在线学习的主用户仿冒攻击策略

在认知无线网络中,次用户通过频谱感知来学习频谱环境,从而接入那些没有被主用户占用的频谱空隙。事实上,多种恶意攻击的存在会影响次用户频谱感知的可靠性。只有深入研究恶意攻击策略,才能确保认知无线网络的安全。基于此,研究了一种认知无线网络中的欺骗性干扰策略,即主用户仿冒攻击策略,该攻击策略通过在信道上传输伪造的主用户信号来降低次用户频谱感知的性能。具体来说,将攻击策略问题建模为在线学习问题,并提出基于汤普森采样的攻击策略以实现在探索不确定信道和利用高性能信道间的权衡。仿真结果表明,与现有的攻击策略相比,提出的攻击策略能更好地通过在线学习优化攻击决策以适应非平稳的认知无线网络。     

云计算访问控制技术研究进展

云计算访问控制技术是近年来云计算安全领域研究的热点,其目标是有效保证云计算资源不被非法访问和使用。以访问控制理论为指导,针对云计算自身的特点,运用文献调研和比较研究法,从访问控制理论、学术界研究现状和工业界实践进展3个方面详细介绍了当前云计算访问控制技术的国内外发展现状。分析了云访问控制技术在虚拟化、分布式等方面的新特性,以及当前云访问控制方法在应用场景中存在的问题;对当前云计算访问控制模型设计、策略安全性分析、策略一致性分析等关键技术中的热点问题进行了研究,并展望了云访问控制发展趋势。     

基于灰色模糊的无线网络安全评估模型

无线网络的飞速发展使得网络安全的量化评估日益重要。结合网络安全属性和攻击属性两方面建立了无线网络安全评估指标体系,在此基础上,提出了基于灰色模糊的安全评估模型,并给出了量化评估的方法和步骤。最后通过实例进行了验证。     

一种基于组的访问控制方法

卫星通信网运控系统是一个大型的分布式系统,它使用CORBA中间件来解决分布式系统的异构问题。在研究DAC、MAC、RBAC等访问控制模型的基础上,提出并实现了一种基于组的用户访问控制(GBAC)策略,提高了运控系统的访问控制效率。     

信息价值的战场网络战攻击威胁评估方法

通过构建信息价值综合评估模型,对C4ISR网络信息价值程度进行定量评估.然后对战场网络战攻击行为进行分析,将其攻击威胁量化到信息价值评估模型,通过被攻击网络信息价值的变化来衡量网络战攻击的威胁程度,从而提供了一种网络战攻击威胁的评估方法.     

基于预授权的机密性和完整性动态统一模型

目前的访问控制模型无法对机密性、完整性和可用性做到合理的统一控制,尤其是对动态的、随机的访问请求控制不完善,使得攻击者总能找到脆弱点,也使得信息系统在实际应用中无法避免用户误操作引起的安全问题。提出了一种基于预授权的机密性和完整性访问控制模型,将BLP模型和Biba模型结合起来,通过引入预授权机制,对一些随机动态的访问活动进行合理控制。运用条件控制项,对主体执行任务的权限进行实时监控,动态地授予和取消主体执行任务的权限,实现系统机密性和完整性的统一,同时保证其具有较高的可用性,有利于信息的双向流动。给出了模型的应用实例,并对其安全性进行了证明。     

记录可寻址随机访问文件的设计与实现

记录可寻址随机访问文件是一种新型ＦＯＲＴＲＡＮ文件,它集中了顺序与直接文件两者的优点,为用户随机访问文件中不等长记录提供了更为有效的手段。本文不仅介绍了其使用方法,而且还讨论了实现中的有关问题。     

一种基于3阶段实现的高性能云存储计算

提出了一种基于动态数据复制策略和放置算法的3阶段云存储计算。在第1阶段,计算出一个文件的PD,然后根据得到的PD,从中找到最需要访问的文件和需要复制的文件;在第2阶段,计算出需要复制文件的RF,以确定文件是否应当复制或创建副本;在第3阶段,计算出这些节点的AF,以找到创建副本的数量并把副本放置在适当位置的特定节点,从而向用户提供相同服务的不同副本来增加数据可用性;实验结果表明,提出的云存储计算策略不仅能够有效找到需要复制的文件及创建和放置副本,而且在SBER和执行时间性能方面都优于目前比较先进的技术。     

