基于动态距离的模糊社区识别算法

社区识别技术是公共安全领域潜在危害行为预警预测和已发生危害行为追踪溯源的基础，针对传统社区识别算法将社区视作单一集合而无法描述社区主次成员的问题，提出一种基于动态距离的模糊社区识别算法。该算法将传统的单一社区结构划分为核心区域和边际区域，以边际区域来描述社区的模糊区间。该算法首先将网络设想为动态演变模型，网络中的任意节点均会与其他节点产生互动，互动将改变各节点间距离，距离也反过来影响互动。在阈值的界定下，受到多个社区吸引的节点被划分到边际区域，最终距离分布趋于稳定，各个社区结构得以显现。通过对比实验验证了CDFDD算法在社区识别上的有效性。     

Response time and mechanism of Pd modified TiO2 gas sensor

In this work, gas response properties of Pd modified TiO₂ sensing films are discussed when exposed to H₂ and O₂. TiO₂ films are surface modified in PdCl₂-containing solution by the dipping method and treated for different treatment times to get different surface states. X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM) and Kröger–Vink defect theory are used to characterize the sensing films. The gas response properties indicate that the sensor response time which related to the rate of change of sensor resistance is affected by the activation energy (E). In particular, the sensor treated at 900 °C for 2 h exhibits a response time of about 20–240 ms when exposed to H₂ and 40–130 ms when exposed to O₂ at 500–800 °C.     

Robust visual tracking via CAMShift and structural local sparse appearance model

This paper addresses issues in visual tracking where videos contain object intersections, pose changes, occlusions, illumination changes, motion blur, and similar color distributed background. We apply the structural local sparse representation method to analyze the background region around the target. After that, we reduce the probability of prominent features in the background and add new information to the target model. In addition, a weighted search method is proposed to search the best candidate target region. To a certain extent, the weighted search method solves the local optimization problem. The proposed scheme, designed to track single human through complex scenarios from videos, has been tested on some video sequences. Several existing tracking methods are applied to the same videos and the corresponding results are compared. Experimental results show that the proposed tracking scheme demonstrates a very promising performance in terms of robustness to occlusions, appearance changes, and similar color distributed background.     

Digital provenance: Enabling secure data forensics in cloud computing

Secure provenance that records the ownership and process history of data objects is vital to the success of data forensics in cloud computing. In this paper, we propose a new secure provenance scheme based on group signature and attribute-based signature techniques. The proposed provenance scheme provides confidentiality on sensitive documents stored in a cloud, unforgeability of the provenance record, anonymous authentication to cloud servers, fine-grained access control on documents, and provenance tracking on disputed documents. Furthermore, it is assumed that the cloud server has huge computation capacity, while users are regarded as devices with low computation capability. Aiming at this, we show how to utilize the cloud server to outsource and decrease the user’s computational overhead during the process of provenance. With provable security techniques, we formally demonstrate the security of the proposed scheme under standard assumptions.     

Real-Time neural signal decoding on heterogeneous MPSocs based on VLIW ASIPs

An important research problem, at the basis of the development of embedded systems for neuroprosthetic applications, is the development of algorithms and platforms able to extract the patient’s motion intention by decoding the information encoded in neural signals. At the state of the art, no portable and reliable integrated solutions implementing such a decoding task have been identified. To this aim, in this paper, we investigate the possibility of using the MPSoC paradigm in this application domain. We perform a design space exploration that compares different custom MPSoC embedded architectures, implementing two versions of a on-line neural signal decoding algorithm, respectively targeting decoding of single and multiple acquisition channels. Each considered design points features a different application configuration, with a specific partitioning and mapping of parallel software tasks, executed on customized VLIW ASIP processing cores. Experimental results, obtained by means of FPGA-based prototyping and post-floorplanning power evaluation on a 40nm technology library, assess the performance and hardware-related costs of the considered configurations. The reported power figures demonstrate the usability of the MPSoC paradigm within the processing of bio-electrical signals and show the benefits achievable by the exploitation of the instruction-level parallelism within tasks.     

基于能量和信任的传感器网络行为分析

无线传感器集数据采集、处理和通信于一体,被广泛应用于军事、地震等应急通信领域。但安全问题是无线传感器网络的关键问题之一,介绍一种基于能量和信任的网络行为分析算法,可用于对网络入侵节点进行检测和控制,仿真实验结果表明该算法能快速有效检测节点入侵,对于提高传感器网络的安全可信能力具有重要的理论意义和应用价值。     

基于容错学习的属性基加密方案的具体安全性分析

为了能全面研究基于容错学习(LWE)的属性基加密(ABE)方案的安全性,考察其抵抗现有攻击手段的能力,在综合考虑格上算法和方案噪声扩张对参数的限制后,利用已有的解决LWE的算法及其可用程序模块,该文提出了针对基于LWE的ABE方案的具体安全性分析方法。该方法可以极快地给出满足方案限制要求的具体参数及方案达到的安全等级,此外,在给定安全等级的条件下,该方法可以给出相应的具体参数值。最后,利用该方法分析了4个典型的基于LWE的属性基加密方案的具体安全性。实验数据表明,满足一定安全等级的基于LWE的属性基方案的参数尺寸过大,还无法应用到实际中。     

基于异常分布导向的智能Fuzzing方法

现有主流智能Fuzzing测试一般通过对程序内部结构的精确分析构造新测试样本,因而严重依赖于当前计算机的性能,往往忽略了已发现的程序异常信息对新测试样本构造的指导意义。为了克服上述缺陷,该文提出一种基于异常分布导向的智能Fuzzing方法。该方法针对二进制程序测试,建立了TGM(Testcase Generation Model)样本构造模型:首先根据计算能力收集测试样本集的相关信息;然后随机选择初始测试样本进行测试;最后,基于测试结果初始化模型参数,根据模型优先选择更有效的输入属性构造新样本并进行新一轮测试,通过重复进行该步骤,在迭代测试中不断更新模型参数,用于指导下一轮新测试样本构造。实验数据表明该方法可以辅助Fuzzing选择更有效的样本优先进行测试,设计的原型工具CombFuzz在异常检测能力和代码覆盖能力上都有良好表现,同时,在对大型应用程序进行测试时,与微软SDL实验室的MiniFuzz测试器相比,在限定时间内平均异常发现率提高近18倍,并在WPS 2013等软件中发现了7个MiniFuzz无法发现的未公开可利用脆弱点。     

匿名通信中门限密码的应用研究

基于门限密码体制设计了具有较强匿名性和抗攻击的匿名通信方案。该方案在完成匿名通信合理选择路由的同时,也完成了接收方秘密份额的分配管理;经过匿名传送到接收方服务器的秘密份额将分步存储;在确认发送终端身份和数量时,由接收方服务器完成对其身份的恢复和统计。经过实验分析,该方案比传统的匿名通信协议提高了系统通信性能和抗攻击能力。     

一种面向应用系统的强制访问控制模型

为解决传统BLP模型不适用于应用系统的问题,提出了一种面向应用系统的强制访问控制（ASOMAC）模型,该模型对BLP模型进行了扩展,通过角色与安全标记的结合运用,实现了最小权限和职责分离原则,有效提高了强制访问控制的灵活性,使其符合应用系统的特点和需求。对模型进行了形式化定义,给出了一套公理系统,最后设计并分析了基于该模型的强制访问控制系统。