The 2007 International Capture The Flag in UCSB

iCTF竞赛介绍
iCTF是一项分布式的大型安全竞赛,旨在从攻击和防御的角度测试参赛者的安全技能。比赛采取多地点、多队伍的形式,各队伍独立对抗。每支队伍会获得一个虚拟化的网络安装环境,比如Linux或Windows主机,这些主机提供多种服务并包含未知漏洞。参赛队伍的目标是在比赛中保持服务可用且不受损害,同时尝试攻破其他队伍的服务。

The UCSB International Capture The Flag (also known as the iCTF) is a distributed, wide-area security exercise, whose goal is to test the security skills of the participants from both the attack and defense viewpoints.

The Capture The Flag contest is a multi-site, multi-team hacking contest in which a number of teams compete independently against each other.

Each team is given a virtualized network installation (for example, a Linux host and/or a Windows host). The hosts provide a number of services. The services have a number of undisclosed vulnerabilities, which have been included in the servers' software by the contest organizers.

The goal of each team is to maintain the set of services available and uncompromised throughout the contest phase. Each team can (and should) attempt to compromise other teams' services. Since all the teams receive an identical copy of the virtual network, the task of each team is to find vulnerabilities in their copy of the hosts and possibly fix the vulnerabilities without disrupting the services. At the same time, the teams have to leverage their knowledge about the vulnerabilities they found to compromise the servers run by other teams. Compromising a service will allow a team to bypass the service's security mechanisms and to "capture the flag" associated with the service.

During the contest a scoring system keeps track, for each team, of which services are available, and which services have been compromised.

The 2007 iCTF is scheduled Friday, December 7, 2007, from 8am to 5pm, PST.

more at: http://www.cs.ucsb.edu/~vigna/CTF/
MATLAB主动噪声和振动控制算法——对较大的次级路径变化具有鲁棒性内容概要:本文主要介绍了一种在MATLAB环境下实现的主动噪声和振动控制算法,该算法针对较大的次级路径变化具有较强的鲁棒性。文中详细阐述了算法的设计原理与实现方法,重点解决了传统控制系统中因次级路径动态变化导致性能下降的问题。通过引入自适应机制和鲁棒控制策略,提升了系统在复杂环境下的稳定性和控制精度,适用于需要高精度噪声与振动抑制的实际工程场景。此外,文档还列举了多个MATLAB仿真实例及相关科研技术服务内容,涵盖信号处理、智能优化、机器学习等多个交叉领域。; 适合人群:具备一定MATLAB编程基础和控制系统理论知识的科研人员及工程技术人员,尤其适合从事噪声与振动控制、信号处理、自动化等相关领域的研究生和工程师。; 使用场景及目标:①应用于汽车、航空航天、精密仪器等对噪声和振动敏感的工业领域;②用于提升现有主动控制系统对参数变化的适应能力;③为相关科研项目提供算法验证与仿真平台支持; 阅读建议:建议读者结合提供的MATLAB代码进行仿真实验,深入理解算法在不同次级路径条件下的响应特性,并可通过调整控制参数进一步探究其鲁棒性边界。同时可参考文档中列出的相关技术案例拓展应用场景。
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