Price‐based interference management in dense femtocell systems

Femtocell technology has been drawing considerable attention as a cost‐effective means of improving cellular coverage and capacity. However, under co‐channel deployment, femtocell system in dense environment may incur high uplink interference to existing macrocells and experiences strong inter‐cell interference at the same time. To manage the uplink interference to macrocell, as well as the inter‐cell interference, this paper proposes a price‐based uplink interference management scheme for dense femtocell systems. Specifically, on the one hand, to guarantee the macrocell users' quality of service, the macrocell base station prices the interference from femtocell users (FUEs) subject to a maximum tolerable interference power constraint. On the other hand, the inter‐cell interference is also taken into consideration. Moreover, a Stackelberg game model is adopted to jointly study the utility maximization of the macrocell base station and FUEs. Then, in order to reduce the amount of information exchange, we design a distributed power allocation algorithm for FUEs. In addition, admission control is adopted to protect the active FUEs' performance. Numerical results show that the price‐based interference management scheme is effective. Meanwhile, it is shown that the distributed power allocation combined with admission control is capable of robustly protecting the performance of all the active FUEs. Copyright © 2013 John Wiley & Sons, Ltd.     

Game theory approach for detecting vulnerable data centers in cloud computing network

Nowadays, cloud computing has many benefits to accessibility, scalability, and cost‐effectiveness, leading to network security risks and vulnerabilities. Cloud computing is gaining in popularity with the advances and growth of its systems. Therefore, the security of this system and the identification of vulnerable data centers are more complicated than the past. Definitely discovering vulnerable data centers that are vulnerable to attacks can help to strengthen these data centers and provide a safer and more secure network structure. This paper examines the vulnerability of malware data centers in the infrastructure and cloud computing network structure. Based on the analysis of the cloud computing system in the field of game theory, we introduce a developed model for identifying vulnerable data centers in cloud computing. The developed model in this paper is based on the game theory as a mathematical tool. According to the game theory, we introduce a measure of the degree of vulnerability of data centers in the cloud computing network.     

RAT selection for a low battery mobile device for future 5G networks

The growth of wireless communication toward fifth generation will lead to the existence of number of access technologies to provide seamless connectivity and form heterogeneous network environment. Earlier, there was single access technology to run applications, but 5G will have heterogeneous network environment and provide separate network for each application. As compared with 4G, 5G will provide increase in data rate, decrease in delay, increase in quality of service, and so on because of its various enabling technologies. Therefore, for each application, selection of best access network via its enabling technology is an important task. This selection is done either at user terminal side or at network operator side by combining preferences for network attributes and network parameters. In this paper, to enjoy 5G, selection is done in a heterogeneous networks environment for enabling technologies like device‐to‐device communication, spectrum sharing, enhancing quality of experience, energy efficiency, and so on. This selection is done via optimization techniques for a fixed duration video clip that is to be transmitted from a device running low in battery. The selection environment composed of UMTS, WLAN1, and WLAN2 as available networks. The simulation results show that the network selected for each enabling technology supports various features of 5G. Also, error analysis of selection results is done using confidence interval estimate at 90%, 92%, and 95% confidence level. From results obtained, it is seen that different optimization techniques used to access network for different enabling technologies (providing 5G features) prove to be useful for future 5G network.     

一种基于博弈的联盟组网方法

针对缺乏有效联盟收益分配机制,导致发送端拒绝协作,同时发送信号,造成接收端信号重叠,该文提出一种基于博弈的安全联盟组网方法。首先,将协作博弈机制中的收益分摊机制引入安全联盟组网自适应形成方法,建立发送端联盟组网模型。然后,为实现联盟方式组网,基于博弈方法将联盟组网相比非联盟时增加的总安全速率作为可转移的收益函数,平均分配给组网内各个发送端;之后,发送端遍历所有可能形成的联盟组网,得到均摊收益最大的联盟组网方式;最后,发送端自适应形成该联盟组网,无需发送信号或相同需求下窃听信道条件最坏的发送端发信号,其余所有发送端通过发送人工噪声进行协作。仿真分析验证了该方法的公平性和有效性,当发送端功率等于20 mW时,高斯信道下的网络平均安全速率相比初始状态提高1.8 。     

基于博弈论的无意攻击和隐写分析攻击下嵌入水印漏警概率分析(英文)

Steganalysis attack is to statistically estimate the embedded watermark in the watermarked multimedia,and the estimated watermark may be destroyed by the attacker.The existing methods of false negative probability,however,do not consider the influence of steganalysis attack.This paper proposed the game theory based false negative probability to estimate the impacts of steganalysis attack,as well as unintentional attack.Specifically,game theory was used to model the collision between the embedment and steganalysis attack,and derive the optimal building embedding/attacking strategy.Such optimal playing strategies devote to calculating the attacker destructed watermark,used for calculation of the game theory based false negative probability.The experimental results show that watermark detection reliability measured using our proposed method,in comparison,can better reflect the real scenario in which the embedded watermark undergoes unintentional attack and the attacker using steganalysis attack.This paper provides a foundation for investigating countermeasures of digital watermarking community against steganalysis attack.     

