标准模型下群签名的批验证协议*

首次对标准模型下群签名的批验证协议进行了研究。利用小指数测试技术和双线性对映射的特殊性质,为目前效率较高的两个群签名方案按照多人签署相同消息和不同消息这两种情况,分别设计了相应的批验证协议。相较于单独验证,认证效率大大提高。     

悬挂式重力补偿系统精密跟踪方法

介绍了一种用于研究空间机器人微重力条件下的工作特性的悬挂系统——悬挂式重力补偿系统,并给出了悬挂模块的动力学模型.通过数值求解与仿真,运用非线性规化求出了一定条件下的最优控制参数;用正交试验寻优、基于时间最优控制的试凑法证明了优化模型的解正确性.该研究为空间机器人地面试验系统模拟微重力环境下精密跟踪运动提供了最优控制方法.     

多总线接口信号处理SoC虚拟验证平台的实现

多总线接口信号处理SoC芯片是以信号处理DSP为核心集成了多个总线接口的片上系统,该SoC涉及的总线协议众多,验证复杂、工作量大,验证将是该SoC芯片开发的瓶颈。为了缩短多总线接口信号处理SoC芯片的开发周期,提高该SoC芯片的一次流片成功率,必须采用更为可靠和有效的验证方案。以SoC验证流程及方法为指导,重点介绍了多总线接口信号处理SoC虚拟验证平台的构建和具体实施。验证结果表明,该验证平台能高效、全面验证芯片功能,提高了芯片验证效率,缩短了整个芯片开发周期,为芯片的成功投片提供了可靠保障。     

恒压供水系统的调试及验证

介绍恒压供水系统的调试及验证.     

基于安全协议代码的形式化辅助建模研究

随着安全协议形式化分析技术的不断发展,利用工具自动验证虽已得到实现,但建模环节仍需依赖专业人员手工建模,难度大且成本高,限制了此技术的进一步推广。为了提高建模的自动化程度,提出了依据安全协议代码进行形式化模型辅助生成的方案。首先,使用污点分析获取协议的通信流程,并且记录密码学原语操作;然后,根据通信流程之间的序列关系构建协议通信状态机;最终,根据目前主流的安全协议形式化分析工具Tamarin的模型语法生成形式化模型。实验结果表明,此方案可以生成形式化模型中的关键部分,提高了形式化建模的自动化程度,为形式化分析技术的推广作出贡献。     

高性能MCU的FPGA原型验证系统研究与平台实现

本文研究并实现了一种基于Cortex-A7核的高性能MCU在FPGA原型阶段的验证平台。该设计研究可以针对高性能MCU芯片或其FPGA原型验证阶段的软硬件验证环境快速搭建,通过交互式、软硬件协同的方式对MCU芯片各个模块功能进行实时、可靠的功能验证。高效的FPGA原型验证可以提高MCU研发速度、缩短验证时间、提高验证效率、及时发现芯片设计的缺陷、缩短芯片研发周期。     

A multimodal-Siamese Neural Network (mSNN) for person verification using signatures and EEG

Signatures have long been considered to be one of the most accepted and practical means of user verification, despite being vulnerable to skilled forgers. In contrast, EEG signals have more recently been shown to be more difficult to replicate, and to provide better biometric information in response to known a stimulus. In this paper, we propose combining these two biometric traits using a multimodal Siamese Neural Network (mSNN) for improved user verification. The proposed mSNN network learns discriminative temporal and spatial features from the EEG signals using an EEG encoder and from the offline signatures using an image encoder. Features of the two encoders are fused into a common feature space for further processing. A Siamese network then employs a distance metric based on the similarity and dissimilarity of the input features to produce the verification results. The proposed model is evaluated on a dataset of 70 users, comprised of 1400 unique samples. The novel mSNN model achieves a 98.57% classification accuracy with a 99.29% True Positive Rate (TPR) and False Acceptance Rate (FAR) of 2.14%, outperforming the current state-of-the-art by 12.86% (in absolute terms). This proposed network architecture may also be applicable to the fusion of other neurological data sources to build robust biometric verification or diagnostic systems with limited data size.     

一种基于产生式的流程模型分析方法*

在深入分析业务流程模型和合理的抽象业务活动基础上,提出了一种基于产生式的流程模型形式化分析方法,并提供了一种从一般流程描述到该模型的转换方法;在此基础上,推导了一系列行之有效的流程属性验证规则,并通过应用实际例子证明了所提出方法的有效性。     

Ongoing verification of a multiphysics community code: FLASH

When developing a complex, multi‐authored code, daily testing on multiple platforms and under a variety of conditions is essential. It is therefore necessary to have a regression test suite that is easily administered and configured, as well as a way to easily view and interpret the test suite results. We describe the methodology for verification of FLASH, a highly capable multiphysics scientific application code with a wide user base. The methodology uses a combination of unit and regression tests and an in‐house testing software that is optimized for operation under limited resources. Although our practical implementations do not always comply with theoretical regression‐testing research, our methodology provides a comprehensive verification of a large scientific code under resource constraints.Copyright © 2013 John Wiley & Sons, Ltd.     

基于SystemVerilog可重用测试平台的实现

对于中小型设计,传统的验证效率低、可重用性差,而基于方法学的高级验证测试平台搭建较繁琐,验证流程不太灵活。以ARINC429收发器IP核为验证对象,采用System Verilog语言,通过层次化设计,改善工程组织架构,运用虚接口与回调等关键技术,实现了一种可重用测试平台。将不同的测试案例在测试平台上运行,结合断言与覆盖率驱动等验证技术完成了对ARINC429收发器IP核的功能验证,代码覆盖率和功能覆盖率均达到100%。实践表明,该测试平台具有良好的可重用性、易操作性,验证效率较高。