Johns Hopkins University

Intrusion Detection 专项课程

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Johns Hopkins University

Intrusion Detection 专项课程

Master Intrusion Detection for Cybersecurity.

Gain expertise in intrusion detection systems and advanced network analysis to effectively respond to cybersecurity threats.

Jason Crossland

位教师:Jason Crossland

包含在 Coursera Plus

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来自此计划中课程的 5 条评论

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4 月 完成
在 13 小时 一周
灵活的计划
自行安排学习进度
深入学习学科知识

来自此计划中课程的 5 条评论

中级 等级

推荐体验

4 月 完成
在 13 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Explore the principles of intrusion detection systems and their role in enhancing cybersecurity defenses across various environments.

  • Gain hands-on experience with machine learning techniques to improve threat detection and incident response strategies in networks.

  • Develop a comprehensive understanding of Tor networking and its implications for privacy, security, and intrusion detection.

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授课语言:英语(English)

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  • 培养对关键概念的深入理解
  • 通过 Johns Hopkins University 获得职业证书

专业化 - 3门课程系列

您将学到什么

  • Understand the roles of HIDS and NIDS, their key components, and applications across cybersecurity contexts.

  • Install and configure IDS solutions on VMs to detect real-time threats in host and network environments.

  • Compare signature-based and anomaly-based detection methods and configure IDS rules accordingly.

  • Use quantitative techniques to assess IDS effectiveness, analyzing data to select optimal solutions for security needs.

您将获得的技能

类别:Intrusion Detection and Prevention
类别:Anomaly Detection
类别:Network Security
类别:System Monitoring
类别:Network Analysis
类别:Network Monitoring
类别:Continuous Monitoring
类别:Event Monitoring
类别:Virtual Machines
类别:Threat Detection
类别:Threat Management
类别:Endpoint Detection and Response
类别:Distributed Denial-Of-Service (DDoS) Attacks

您将学到什么

  • Understand the differences between network situational awareness and traditional NIDS for effective incident detection.

  • Gain proficiency in using GOTS and COTS tools for network packet analysis and troubleshooting networking challenges.

  • Learn to conduct ROC analysis on IDS data and interpret event graphs and precision-recall metrics for better decision-making.

  • Explore the NIST Cybersecurity Framework and SANS Incident Response Cycle to effectively manage and respond to cyber incidents.

您将获得的技能

类别:Incident Response
类别:Anomaly Detection
类别:Intrusion Detection and Prevention
类别:Network Analysis
类别:Network Protocols
类别:AI Security
类别:Network Security
类别:Network Monitoring
类别:Security Management
类别:Cloud Security
类别:NIST 800-53
类别:Cyber Threat Hunting
类别:Cyber Security Policies
类别:Computer Security Incident Management
类别:Threat Detection
类别:Cyber Security Strategy
类别:Cybersecurity

您将学到什么

  • Explore advanced machine learning techniques, including neural networks and clustering, for improved threat detection in cybersecurity.

  • Understand the integration of machine learning algorithms into Intrusion Detection Systems (IDS) for enhanced security measures.

  • Gain knowledge of The Onion Router (ToR) architecture and its applications, focusing on privacy and anonymous communication.

  • Learn to utilize Security Onion tools for effective incident response within high-volume enterprise environments, enhancing cybersecurity strategy.

您将获得的技能

类别:Intrusion Detection and Prevention
类别:Machine Learning
类别:Applied Machine Learning
类别:Anomaly Detection
类别:Unsupervised Learning
类别:Supervised Learning
类别:Threat Detection
类别:Cybersecurity
类别:Artificial Neural Networks
类别:Model Evaluation
类别:Network Security
类别:Computer Security Incident Management

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位教师

Jason Crossland
Johns Hopkins University
9 门课程 6,020 名学生

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