可防御SSDF攻击的宽带压缩频谱感知

SSDF（Spectrum Sensing Data Falsification）攻击是认知无线网络中对频谱感知性能危害最大的攻击方式之一。基于认知无线网络中信号频域的固有稀疏性,本文结合了压缩感知(CS)技术与平均一致(average consensus)算法,建立了可防御SSDF攻击的分布式宽带压缩频谱感知模型。本文建立了次用户的声望值指标,用以在分布式信息融合的过程中更加准确地排除潜在的恶意次用户影响。在感知阶段,各个CR节点对接收到的主用户信号进行压缩采样以减少对宽带信号采样的开销和复杂度,并做出本地频谱估计。在信息融合阶段,各CR节点的本地频谱估计结果以分布式的方式进行信息融合,排除潜在恶意次用户的影响,得到最终的频谱估计结果。仿真结果表明,本文提出的分布式频谱感知模型可以有效地抵御SSDF攻击,提高了频谱感知的性能。      

Distributed cooperative spectrum sensing based on reinforcement learning in cognitive radio networks

Spectrum sensing is an initial task for the successful operation of cognitive radio networks (CRN). During cooperative spectrum sensing, malicious secondary user (SU) may report false sensing data which would degrade the final aggregated sensing outcome. In this paper, we propose a distributed cooperative spectrum sensing (CSS) method based on reinforcement learning (RL) to remove data fusion between users with different reputations in CRN. This method regards each SU as an agent, which is selected from the adjacent nodes of CRN participating in CSS. The reputation value is used as reward to ensure that the agent tends to merge with high reputation nodes. The conformance fusion is adopted to promote consensus of the whole network, while it’s also compared with the decision threshold to complete CSS. Simulation results show that the proposed method can identify malicious users effectively. As a result, the whole CRN based on RL is more intelligent and stable.     

移动终端数据同步协议研究

作为移动因特网的一种重要的应用，数据同步可以使人们能够使用各种各样的无线或者移动终端设备处理和存储各种个人数据，像电话号码，个人记事本，会议信息以及进行移动设备之间的信息交换和数据同步，国际上由SyncML发起组制定的SyncML同步协议已经成为WAP2.0的一个标准应用，在SyncML所支持的有限的几个文本数据类型基础上，本文利用XML语音定义了一种全新的数据类型，它包含了图像，声音等SyncML没有定义的多媒体数据类型，从而大大丰富了SyncML的数据类型。     

模拟人群信任和决策机制的协作频谱感知方法

通过模拟人群内部的信任和决策机制,针对多用户的频谱协作感知一致性问题,提出了一种分布式算法。该算法首先通过网络的历次协作过程预测出各感知用户的动态可信值,据此产生用户的相对可信值,并结合决策机制使得用户之间进行数据交互,随着数据的可信、迭代交互,所有用户状态将趋于一致,最后通过判定算法得出最终结果。算法充分考虑了实际环境中各用户频带感知能力的不平衡性,而且各次级用户只需要进行少量局部数据交换即可实现协作感知,与传统的OR-rule、1-out-of-N rule以及普通迭代法有较大区别。对3种数据篡改攻击进行了分析,并在预测算法的基础上提出了相应的安全策略。理论分析与仿真结果表明,新算法在准确性和安全性上均优于传统合作频谱感知算法,能显著提高频谱感知准确率,同时兼具较强的防攻击能力。     

TAEffect: Quantifying interaction risks in trust-enabled communication systems

The interactive risks of different devices, serving as clients or servers, have increasingly attracted huge attention in various communication systems, such as wireless sensor networks, wireless communication networks, and mobile crowd-sensing. At present, lots of countermeasures had been proposed and deployed accordingly. Nevertheless, the investigation on the interaction risks between different devices is still very limited to date. In this paper, we propose a novel adverse effect inference mechanism TAEffect for malicious behaviors of devices emerged in various decentralized and open communication systems/networks through network-percolation theory. At first, four typical malicious interactional behaviors are mapped into four topologies, then, upon which a network influence-inspired approach is employed to quantify the adverse effect. Finally, multifacet experiments using five real-world datasets and a synthetic testbed are performed to validate the efficiency and effectiveness. The experimental results show our proposed approach is significant and rational to quantitatively calculate and qualitatively mirror the four kinds of malicious interactional behaviors in diverse misbehavior-emerged communication systems.     

