反馈信息自动寻优.实验结果表明:相对于单个漏洞检测方法而言,该方法的误报率和漏报率明显降低.     

基于邻域粗糙集的入侵检测

针对入侵检测系统存在的高漏报率和误报率,提出了一种基于邻域粗糙集的入侵检测方法.该方法在粗糙集理论的基础上引入邻域概念,这样便无需对数据进行离散化处理,可以减少信息损失.实验结果表明:该方法可选择出更为重要的属性组合,从而获得较高的检测率和较低的漏报率与误报率.     

传统NIDS漏报和误报起因及改进技术

传统的网络入侵检测系统大都采用模式匹配的方法进行入侵检测,有着非常高的漏报率和误报率。本文通过对模式匹配算法检测过程的描述,对其产生漏报和误报的原因进行了分析。针对模式匹配算法带来的高漏报率和误报率,引入了协议分析的方法。协议分析方法通过辨别数据包的协议类型,然后使用相应的数据分析程序进行检测。这种方法可以大幅度地降低漏报率和误报率,大大地提高了入侵检测系统的效率。     

基于Multi-stream Combined隐马尔柯夫模型源端检测DDoS攻击

提出了一种新颖的综合考虑多维观测特征的DDoS攻击源端检测方法。该方法引入S-D-P特征概念，并抽取TCP/IP包头中的标志位和ID字段构成多维观测特征，采用Multi-stream Combined隐马尔可夫模型（MC-HMM）在源端网络检测DDoS攻击。大量实验表明,MC-HMM方法克服了基于一维观测特征的检测算法信息量过小的固有缺陷，能够有效降低检测的误报率和漏报率，提高DDoS攻击源端检测精度。     

基于免疫的入侵检测系统可信问题研究

为了降低入侵检测系统的误报率和漏报率,提出了一种基于人工免疫的新型入侵检测系统模型。借鉴生物免疫系统抗体的演化机制,该模型改进了目前基于免疫的入侵检测系统中抗原、抗体的静态描述方式,给出了抗原、抗体的动态描述方式和变化机制,并针对传统固定r连续位匹配方法的不足,提出了一种r可变匹配机制,最后进行了相关仿真实验。理论分析和实验结果表明,该系统具有较低的误报率和漏报率,提高了入侵检测系统的可信性。     

基于行为的分布式恶意代码检测技术

针对已有恶意代码检测技术存在不足,研究恶意代码网络传播行为,提取相应行为特征,在此基础上提出基于行为的分布式恶意代码检测技术,并进行NS-2仿真实验。实验结果表明该方法具有较低的误报率和漏报率,可有效检测恶意代码。     

类别不平衡的多任务人脸属性识别

属性的识别对物体的识别起到了比较重要的作用,例如人脸验证和场景识别。提高属性的识别率对后面基于属性特征的应用的正确率有很大的影响。近些年来,有些工作也开始关注于属性的学习,而很多的工作都是基于属性之间独立的假设,但在实际中很多的属性都是强相关的,例如没有胡子和女性,光头和头发的颜色;很多的工作忽略了类别之间的不平衡性,例如光头的样本比例可能只占样本的很小一部分。基于这2个观察,本文提出一种基于多任务的类别不平衡的人脸属性识别网络架构,该网络结构是由Densenet修改而来。该方法比以往的方法效果要好,一定程度上缓解了不平衡问题,且参数少,计算效率更高,在公开人脸属性数据集CelebA和LFWA上的实验验证了该方法的有效性。     

Integration | Innovation | Inclusion: Values,Variables and the Design of Human Environments

Complexity, complication, contradiction, consumption, confusion, delusion, depression. Opportunity, inspiration, ingenuity, compassion, wisdom. Our world is perplexing, our times are fast moving, and our choices are many. To find an appropriate path is a daunting yet vital challenge that confronts us as individuals, as communities, and as a civilization. How sustainable is our world? How reasonable are our behaviors? The present article is a collection of thoughts on a series of intertwined issues related to the contemporary world, its environmental dimensions, and their present-day problems. The goal is to survey the landscape through a lens of Environmental Design, to provide some perspectives, to raise some questions, and to explore systems, beliefs, and values informing and influencing actions. It is important to consider how people's belief systems influence, inform, and shape actions. This holds true in realms political, spiritual, and cultural. It also proves relevant in the ways in which we imagine, design, develop, and construct our buildings, cities, spaces, and places.