一种安全私有云架构研究与设计

提出了一种安全私有云解决方案,是通过研究云计算安全体系模型,结合私有云架构特点设计的一种安全架构。与其他私有云解决方案相比,该架构安全系数较高,具有多层次、可扩展和强安全的特点。能够保证云用户安全快速登录云系统,使用透明加解密来保证用数据的可用性和安全性,实现了云数据的密文访问控制功能,增强了云存储数据的机密性,为私有云解决方案提供安全技术保障。     

警报关联图：一种网络脆弱性量化评估的新方法

作为一种基于模型的脆弱性分析技术,攻击图能够识别网络中存在的脆弱性和它们之间的相互关系,分析出可能的攻击路径和潜在威胁.论文在攻击图的基础上提出了警报关联图的概念,利用攻击图中蕴含的脆弱性先验知识,将实时IDS警报信息映射到攻击路径,动态反映攻击进程和攻击者意图.在此基础上提出了一种基于警报关联图的网络脆弱性量化评估方法,通过计算警报关联边的权值对网络脆弱性进行动态分析,这种方法结合了静态的网络脆弱性先验知识和动态变化的攻击者意图,能有效反映网络脆弱性在动态攻击情况下的变化.     

基于规则的动态频谱接入研究

动态频谱接入面临的关键技术之一是对接入时机和方式进行有效地管控,防止由于频谱的接入使用过于灵活造成用频的干扰和混乱。将频谱接入的时间和方式给予规则上的约束和指导,基于规则构建动态频谱管理框架可以有效实现频谱的实时管控。对动态频谱接入的规则及表述方式进行了讨论,分析了基于规则的动态频谱接入过程,最后结合美军XG项目的试验结果分析了基于规则的动态频谱接入的应用前景。     

顺序PROLOG机存储组织研究

YH-SIM是一种正在研制中的顺序PROLOG机。本文介绍该机存储组织的设计考虑。根据PROLOG过程执行的具体特点,文中提出了一种多专用Cache的存储子系统结构,旨在支持深度优先加回溯的顺序PROLOG求解机制。即按照不同的访问方式,设立常规Cache和栈式Cache,分别支持存储空间中的随机访问区域和栈式访问区域。作为一个典型的子部分,文中详细讨论了选择点Cache的控制和调度策略。     

Dynamic policy for idling time preservation

This study aims to determine and evaluate dynamic idling policies where an agent can idle while some customers remain waiting. This type of policies can be employed in situations where the flow of urgent customers does not allow the agent to spend sufficient time on back-office tasks. We model the system as a single-agent exponential queue with abandonment. The objective is to minimize the system's congestion while ensuring a certain proportion of idling time for the agent. Using a Markov decision process approach, we prove that the optimal policy is a threshold policy according to which the agent should idle above (below) a certain threshold on the queue length if the congestion-related performance measure is concave (convex) with respect to the number of customers present. We subsequently obtain the stationary probabilities, performance measures, and idling time duration, expressed using complex integrals. We show how these integrals can be numerically computed and provide simpler expressions for fast-agent and heavy-traffic asymptotic cases. In practice, the most common way to regulate congestion is to control access to the service by rejecting some customers upon arrival. Our analysis reveals that idling policies allow high levels of idling probability that such rejection policies cannot reach. Furthermore, the greatest benefit of implementing an optimal idling policy occurs when the objective occupation rate is close to 50% in highly congested situations.     

Stochastic allocation of inspection capacity to competitive processes

Optimal allocation and control of limited inspection capacity for multiple production processes are considered. The production processes, which operate independently but share inspection capacity, are subject to random failures and are partially observed through inspection. This study proposes an approach of stochastic allocation, using a Markov decision process, to minimize expected total discounted cost over an infinite time horizon. Both an optimal model and a disaggregate approximation model are introduced. The study provides some structural results and establishes that the control policy is of a threshold type. Numerical experiments demonstrate a significantly decreased amount of computational time required for the disaggregate approach when compared to the optimal solution, while generating very good control policies. © 2002 John Wiley & Sons, Inc. Naval Research Logistics, 49: 78–94, 2002; DOI 10.1002/nav.1049     