A reconfigurable upper audio band modem for data communication between mobile devices

For communicating short data sequences over small distances, the use of devices with conventional wireless radio frequency interfaces requires standardized hardware, dedicated infrastructure and appropriate Link/Network layer protocols. To address challenges associated with these requirements, a communication mechanism using devices which support simple audio interfaces (speakers and microphones) is proposed using the upper audio band (UAB) of frequencies (16–20 kHz). Devices with audio interfaces can be deployed in a personal area network for communicating at low data rates over small distances. Multi-tone FSK modulation is used for transmitting Reed–Solomon encoded data over the UAB. For peer-to-peer communication applications, a sensing mechanism is enabled on the receiving device to sense for empty time–frequency slots and schedule its data transmission at the appropriate times. A system prototype is developed using portable speakers and smartphones with sensitive microphones. The effective throughput of the modem is evaluated for different sensing durations and distances. Ad-hoc peer-to-peer networks can be enabled between mobile devices for communicating short data sequences based on the UAB modem.     

可信的反馈声誉保护协作频谱感知软判决算法

协作频谱感知中信任机制的引入,起到了抑制恶意用户频谱感知数据伪造( SSDF)攻击行为的作用。然而,数据融合中心不加区分地接收协作感知结束后的反馈信息,为恶意用户带来了实施“掺沙子”攻击的机会。恶意用户向数据融合中心反馈错误的主用户频谱状态,使信任机制不能得出准确的信任值。为此,提出了一种基于反馈声誉的信任机制,考虑反馈中的个体性特征,引入反馈声誉的思想来量化认知用户信任值。同时,将信任值量化结果用于权重经典软判决算法———序贯概率比检测( SPRT)算法,消除SSDF恶意用户参与软判决数据融合的影响,形成可信序贯概率比检测算法( FSPRT)。仿真结果表明FSPRT算法的性能优于传统SPRT算法,能有效降低网络信任值计算误差,并保持较好的感知性能。     

Design and implementation of a wireless sensor network architecture using smart mobile devices

Wireless sensor networks improve the quality of human daily life like ubiquitous city and healthcare services as well as the fundamental monitoring such as environment pollution, tunnel monitoring, earthquake diagnostic, and so on. To increase usability and feasibility of collected sensor data, a wireless sensor network should be required to apply a variety of mobile devices to give the information at anytime and anywhere to users. Thus, we present multi-sensor centric smart sensor network architecture using general mobile devices in order to provide more efficient and valuable sensor network application and services. The proposed system architecture is based on IEEE 802.15.4-2006 standard with smart mobile devices. We also show some scenarios with on-demand request and real time event driven data to show the feasibility of the proposed architecture using five kinds of sensors such as magnetic, photodiode, microphone, motion and vibration. Based on the experiment results, we show that the proposed system has the potential as smart mobile device-based wireless sensor network architecture.     

Architecture and enablers for optimized radio resource usage in heterogeneous wireless access networks: The IEEE 1900.4 Working Group

Over the past decade or so, the wireless industry has undergone many significant changes. Radio systems have moved toward forming heterogeneous wireless networks: collaborations of multiple radio access networks, which in some cases operate different radio access technologies, such as second- and third-generation cellular RATs, IEEE 802.x wireless standards, and so on. On the other hand, multimode reconfigurable user devices with the ability to choose among various supported RATs have become a reality, and devices and networks with dynamic spectrum access capabilities, allowing real-time sharing of spectrum resource usage among different systems, are expected to be a part of the future radio eco-space. As a result of these changes, there is a need to develop a standard that addresses the requirements and leverages the opportunities posed by such a versatile radio environment. To this end, IEEE 1900.4 aims to standardize the overall system architecture and information exchange between the network and mobile devices, which will allow these elements to optimally choose from available radio resources. In other words, the standard facilitates the distributed dynamic optimization of the usage of spectrum offered by the heterogeneous wireless network, relying on a collaborative information exchange between networks and mobile devices, thereby acting as a common means to improve overall composite capacity and quality of service for the served networks. This article provides a snapshot of IEEE P1900.4 in its current form, covering the scope and purpose of the standard, reference use cases for which the standard is applicable, its system and functional architectures, and finally, the information model for its main interfaces.     

