加密不足以确保通信安全,因为通信存在这一简单事实通常足以引起怀疑并采取进一步行动。 隐蔽通道旨在通过使用通常不打算使用的通信方式来隐藏通信的真实存在。 Covert Channels Evaluation Framework (CCHEF) 是一个灵活的软件框架,用于根据经验评估网络隐写术方法或网络协议中的隐蔽通道。 CCHEF 可用于具有真正公开流量的真实网络(例如在研究测试平台中),但也可以使用来自跟踪文件的公开流量(例如在单个主机上进行评估)来模拟隐蔽通道。 CCHEF 旨在评估隐蔽渠道,而不是(错误地)将它们用于实际的隐蔽通信。 CCHEF 的发送方或接收方是正常的用户空间应用程序,没有任何伪装,不包含任何类似恶意软件的代码,例如它们不会非法获取超级用户权限等。
2021-09-08 15:50:51 642KB 开源软件
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基于QCC51XX平台的Sony的LDAC算法移植指引
2021-08-28 09:14:28 297KB LDAC QCC51XX 高通
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Evaluation of Open-Source IDE Plugins for Detecting Security Vulnerabilities
2021-08-21 13:01:22 450KB 互联网
Intel USB4 Evaluation Dock BKC Files Installer Version WW19021 Test Tool
2021-08-12 09:13:00 1.08MB usb 资源达人分享计划
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计算机体系结构性能评估方法,书籍。 Performance evaluation is at the foundation of computer architecture research and development. Contemporary microprocessors are so complex that architects cannot design systems based on in- tuition and simple models only. Adequate performance evaluation methods are absolutely crucial to steer the research and development process in the right direction. However, rigorous performance evaluation is non-trivial as there are multiple aspects to performance evaluation, such as picking workloads, selecting an appropriate modeling or simulation approach, running the model and interpreting the results using meaningful metrics....
2021-08-06 06:49:31 2.43MB 体系结构 研究方法 评估方法 组成原理
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此为用pysot里面的vot功能DIMP50要用到的修改后的tracker.py文件
2021-07-25 17:44:40 29KB python
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TC358870XBG的开发板原理图,可以用于硬件设计参考,Cadence的PDF版本。 TC358870XBG_Evaluation Board(评估板原理图).pdf
2021-07-24 21:27:01 175KB TC358870XBG 原理图 Demo
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C程序,4个评价集,6个评价因子,模糊综合评判算法,
2021-07-20 08:06:00 1KB fuzzy evaluation ;algorithm
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In this tutorial, we provide principled methods to quantitatively evaluate the quality of an estimated trajectory from visual(-inertial) odometry (VO/VIO), which is the foundation of benchmarking the accuracy of different algorithms. First, we show how to determine the transformation type to use in trajectory alignment based on the specific sensing modality (i.e., monocular, stereo and visual-inertial). Second, we describe commonly used error metrics (i.e., the absolute trajectory error and the relative error) and their strengths and weaknesses. To make the methodology presented for VO/VIO applicable to other setups, we also generalize our formulation to any given sensing modality. To facilitate the reproducibility of related research, we publicly release our implementation of the methods described in this tutorial.
2021-07-19 11:01:21 506KB slam
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PCAP01评估板英文数据手册,关于这颗物料的资料少的可怜,这次为了开发终于找全了,可以看我的详细的资源列表。
2021-07-09 09:07:45 2.68MB 数据手册
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