物理层认证的中间人导频攻击分析

现有物理层认证机制依赖合法信道状态信息(CSI)的私有性,一旦攻击者能够操控或窃取合法信道,物理层认证机制就会面临被攻破的威胁。针对上述缺陷,该文提出一种中间人导频攻击方法(MITM),通过控制合法双方的信道测量过程对物理层认证机制进行攻击。首先对中间人导频攻击系统进行建模,并给出一种中间人导频攻击的渐进无感接入策略,该策略允许攻击者能够顺利接入合法通信双方;在攻击者顺利接入后,可对两种基本的物理层认证机制发起攻击：针对基于CSI的比较认证机制,可以实施拒绝服务攻击和仿冒接入攻击;针对基于CSI的加密认证机制,可以实现对信道信息的窃取,从而进一步破解认证向量。该攻击方法适用于一般的公开导频无线通信系统,要求攻击者能够对合法双方的导频发送过程进行同步。仿真分析验证了渐进无感接入策略、拒绝服务攻击、仿冒接入攻击、窃取信道信息并破解认证向量等多种攻击方式的有效性。     

物理层认证的中间人导频攻击分析

现有物理层认证机制依赖合法信道状态信息(CSI)的私有性,一旦攻击者能够操控或窃取合法信道,物理层认证机制就会面临被攻破的威胁.针对上述缺陷,该文提出一种中间人导频攻击方法(MITM),通过控制合法双方的信道测量过程对物理层认证机制进行攻击.首先对中间人导频攻击系统进行建模,并给出一种中间人导频攻击的渐进无感接入策略,该策略允许攻击者能够顺利接入合法通信双方;在攻击者顺利接入后,可对两种基本的物理层认证机制发起攻击:针对基于CSI的比较认证机制,可以实施拒绝服务攻击和仿冒接入攻击;针对基于CSI的加密认证机制,可以实现对信道信息的窃取,从而进一步破解认证向量.该攻击方法适用于一般的公开导频无线通信系统,要求攻击者能够对合法双方的导频发送过程进行同步.仿真分析验证了渐进无感接入策略、拒绝服务攻击、仿冒接入攻击、窃取信道信息并破解认证向量等多种攻击方式的有效性.     

密钥交换中中间人攻击的防范

Diffie-Hellman密钥交换是一种可以在有窃听信道中安全地协商密钥的有效算法,但是它不能抵抗中间人攻击。不过在一些特定环境下,可以通过验证密钥的方法来防范可能存在的中间人攻击。文章不仅论证了该方法的理论基础,并给出厂它在实际应用中的例子,最后还提供了一种获得随机数的新方法。     

移动云计算应用安全问题研究

在移动云计算中,由于数据访问和存储是在移动设备外部完成的,且由远程云服务器进行处理,因而用户无法对其进行控制。因此,安全和隐私是网络安全管理人员面临的重大挑战。随着社交媒体和移动互联网用户的快速增长,恶意威胁也随之增加。这些威胁大多是移动设备威胁、通信威胁和云环境威胁的组合体。文章从移动设备/终端、无线通信信道和云基础设施3个级别分析移动云计算的安全需求,讨论移动云计算应用面临的安全威胁,最后给出移动云计算应用安全的几种解决方案。     

3G背景下异构互连网络的中间人攻击

文章介绍了2G/3G以及3G-WLAN两种异构互连网络的中间人攻击,分析了攻击的可行性,并各自讨论了相应的防御机制,最后对异构无线网络的安全做出了总结和展望。     

一种基于ARP欺骗的中间人攻击方法及防范

中间人攻击是网络攻击的重要手段之一。笔者结合ARP欺骗的技术特点设计并实现了一种中间人攻击的方法,通过对该方法的分析与实现,加深了对中间人攻击的原理及手段的了解,并提出了相应的防范措施。     

移动云计算安全问题及安全度量方法浅析

移动云计算安全度量是云计算安全中的一个研究领域,主要是研究采用手机等移动终端设备,通过移动互联网使用云计算服务过程中的安全问题及安全度量方法。本文分析了目前移动云计算行业发展过程中存在的安全问题,指出了这些安全问题是阻碍用户使用云计算服务的关键,分析了传统的安全度量方法在移动云计算中的应用的优缺点,并在此基础上提出了一种基于场景的移动云计算安全度量方法,该方法可以有效度量和展示用户正在使用的云计算服务的安全情况,可以解除用户对于安全的顾虑,让用户放心使用。     