Appropriate solutions to some of our most daunting problems will arise through the concerted efforts, open dialogue, and collective wisdom of the wide array of stakeholders, professionals, politicians, decision makers, and citizens (both engaged and disenfranchised) who have the will and wherewithal to make a difference and to make the world safer, healthier, and better. It seems vital for us to critically examine, and question, our belief systems and their connections to the ways we define, refine, and realize progress. Architecture and Environmental Design, in both a philosophical and a practical sense, reflect as well as form greater aspirations, directions, and events of our times.     

区域网络中异构数据库存储复制技术

传统异构数据库存储复制技术只注重数据安全性,忽略了异构数据库存储复制的时效性与可靠性。为此,本文提出一种新的区域网络异构数据库存储复制技术。首先构建区域网络中异构数据库存储框架,通过定向随机游走方法对电力企业灾备中心异构数据进行存储,依据多叉索引树对异构数据库中的数据进行查询处理。然后采用一致性树分布备份技术对本地灾备中心数据进行备份,把待恢复数据分割成若干部分,通过若干差异远程备份服务器实现数据恢复。将所提技术应用于电力企业灾备中心,结果表明,所提技术有很高的存储、复制及备份恢复性能。     

基于改进PSO算法的加热系统分数阶控制

针对分数阶加热系统,提出一种基于改进粒子群优化算法的分数阶PIλDμ控制方法。首先,将细菌趋化行为机制引入带收缩因子的粒子群优化算法中,解决粒子群优化算法中由于只存在吸引操作没有排斥操作导致种群多样性失去的问题,从而避免PSO早熟收敛及陷入局部最优;然后使用改进PSO算法优化分数阶PIλDμ控制器的参数;最后,以加热系统为被控对象,分别采用改进粒子群优化算法、标准粒子群优化算法、遗传算法优化分数阶PIλDμ控制器的参数。仿真结果表明,使用该改进算法整定分数阶PIλDμ控制器参数,控制器能有效地抑制模型参数的摄动,系统鲁棒性更强。     

基于结构中心性的航路网络关键节点识别

针对航路网络关键节点识别问题,从航路网络结构中心性角度出发,构建完整航路网路结构和复杂拓扑模型,分别从度中心性、中介中心性和结构中心性这3个角度分析航路网络,并依托PAJEK可视化平台,对航路网络中介中心性和结构中心性进行仿真可视。在此基础上,借助AutoCAD,从中介性和紧密性角度对航路关键节点进行识别的可视化,从中得到对航路网络效能发挥具有重要支撑作用的航路点,仿真结果表明,提取的关键节点在实际航路网络运行中具有衔接枢纽、分配流量等重要作用,在路网重要节点识别研究中具有创新优势。     

支持高效撤销的属性加密方案

属性加密(Attribute-BasedEncryption,ABE)将密钥和密文与一系列属性相关联,被广泛应用于云计算的访问控制中。针对现有撤销方案效率低下的问题,提出一种更高效、细粒度的访问控制方案。方案中采用的访问结构可以表达任意涉及布尔运算符的访问策略;在加密过程中,构建一种属性用户组随机密钥分发方法,并结合ABE实现双重加密,将所有撤销操作转化成属性级别细粒度的撤销;新方案的数据始终以密文形式存在于服务器上,降低了对服务器的安全限制,可以将大部分密文重加密任务转移给云服务器执行,有效利用云服务器的计算能力,提升系统的运行效率,减少通信开销。     

An LMI approach to robust reduced-order H ∞ filter design for polytopic uncertain systems

