Description: 此工程主要用于在任一网段内扫描存活主机及其当前活动端口，便于进一步入侵和探测。-This project is mainly used in any one network segment scanning host survival and their current activities, port, facilitate further intrusion and detection.
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Size: 7328768 |
Author:liu tian |
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Description: IDS入侵检测系统的安装和部署，一款用于Windows平台下的软件。-Snort® is an open source network intrusion prevention and detection system (IDS/IPS) developed by Sourcefire. Platform: |
Size: 693248 |
Author:gram |
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Description: 网络对抗课程实验，宏病毒的入侵和检测，包括截图及说明-Network the confrontation course experiments, intrusion and detection of macro viruses, including screenshots and instructions Platform: |
Size: 491520 |
Author:钟圣唯 |
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Description: 这是一个地沟电缆防盗报警系统检测单元的汇编程序，主要是检测是否有断线事件、入侵事件，若没有就发送正常标志。-This is a trench cable assembler burglar alarm system detection unit, mainly to detect whether there is disconnection event, intrusion events, if not it sends a normal flag. Platform: |
Size: 6144 |
Author:John LONG |
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Description: 该程序是我多年的经验总结以及代码，实现了全景目标跟踪、火焰识别、烟雾识别、起立坐下行为判断、越界闯入、徘徊、违规停车等多种智能功能一体化，粒子滤波、贝叶斯分类器、随机森林等多种在线学习机制，还有传统的camshift、meanshift、光流法、卡尔曼滤波、struck、KCF、TLD、CT、区域匹配，相位相关、轮廓跟踪等多种算法-The program is my many years of experience and code, the realization of the panorama target tracking, flame detection, smoke detection, standing up sitting judge, cross-border intrusion, wandering, illegal parking and other various intelligent functions integration, particle filter, Bayesian classifier, random forest variety of online learning mechanism, and the traditional CAMSHIFT, meanshift, optical flow method, Kalman filter, the, KCF, regional matching, phase correlation, contour tracking and other several algorithms Platform: |
Size: 5217280 |
Author:王东 |
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Description: The cybersecurity community is slowly leveraging machine learning (ML) to
combat ever-evolving threats. One of the biggest drivers for the successful
adoption of these models is how well domain experts and users can under
stand and trust their functionality. Most models are perceived as a black box
despite the growing popularity of machine learning models in cybersecurity
applications (e.g., an intrusion detection system (IDS)). As these black-
box models are employed to make meaningful predictions, the stakeholders’
demand for transparency and explainability increases. Explanations support
ing the output of ML models are crucial in cybersecurity, where experts
require far more information from the model than a simple binary output for
their analysis. Platform: |
Size: 28830371 |
Author:iqzer0 |
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