移动互联网环境下云计算安全浅析

移动云计算是移动互联网产业与云计算技术的结合,是ICT行业炙手可热的新业务发展模式,但其面临着新的安全威胁。文章浅析了移动互联网环境下的云计算安全问题,给出了安全建议,为移动互联网环境下云计算安全发展提供参考。     

移动互联网中的云计算安全架构

移动互联网(Mobile Internet)是以移动设备为核心,融合了互联网和移动通信技术的一种计算机技术,是当今信息科技发展的热点之一。而云计算(Cloud Computing)作为一种高效、灵活、节能的计算模式,是当前信息化建设的重要技术手段之一。移动互联网与云计算的结合,可以为用户提供更多、更丰富的服务,提高信息处理的效率和质量。然而,移动互联网中的云计算也面临着安全问题,如何构建安全、可靠的云计算安全架构,成了一个亟待解决的问题。     

移动互联网环境下的云计算安全技术体系架构

文章在研究分析云计算安全风险和安全技术体系架构的基础上,结合移动互联网的特点,设计了一个多层次、多级别、弹性、跨平台和统一用户接口的移动互联网通用云计算安全技术体系架构。该架构可实现不同等级的差异化云安全服务,其中跨层的云安全管理平台可对整个系统的运维安全情况进行跨安全域和跨安全级别的监控。     

双云安全计算架构

针对现有安全技术对云计算数据外包保护的不足,提出一个可以应用于不可信商业云环境的数据外包计算和存储双云安全框架,用户通过一个可信任的云(可以是一个私有云或是通过多个安全硬件模块建立的云)来通信,可信的云加密并校验不可信云中存储的数据以及执行的操作。通过分离计算,把可信的云用来处理对时间不敏感的安全设置操作,同时用商业不可信云来处理大量的计算,从而实现安全的云计算数据外包。     

一种基于分层多代理的云计算负载均衡方法

针对现有云计算系统中负载均衡方法的不足,借鉴系统逻辑分层和多代理的思想,提出一种基于分层多代理的云计算负载均衡方法.通过对云计算平台逻辑分层,在任务代理层设置任务监控代理和任务子代理,根据用户任务的差异性,采用基于任务优先级和QoS目标约束的调度策略协同完成任务调度;在资源代理层设置资源监控代理和资源子代理,考虑物理节点的异构性,采用基于启发式贪婪的资源分配策略协同完成虚拟机到物理节点的映射.通过评估对比仿真实验,结果表明该方法在任务调度效率、任务完成时间、截止时间违背率和负载均衡度方面表现更优,多代理有效地分担了中心管理节点的管理负载,使云计算平台的任务处理能力、资源利用率及鲁棒性均得到了进一步的提升.     

Building a Platform to Bridge Low End Mobile Phones and Cloud Computing Services

Two waves of technology are dramatically changing daily life: cloud computing and mobile phones. New cloud computing services such as webmail and content rich data search have emerged. However, in order to use these services, a mobile phone must be able to run new applications and handle high network bandwidth. Worldwide, about 3.45 billion mobile phones are low end phones;they have low bandwidth and cannot run new applications. Because of this technology gap, most mobile users are unable to experience cloud computing services with their thumbs. In this paper, a novel platform, Thumb-in-Cloud, is proposed to bridge this gap.Thumb-in-Cloud consists of two subsystems: Thumb-Machine and Thumb-Gateways. Thumb-Machine is a virtual machine built into a low end phone to enable it to run new applications. Thumb-Gateways can tailor cloud computing services by reformatting and compressing the service to fit the phone' s profile.     

面向移动云计算的自适应服务选择方法研究

Despite the rapid advances in mobile tech-nology, many constraints still prevent mobile de-vices from running resource-demanding applica-tions in mobile environments. Cloud computing with flexibility, stability and scalability enables ac-cess to unlimited resources for mobile devices, so more studies have focused on cloud computing- based mobile services. Due to the stability of wire-less networks, changes of Quality of Service (QoS) level and user' real-time preferences, it is becoming challenging to determine how to adaptively choose the “appropriate”service in mobile cloud compu-ting environments. In this paper, we present an a-daptive service selection method. This method first extracts user preferences from a service's evaluation and calculates the similarity of the service with the weighted Euclidean distance. Then, they are com-bined with user context data and the most suitable service is recommended to the user. In addition, we apply the fuzzy cognitive maps-based model to the adaptive policy, which improves the efficiency and performance of the algorithm. Finally, the experi-ment and simulation demonstrate that our approach is effective.     