This paper proposes a method for robust reduced-order H _∞ filter design for polytopic uncertain systems, using linear matrix inequalities (LMIs). Sufficient LMI conditions for both robust full- and reduced-order H _∞ filter design are derived. Convex optimization problems are formulated and solved to obtain optimal H _∞ filters by using the resulting LMI conditions. The resulting conditions do not involve any non-convex rank constraints, and thus the proposed method for H _∞ filter design guarantees global optimum solutions. Numerical examples are presented to show the effectiveness of the proposed method. Recommended by Editorial Board member Huanshui Zhang under the direction of Editor Young Il Lee. This work was supported by the Brain Korea 21 Project and the Basic Research Program of the Korea Science and Engineering Foundation under grant R01-2006-000-11373-0. Hyoun-Chul Choi received the B.S., M.S., and Ph.D. degrees in Control and Instrumentation Engineering from Ajou University, Suwon, Korea, in 1995, 1997, and 2006, respectively. He was a Visiting Researcher at Griffith University, Brisbane, Australia, from 2001 to 2002, and a Postdoctoral researcher at Ajou University, Suwon, Korea, from 2006 to 2007. Since 2008, he has been with ASRI, School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Korea, where he is currently a Postdoctoral Researcher. His research interests include LMI-based control, optimal and robust control, network-based control, and mechatronics. Dongkyoung Chwa received the B.S. and M.S. degrees from the Department of Control and Instrumentation Engineering in 1995 and 1997, respectively, and the Ph.D. degree from the School of Electrical and Computer Engineering in 2001, all from Seoul National University, Seoul, Korea. From 2001 to 2003, he was a Postdoctoral Researcher with Seoul National University. In 2003, he was a Visiting Research Fellow at The University of New South Wales, Australian Defence Force Academy, and was the Honorary Visiting Academic at the University of Melbourne, Melbourne, Australia. In 2004, he was a BK21 Assistant Professor with Seoul National University. Since 2005, he has been an Assistant Professor with the Department of Electrical and Computer Engineering, Ajou University, Suwon, Korea. His research interests are nonlinear, robust, and adaptive control theories and their applications to the robotics, underactuated systems including wheeled mobile robots, underactuated ships, cranes, and guidance and control of flight systems. Suk-Kyo Hong received the B.S., M.S., and Ph.D. degrees in Electrical Engineering from Seoul National University, Seoul, Korea, in 1971, 1973, and 1981, respectively. His major graduate research works were centered on speed control of induction motors. He was an Exchange Professor at Rensselaer Polytechnic Institute, Troy, NY, from 1982 to 1983, and at the Institut National de Recherche en Informatique et en Automatique, France, from 1988 to 1989. He has been with the faculty of the Department of Electrical and Computer Engineering, Ajou University, Suwon, Korea, since 1976, and was a Visiting Professor at Griffith University, Australia, in 2001 and 2002. His current research interests include robust robot control, microprocessor applications, factory automation, and computer integrated manufacturing.     

构建安全的局域网策略

网络安全是一门涉及计算机科学、网络技术、密码技术、信息安全技术、应用数学、教论、信论等多种学科的综合性学科,它涉及的因素主要包括物理安全、系统安全、信息安全和文化安全等范围。局域网络中人为的、非人为的,有意的、无意的;非法用户入侵、计算机病毒、黑客的不断侵袭等随时威胁局域网的安全。随着计算机网络技术迅速发展,网络安全问题也日渐突出。该文分析了威胁局域网安全的主要因素,探讨了从物理环境、网络层、应用层以及管理制度方面,运用VPN、NAT、VLAN、IDS、身份验证等技术构建安全局域网的策略。     

基于增量学习的非平衡SVM分类方法

针对传统支持向量机（SupportVectorMachine,SVM）无法有效处理非平衡分类的问题,提出一种基于增量学习的非平衡SVM分类方法（ImbalancedSVMBasedonIncrementalLearning,ISVM_IL）。该方法首先提取多数类样本中的部分样本,与少数类样本合并参与训练得到初始分类器,然后根据分类器与其他样本的关系,选择距离分类器最近的样本作为增量样本加入训练集参与训练,从而减小实际参与训练的负类数据规模,提高非平衡分类的性能。实验结果表明,本文提出的ISVM_IL方法可以有效提高非平衡分类中重要的少数类样本的分类性能。     

