小块气藏早期动态特征综合评价

应用试井方法，提出一套比较切合实际的小块气藏动态特征综合评价方法，推导出水驱气藏水侵量的计算公式，编制了天然气高压物性参数计算和气藏稳产年限预测等程序软件。     

基于模态Petri网的行为有效区间寻找最优路径的方法

为满足客户需求,在行为约束下的业务流程中寻找行为执行的最优路径具有一定的实际意义。已有的研究是建立在静态分析基础上,通过优化算法或是行为分析来寻找最优执行路径,忽略了行为约束条件对执行行为有效性的影响,所得结果具有一定的局限性。文中在已有方法的基础上,利用Petri网行为轮廓序关系描述约束条件并确定行为有效区间,提出了基于模态Petri网分支有效区间的业务流程最优路径选择方法。该方法以行为有效区间替代已有的固定值方法,以便更好地描述业务流程的行为约束以及约束下的有效行为。通过一个具体的业务流程分析实例分析了该方法的有效性。     

基于EFPN的模糊离散事件系统可诊断性分析

针对模糊有限自动机及模糊Petri网在模糊离散事件系统(Fuzzy Discrete Event System,FDES)行为建模中的不足,提出一种扩展模糊Petri网(Extended Fuzzy Petri Net,EFPN),并基于EFPN构造了FDES行为模型及系统故障诊断器。EFPN以一种新的事件模型为基础对FDES的系统行为进行建模,并根据事件触发矩阵计算下一系统状态中各分量的可能性分布。与模糊有限自动机及模糊Petri网的对比分析表明,在描述FDES模糊事件时,对于同步距离为0的一组事件所造成的影响,EFPN的表达能力强于经典模糊Petri网;在对含有多个状态分量的FDES建模时,EFPN模型的规模远小于模糊有限自动机。在基于EFPN构造的系统行为模型中,运用可达状态标识图分析系统状态集,可有效地构造FDES的故障诊断器,并可据此进行系统可诊断性分析。     

基于生物加密的认证机制

为克服传统认证技术在保护安全和隐私方面的不足,提出了一种基于生物加密的身份认证模型。运用生物加密技术对用户脸部特征和密钥进行保护,防止非授权用户的访问和非授权资源的使用。实验结果表明,尽管人的面部表情变化多端,基于生物加密技术的认证系统仍能正确区分真正的用户与仿冒用户,起到很好的认证效果,保证了安全通信。     

PalmPhasor算法性能的理论分析

模板的安全性和隐私性是掌纹系统实际应用的关键问题,然而生物特征保护的多项指标通常相互冲突并且难以同时满足.作为解决上述冲突的一种可撤销掌纹编码算法,PalmPhasor实现了高效、安全的掌纹认证.建立了系统分析PalmPhasor性能的完整框架.为了便于具体分析,将情景分为4种情况,并且提供了支持相应分析的预备知识,包括辅助定理以及Gabor滤波掌纹图像实部和虚部分布特性.在统计学基础上建立的理论分析和实验结果均表明:即使在用户口令被盗的情况下,多方向分数级融合增强的PalmPhasor算法也可以同时有效地满足可撤销生物特征的4项指标.     

基于键盘行为数据的用户身份识别

用户击键行为作为一种生物特征,具有采集成本低、安全性高的特点。然而,现有的研究方法和实验环境都是基于实验室数据,并不适用于极度不平衡的真实数据。比如,在实验室数据上效果出色的分类算法在真实数据上却无法应用。针对此问题,提出了基于真实击键行为数据的用户识别算法。该方法将聚类算法和距离算法结合起来,通过比较新来的击键行为和历史击键行为相似度以实现用户识别。实验结果表明,该算法在100名用户的3015条真实击键记录组成的数据集上准确率达到88.22%,在投入实际应用后,随着样本集的增大算法的准确率还可以进一步提升。     

Biometrics:Standing Throughout Emerging Technologies

Biometrics technologies have been around for quite some time and many have been deployed for different applications all around the world, ranging from small companies' time and attendance systems to access control systems for nuclear facilities. Biometrics offer a reliable solution for the establishment of the distinctiveness of identity based on who an individual is, rather than what he or she knows or carries. Biometric Systems automatically verify a person's identity based on his/her anatomical and behav...     

四阶锁相频率合成器的环路参数设计及仿真

采用三阶环路滤波器的四阶频率合成器比三阶频率合成器能够更好的改善频率合成器的频谱杂散性能,但增加的极点会使得环路滤波器中电阻电容值的优化设计更为复杂.通过对系统的相位裕度、环路带宽、零极点频率等环路参数之间的关系,提出了一种无源环路滤波器优化设计的估算方法,并给出仿真流程.方法从相位裕度和环路带宽出发,通过指定零点和第二个非零极点所需要提供的参考毛刺的衰减程度来得出环路滤波器的各个原件值,简化了优化计算过程.     

A Proposed Biometric Authentication Model to Improve Cloud Systems Security

Most user authentication mechanisms of cloud systems depend on the credentials approach in which a user submits his/her identity through a username and password. Unfortunately, this approach has many security problems because personal data can be stolen or recognized by hackers. This paper aims to present a cloud-based biometric authentication model (CBioAM) for improving and securing cloud services. The research study presents the verification and identification processes of the proposed cloud-based biometric authentication system (CBioAS), where the biometric samples of users are saved in database servers and the authentication process is implemented without loss of the users’ information. The paper presents the performance evaluation of the proposed model in terms of three main characteristics including accuracy, sensitivity, and specificity. The research study introduces a novel algorithm called “Bio_Authen_as_a_Service” for implementing and evaluating the proposed model. The proposed system performs the biometric authentication process securely and preserves the privacy of user information. The experimental result was highly promising for securing cloud services using the proposed model. The experiments showed encouraging results with a performance average of 93.94%, an accuracy average of 96.15%, a sensitivity average of 87.69%, and a specificity average of 97.99%.     

Robust solutions to Stackelberg games: Addressing bounded rationality and limited observations in human cognition

How do we build algorithms for agent interactions with human adversaries? Stackelberg games are natural models for many important applications that involve human interaction, such as oligopolistic markets and security domains. In Stackelberg games, one player, the leader, commits to a strategy and the follower makes her decision with knowledge of the leader's commitment. Existing algorithms for Stackelberg games efficiently find optimal solutions (leader strategy), but they critically assume that the follower plays optimally. Unfortunately, in many applications, agents face human followers (adversaries) who — because of their bounded rationality and limited observation of the leader strategy — may deviate from their expected optimal response. In other words, human adversaries' decisions are biased due to their bounded rationality and limited observations. Not taking into account these likely deviations when dealing with human adversaries may cause an unacceptable degradation in the leader's reward, particularly in security applications where these algorithms have seen deployment. The objective of this paper therefore is to investigate how to build algorithms for agent interactions with human adversaries.To address this crucial problem, this paper introduces a new mixed-integer linear program (MILP) for Stackelberg games to consider human adversaries, incorporating: (i) novel anchoring theories on human perception of probability distributions and (ii) robustness approaches for MILPs to address human imprecision. Since this new approach considers human adversaries, traditional proofs of correctness or optimality are insufficient; instead, it is necessary to rely on empirical validation. To that end, this paper considers four settings based on real deployed security systems at Los Angeles International Airport (Pita et al., 2008 [35]), and compares 6 different approaches (three based on our new approach and three previous approaches), in 4 different observability conditions, involving 218 human subjects playing 2960 games in total. The final conclusion is that a model which incorporates both the ideas of robustness and anchoring achieves statistically significant higher rewards and also maintains equivalent or faster solution speeds compared to existing approaches.