AID,GLENEAGLES AND THE RUN-UP TO THE MILLENNIUM +5 SUMMIT

Africa has emerged as a strategic location for transcontinental narcotics trade. Particularly the West African subcontinent has turned into a cocaine warehousing and trans-shipment hub along the way to the European underground markets. At this juncture, African drug networks (ADNs) began to play a momentous role in global drug trade, and pose a considerable threat to international security, as they operate in more than 80 countries. The United Nations Office on Drugs and Crime, Interpol, and Europol perceive ADNs as one of the primary issues in international counter-narcotics policy. These agencies have launched several multilateral initiatives to contain the West African threat. None of these initiatives, however, retarded the expansion of the problem. Indeed, the containment efforts turned out to be quite embryonic. The ADNs eventually entered the Turkish market by the early 2000s. West African drug networks (WADNs) in particular have begun to operate within Turkey extensively, often supplying and distributing drugs. The gravity of the threat became ever more serious by 2012. The upsurge of the new threat has compelled the Turkish drug-law enforcement agencies to adopt new policies and counter-strategies. These policies have to be based upon proper strategic analysis of the threat. This paper seeks to address the need for a threat assessment of ADNs. It investigates the dimensions of the problem, profiles the members of WADNs, their modes of operation, and the factors that compelled them to exploit the illicit Turkish drug markets. The analyses are based upon the scrutiny of 227 narcotic interdictions files and statements from the African individuals in these case files. The paper concludes by presenting policy implications and recommendations for the Turkish security and foreign-policy institutions to cope with this impending threat.     

Bayes adaptive control of two-echelon inventory systems i: development for a special case of one-station lower echelon and monte carlo evaluation

Bayes adaptive control policies are developed in the present paper for the special case of a one-station lower echelon: a Poisson distribution of demand, whose mean is assumed to have a prior gamma distribution. The cost structure is of a common type. The ordering policy for the upper echelon, which minimizes expected cost, is replaced by a new type of policy, called Bayes prediction policy. This policy does not require tedious computations, of the sort required by dynamic programming solutions. The characteristics of the policies are studied by Monte Carlo simulation, and supplemented by further theoretical development.     

UDP协议的海量信息快速传输解决方案

提出了一种在网络上提高大容量信息传输速度的实现方案和算法。它对传统的文件传输方式进行了改进,将点对点的传输转换成多点对一点的传输。对数据源的识别、缓冲区的管理、负载的分配、流量的控制等问题进行了说明。该算法简洁、灵活、高效,具有很强的实用性。最后对实验结果进行了讨论和分析。     

Stationary (s,s) policies for a finite horizon

In the finite-horizon stochastic (s, S) inventory model with periodic review the parameters of the optimal policy generally vary with the length of the horizon. A stationary policy, however, is easier to implement and may be easier to calculate. This paper studies optimal stationary policies for a finite horizon and relates them to optimal policies through their relation to optimal stationary policies for an infinite horizon.     

Dynamic inventory control with limited capital and short‐term financing

For most firms, especially the small‐ and medium‐sized ones, the operational decisions are affected by their internal capital and ability to obtain external capital. However, the majority of the literature on dynamic inventory control ignores the firm's financial status and financing issues. An important question that arises is: what are the optimal inventory and financing policies for firms with limited internal capital and limited access to external capital? In this article, we study a dynamic inventory control problem where a capital‐constrained firm periodically purchases a product from a supplier and sells it to a market with random demands. In each period, the firm can use its own capital and/or borrow a short‐term loan to purchase the product, with the interest rate being nondecreasing in the loan size. The objective is to maximize the firm's expected terminal wealth at the end of the planning horizon. We show that the optimal inventory policy in each period is an equity‐level‐dependent base‐stock policy, where the equity level is the sum of the firm's capital level and the value of its on‐hand inventory evaluated at the purchasing cost; and the structure of the optimal policy can be characterized by four intervals of the equity level. Our results shed light on the dynamic inventory control for firms with limited capital and short‐term financing capabilities.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 184–201, 2014     

Denumerable state markovian sequential control processes: On randomizations of optimal policies

We consider a denumerable state Markovian sequential control process. It is well known that when we consider the expected total discounted income as a criterion, there exists a nonrandomized stationary policy that is optimal. It is also well known that when we consider the expected average income as a criterion, an optimal nonrandomized stationary policy exists when a certain system of equations has a solution. The problem considered here is: if there exist two optimal nonrandomized stationary policies, will a randomization of these two policies be optimal? It is shown that in the discounted case the answer is always yes, but in the average income case, the answer is yes only under certain additional conditions.