Design and analysis of the Dual-Torus Network

In this paper, we propose a new topology called theDual Torus Network (DTN) which is constructed by adding interleaved edges to a torus. The DTN has many advantages over meshes and tori such as better extendibility, smaller diameter, higher bisection width, and robust link connectivity. The most important property of the DTN is that it can be partitioned into sub-tori of different sizes. This is not possible for mesh and torus-based systems. The DTN is investigated with respect to allocation, embedding, and fault-tolerant embedding. It is shown that the sub-torus allocation problem in the DTN reduces to the sub-mesh allocation problem in the torus. With respect to embedding, it is shown that a topology that can be embedded into a mesh with dilation δ can also be embedded into the DTN with less dilation. In fault-tolerant embedding, a fault-tolerant embedding method based on rotation, column insertion, and column skip is proposed. This method can embed any rectangular grid into its optimal square DTN when the number of faulty nodes is fewer than the number of unused nodes. In conclusion, the DTN is a scalable topology well-suited for massively parallel computation. Sang-Ho Chae, M.S.: He received the B.S. in the Computer Science and Engineering from the Pohang University of Science and Technology (POSTECH) in 1994, and the M.E. in 1996. Since 1996, he works as an Associate Research Engineer in the Central R&D Center of the SK Telecom Co. Ltd. He took part in developing SK Telecom Short Message Server whose subscribers are now over 3.5 million and Advanced Paging System in which he designed and implemented high availability concepts. His research interests are the Fault Tolerance, Parallel Processing, and Parallel Topolgies. Jong Kim, Ph.D.: He received the B.S. degree in Electronic Engineering from Hanyang University, Seoul, Korea, in 1981, the M.S. degree in Computer Science from the Korea Advanced Institute of Science and Technology, Seoul, Korea, in 1983, and the Ph.D. degree in Computer Engineering from Pennsylvania State University, U.S.A., in 1991. He is currently an Associate Professor in the Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea. Prior to this appointment, he was a research fellow in the Real-Time Computing Laboratory of the Department of Electrical Engineering and Computer Science at the University of Michigan from 1991 to 1992. From 1983 to 1986, he was a System Engineer in the Korea Securities Computer Corporation, Seoul, Korea. His major areas of interest are Fault-Tolerant Computing, Performance Evaluation, and Parallel and Distributed Computing. Sung Je Hong, Ph.D.: He received the B.S. degree in Electronics Engineering from Seoul National University, Korea, in 1973, the M.S. degree in Computer Science from Iowa State University, Ames, U.S.A., in 1979, and the Ph.D. degree in Computer Science from the University of Illinois, Urbana, U.S.A., in 1983. He is currently a Professor in the Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea. From 1983 to 1989, he was a staff member of Corporate Research and Development, General Electric Company, Schenectady, NY, U.S.A. From 1975 to 1976, he was with Oriental Computer Engineering, Korea, as a Logic Design Engineer. His current research interest includes VLSI Design, CAD Algorithms, Testing, and Parallel Processing. Sunggu Lee, Ph.D.: He received the B.S.E.E. degree with highest distinction from the University of Kansas, Lawrence, in 1985 and the M.S.E. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 1987 and 1990, respectively. He is currently an Associate Professor in the Department of Electronic and Electrical Engineering at the Pohang University of Science and Technology (POSTECH), Pohang, Korea. Prior to this appointment, he was an Associate Professor in the Department of Electrical Engineering at the University of Delaware in Newark, Delaware, U.S.A. From June 1997 to July 1998, he spent one year as a Visiting Scientist at the IBM T. J. Watson Research Center. His research interests are in Parallel, Distributed, and Fault-Tolerant Computing. Currently, his main research focus is on the high-level and low-level aspects of Inter-Processor Communications for Parallel Computers.