A secure mobile healthcare system using trust-based multicast scheme

Due to the introduction of telecommunication technologies in telemedicine services, the expeditious development of wireless and mobile networks has stimulated wide applications of mobile electronic healthcare systems. However, security is an essential system requirement since many patients have privacy concerns when it comes to releasing their personal information over the open wireless channels. For this reason, this study discusses the characteristics and security issues with wireless and pervasive data communications for a ubiquitous and mobile healthcare system which consists of a number of mobile devices and sensors attached to a patient. These devices form a mobile ad hoc sensor network and collect data that are sent to a hospital or healthcare center for monitoring. Subsequently, this paper discusses the innovation and design of a novel trust evaluation model. We then propose a secure multicast strategy that employs trust in order to evaluate the behavior of each node, so that only trustworthy nodes are allowed to participate in communications, while the misbehavior of malicious nodes is effectively prevented. We analyze the security properties of our multicast scheme and evaluate its performance based on simulation experiments. Our experimental results demonstrate that our scheme not only achieves the necessary data transmission in mobile environments, but also provides more security with reasonably little additional overhead.     

DCR‐MAC: distributed cognitive radio MAC protocol for wireless ad hoc networks

The MAC protocol for a cognitive radio network should allow access to unused spectrum holes without (or with minimal) interference to incumbent system devices. To achieve this main goal, in this paper a distributed cognitive radio MAC (DCR‐MAC) protocol is proposed for wireless ad hoc networks that provides for the detection and protection of incumbent systems around the communication pair. DCR‐MAC operates over a separate common control channel and multiple data channels; hence, it is able to deal with dynamics of resource availability effectively in cognitive networks. A new type of hidden node problem is introduced that focuses on possible signal collisions between incumbent devices and cognitive radio ad hoc devices. To this end, a simple and efficient sensing information exchange mechanism between neighbor nodes with little overhead is proposed. In DCR‐MAC, each ad hoc node maintains a channel status table with explicit and implicit channel sensing methods. Before a data transmission, to select an optimal data channel, a reactive neighbor information exchange is carried out. Simulation results show that the proposed distributed cognitive radio MAC protocol can greatly reduce interference to the neighbor incumbent devices. A higher number of neighbor nodes leads to better protection of incumbent devices. Copyright © 2008 John Wiley & Sons, Ltd.     

NFC安全通信架构的研究

随着数字信息的使用越来越广泛,信息遭受攻击的次数和种类也越来越多,现阶段的智能卡身份验证架构在安全性和性能上,依然有一定程度的提升空间。在基于智能卡安全性的前提下,增加智能卡进行身份认证时的计算性能,加入了NFC近距离无线通信技术,以目前个人式手持设备中使用率最高的手机为例,模拟NFC手机在ATM上进行用户身份认证的沟通流程,以期能为用户提供一个崭新、可靠、便利性高的安全通信机制。     

群智感知网络的发展及挑战

随着无线移动终端设备的爆炸式普及,移动感知和众包思想的结合产生了新型物联网感知模式,即群智感知。文章结合群智感知网络的发展,分别介绍了它的概念、基本特征、系统结构、典型应用以及面临的问题。     

Mitigating spectrum sensing data falsification attack in ad hoc cognitive radio networks

In a cognitive radio ad hoc network, there is no central authority. Hence, distributed collaborative spectrum sensing (CSS) plays a major role in achieving an accurate spectrum sensing result. However, CSS is sensitive to spectrum sensing data falsification (SSDF) attack, in which a malicious user falsifies its local sensing report before disseminating it into the network. To capture such abnormal behavior of a node, we present an approach for detecting SSDF attack based on dissimilarity score. A secondary user (SU) computes the dissimilarity score of its neighbors from the messages received from its h‐hop neighbors. Further, we also present how the proposed scheme can be used on the sequence of sensing reports to detect and isolate the malicious SUs on the fly.     