基于水资源的“绿色GDP”核算信息系统建设分析

“绿色GDP”就是不以资源环境的破坏为代价的经济发展模式。可持续发展的社会主义社会建设过程中,并不仅仅将GDP作为国民经济发展的核算方式,而是经济发展过程中所消耗掉的各种自然资源、环境纳入其会计核算范围内,从而以更加客观、真实的角度来呈现出国民经济的运行与发展状态。对我国而言,水资源正日益成为制约经济可持续发展的自然资源之一,加强水资源的“绿色GDP ”核算信息体系的建设,是应对这一问题的有利方式。     

基于博弈的协作路由算法

协作虚拟多输入多输出（VMIMO）传输是一种有效的无线传输性能优化技术。将物理层协作VMIMO技术和网络层路由选择技术相结合,设计跨层VMIMO路由选择方案可以利用VMIMO的分集增益,显著地降低网络传输能耗。如何设计VMIMO协作路由协议抵抗无线网络的自私节点和欺骗行为,保证高数据转发率和低传输能耗成为路由设计中的重大挑战。为了提高自私网络的VMIMO路由性能,提出了一种基于重复路由博弈的VMIMO协作路由算法。该算法将网络划分成多个Group、Group间使用VMIMO传输数据。将Group间路由选择过程建模为重复路由博弈过程。为了提高数据转发的成功率,提出适用度函数评估节点参与数据分组转发的信誉。以此为基础,提出基于适用度的路由选择子算法和路由转发子算法。理论证明所提重复路由博弈可达到帕累托最优。仿真实验结果表明本算法可以促进自私节点相互合作,可获得较高的数据转发率,较好地减少数据传输时延以及能量消耗。     

面向电网业务质量保障的5G高可靠低时延通信资源调度方法

该文研究面向电网业务质量保障的5G 高可靠低时延通信(URLLC)的资源调度机制,以高效利用低频段蜂窝通信系统内有限的频谱和功率资源来兼顾电力终端传输速率和调度时延、调度公平性,保障不同电力业务的通信质量（QoS）。首先,基于URLLC的高可靠低时延传输特性,建立电力终端多小区下行传输模型。然后,提出面向系统下行吞吐量最大化的资源分配问题模型并对其进行分步求解,分别提出基于定价机制与非合作博弈的功率分配算法和基于调度时延要求的改进比例公平算法（DPF）动态调度信道资源。仿真结果表明,提出的资源调度方法能在保证一定传输可靠性和公平性的条件下降低电力终端调度时延,满足不同业务等级的QoS需求,与已知算法对比有一定的优越性。     

Markov微分博弈模型及其在网络安全中的应用

当前基于博弈理论的网络安全研究成果难以应用于实时、连续、随机对抗的网络攻防过程.本文针对网络安全防御的实时性和网络状态变化的随机性,基于动态、实时对抗的视角分析攻防行为,在结合微分博弈模型和Markov决策方法的基础上进行扩展,构建Markov攻防微分博弈模型,分析具有多个阶段且每阶段持续时间较短的攻防过程;提出多阶段博弈均衡解计算方法,设计多阶段最优防御策略选取算法.仿真实验结果表明,模型和算法有效且可行.     

大容量自适应隐写对抗的博弈研究

攻击方拥有自适应规范边信息条件下,如何提高大容量自适应隐写的安全性成为亟待解决的问题.本文对大容量自适应隐写方和攻击方进行博弈建模,分析了博弈均衡存在的条件,通过理论证明给出均衡局势下隐写对抗双方的混合策略和期望支付,最后利用仿真实验验证了理论分析的正确性.研究表明,攻击方的策略与嵌入的信息量无关,期望支付随着嵌入信息量的增加而增加;隐写方选择在载体中某位置进行较多嵌入的概率随着该位置的复杂度增加而增加且不为零.该结论对设计安全的大容量自适应隐写具有一定的指导意义.