移动云服务的自适应业务质量管理

The rapid growth of cloud computing and mobile Internet services has triggered the emergence of mobile cloud services. Among many challenges, QoS management is one of the crucial issues for mobile cloud services. However, existing works on QoS management for cloud computing can hardly fit well to the mobile environment. This paper presents a QoS management architecture and an adaptive management process that can predict, assess and ensure QoS of mobile cloud services. Furthermore, we propose an adaptive QoS management model based on Fuzzy Cognitive Maps (FCM), which suitably represents the causal relationships among QoS related properties and cloud service modes. We evaluate the proposed solution and demonstrate its effectiveness and benefits based on simulation work.     

A provable and secure mobile user authentication scheme for mobile cloud computing services

The mobile cloud computing (MCC) has enriched the quality of services that the clients access from remote cloud‐based servers. The growth in the number of wireless users for MCC has further augmented the requirement for a robust and efficient authenticated key agreement mechanism. Formerly, the users would access cloud services from various cloud‐based service providers and authenticate one another only after communicating with the trusted third party (TTP). This requirement for the clients to access the TTP during each mutual authentication session, in earlier schemes, contributes to the redundant latency overheads for the protocol. Recently, Tsai et al have presented a bilinear pairing based multi‐server authentication (MSA) protocol, to bypass the TTP, at least during mutual authentication. The scheme construction works fine, as far as the elimination of TTP involvement for authentication has been concerned. However, Tsai et al scheme has been found vulnerable to server spoofing attack and desynchronization attack, and lacks smart card‐based user verification, which renders the protocol inapt for practical implementation in different access networks. Hence, we have proposed an improved model designed with bilinear pairing operations, countering the identified threats as posed to Tsai scheme. Additionally, the proposed scheme is backed up by performance evaluation and formal security analysis.     

移动Ad Hoc云中任务卸载的联合优化策略

为了降低移动Ad Hoc云中客户端卸载计算密集型任务过程中产生的计算能耗、传输能耗和任务时延,该文提出了一种联合优化算法。该算法首先基于计算能耗、通信能耗及任务时延进行建模;然后进行预估计,以选择更优的代理终端,并由此降低总的系统能耗与任务时延。仿真结果表明,相对于传统云算法,该算法在系统能耗和任务时延两方面均有显著提升。     

车联网移动云系统虚拟机迁移技术研究

智能交通车联网的发展面临着异构网络传输容量瓶颈、海量信息高效处理瓶颈等一系列具有挑战性的难题。针对该系列问题,本文提出一种层次化移动云系统参考模型,使车载移动终端根据其网络环境与通信能力择优接入相应层次的云服务,达到移动网络资源与云计算资源的最佳匹配。同时,由于车载单元的快速移动性,车联网中的信息传输随时可能中断,这就制约了车联网业务服务质量的提高,对云计算持续稳定的服务构成了很大的挑战,这一瓶颈问题可以通过虚拟机动态迁移技术得到改善,从而实现服务的不间断。     

A genetic‐based decision algorithm for multisite computation offloading in mobile cloud computing

Mobile cloud computing is a promising approach to improve the mobile device's efficiency in terms of energy consumption and execution time. In this context, mobile devices can offload the computation‐intensive parts of their applications to powerful cloud servers. However, they should decide what computation‐intensive parts are appropriate for offloading to be beneficial instead of local execution on the mobile device. Moreover, in the real world, different types of clouds/servers with heterogeneous processing speeds are available that should be considered for offloading. Because making offloading decision in multisite context is an NP‐complete, obtaining an optimal solution is time consuming. Hence, we use a near optimal decision algorithm to find the best‐possible partitioning for offloading to multisite clouds/servers. We use a genetic algorithm and adjust it for multisite offloading problem. Also, genetic operators are modified to reduce the ineffective solutions and hence obtain the best‐possible solutions in a reasonable time. We evaluated the efficiency of the proposed method using graphs of real mobile applications in simulation experiments. The evaluation results demonstrate that our proposal outperforms other counterparts in terms of energy consumption, execution time, and weighted cost model.