Building accurate radio environment maps from multi-fidelity spectrum sensing data

In cognitive wireless networks, active monitoring of the wireless environment is often performed through advanced spectrum sensing and network sniffing. This leads to a set of spatially distributed measurements which are collected from different sensing devices. Nowadays, several interpolation methods (e.g., Kriging) are available and can be used to combine these measurements into a single globally accurate radio environment map that covers a certain geographical area. However, the calibration of multi-fidelity measurements from heterogeneous sensing devices, and the integration into a map is a challenging problem. In this paper, the auto-regressive co-Kriging model is proposed as a novel solution. The algorithm is applied to model measurements which are collected in a heterogeneous wireless testbed environment, and the effectiveness of the new methodology is validated.     

基于加权平均一致算法的宽带压缩频谱感知

在认知无线电(CR)网络中进行频谱共享接入,首要的任务是进行频谱感知,并发现频谱空洞。基于认知无线网络中信号频域的固有稀疏性,本文结合了压缩感知(CS)技术与加权平均一致(weighted average consensus)算法,建立了分布式宽带压缩频谱感知模型。频谱感知分为两个阶段,在感知阶段,各个CR节点对接收到的主用户信号进行压缩采样以减少对宽带信号采样的开销和复杂度,并做出本地频谱估计;在信息融合阶段,各CR节点的本地频谱估计结果以分布式的方式进行信息融合,并得到最终的频谱估计结果,获得分集增益。仿真结果表明,结合压缩感知与加权平均一致算法增强了频谱感知的性能,比在相同的CR网络中使用平均一致算法时有了性能上的提升。      

Scalable Data Processing for Community Sensing Applications

Participatory Sensing is a new computing paradigm that aims to turn personal mobile devices into advanced mobile sensing networks. For popular applications, we can expect a huge number of users to both contribute with sensor data and request information from the system. In such scenario, scalability of data processing becomes a major issue. In this paper, we present a system for supporting participatory sensing applications that leverages cluster or cloud infrastructures to provide a scalable data processing infrastructure. We propose and evaluate three strategies for data processing in this architecture.     

移动互联网端到端流量管控策略研究

本文通过对无线网络新技术和新架构的分析,针对2G/3G/LTE/WLAN多网络环境下,研究如何对不同的用户类型、业务类型、时间段、累积量进行QoS控制,以提升业务体验和用户满意度。基于PCC承载架构和ANDSF多连接管理机制,通过端到端的流量管控技术提升互联网带宽的使用率。借鉴都江堰水利工程原理,通过实施网络流量控制、均匀网络流量、降低并有效控制流量峰值,提出了移动互联网网络协同的融合策略控制方案,实现了合理配置网络资源、合理有效控制网络投资,为移动互联网业务发展创造条件,为移动互联网时代应对数字洪水做好充分的技术储备。     

基于ESD测试的无线电网络抗SSDF攻击协作频谱感知方案

针对认知无线电网络中协作频谱感知容易遭受数据伪造攻击的问题,提出一种基于检验统计和极端学生化偏差检验法的协作频谱感知方案。首先,将差分进化算法与加权增益合并软决策融合方法相结合,形成一种高效的节点决策融合机制。然后,在协作感知中,根据节点的软决策数据,利用检验统计消除故障认知节点。最后,利用提出的改进型ESD检验法消除恶意认知节点,从而形成全局决策。仿真结果表明,该方案在协作感知中能够有效过滤SSDF攻击数据,具有较低的误检测率。     

Querying in Packs: Trustworthy Data Management in Ad Hoc Networks

We describe a trust-based data management framework enabling mobile devices to access the distributed computation, storage, and sensory resources available in pervasive computing environments. Available resources include those in the fixed surrounding infrastructure as well as services offered by other nearby mobile devices. We take a holistic approach that considers data trust, security, and privacy and focus on the collaborative mechanisms providing a trustworthy data management platform in an ad hoc network. The framework is based on a pack formation mechanism that enables collaborative peer interactions using context information and landmarks. A pack provides a routing substrate allowing devices to find reliable information sources and coordinated pro-active and reactive mechanisms to detect and respond to malicious activity. Consequently, a pack forms a foundation for distributed trust management and data intensive interactions. We describe our data management framework with an emphasis on pack formation in mobile ad hoc networks and present preliminary results from simulation experiments.