Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Will I earn university credit for completing the Specialization?

This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

Intrusion Detection 专项课程

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.

位教师：Jason Crossland

包含在 Coursera Plus 中

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3 门课程系列

深入学习学科知识

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

3 门课程系列

深入学习学科知识

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.

要了解的详细信息

可分享的证书

添加到您的领英档案

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

精进特定领域的专业知识

向大学和行业专家学习热门技能
借助实践项目精通一门科目或一个工具
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

The specialization "Intrusion Detection" is designed for postgraduate students seeking to enhance their expertise in cybersecurity with a focus on intrusion detection and incident response. Through three comprehensive courses, you will delve into the essential principles and advanced techniques necessary for effectively safeguarding networks and systems against cyber threats.

In the first course, "Introduction to Intrusion Detection Systems (IDS)," you'll learn the foundational concepts of IDS, including how to identify and respond to security incidents. The second course, "Advanced Network Analysis and Incident Response," builds on this knowledge by exploring sophisticated network analysis techniques and incident response strategies, enabling you to handle complex security challenges. The final course, "Machine Learning and Emerging Technologies in Cybersecurity," emphasizes the integration of machine learning techniques within cybersecurity frameworks, equipping you with cutting-edge skills in threat detection and prevention.

By completing this Specialization, you will be well-prepared to take on roles in cybersecurity, focusing on protecting organizations from evolving threats and ensuring robust security measures.

应用的学习项目

In this specialization on Intrusion Detection, learners will engage in hands-on projects that delve into the principles of anomaly detection and the application of machine learning techniques in cybersecurity. One key project involves completing a problem set that challenges learners to analyze a dataset using defined parameters, including bias, weights, and an activation threshold. Participants will interpret data points to classify network behavior accurately, honing their skills in critical thinking and technical analysis. Additionally, learners will explore various intrusion detection methods, gaining practical experience with tools and techniques essential for identifying and mitigating threats in real-world environments. This project emphasizes practical problem-solving while critically assessing the effectiveness and limitations of different intrusion detection strategies.

Introduction to Intrusion Detection Systems (IDS)

第 1 门课程51小时

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：Network Analysis

类别：Network Monitoring

类别：Continuous Monitoring

类别：Event Monitoring

类别：System Monitoring

类别：Virtual Machines

类别：Endpoint Detection and Response

类别：Threat Detection

类别：Threat Management

类别：Distributed Denial-Of-Service (DDoS) Attacks

Advanced Network Analysis and Incident Response

第 2 门课程46小时

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 Security

类别：Cloud Security

类别：Network Monitoring

类别：Cyber Security Strategy

类别：Threat Detection

类别：Computer Security Incident Management

类别：NIST 800-53

类别：Cyber Threat Intelligence

Machine Learning and Emerging Technologies in Cybersecurity

第 3 门课程39小时

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：Applied Machine Learning

类别：Machine Learning Algorithms

类别：Machine Learning

类别：Supervised Learning

类别：Artificial Neural Networks

类别：Network Security

类别：Threat Detection

类别：Computer Security Incident Management

类别：Cybersecurity

类别：Unsupervised Learning

类别：Machine Learning Software

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Jason Crossland

Johns Hopkins University

9 门课程4,544 名学生

提供方

Johns Hopkins University

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自 2020开始学习的学生

''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

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常见问题

The specialization is designed to be completed at your own pace, but on average, it is expected to take approximately 3 months to finish if you dedicate around 5 hours per week. However, as it is self-paced, you have the flexibility to adjust your learning schedule based on your availability and progress.

You are encouraged to take the courses in the recommended sequence to ensure a smoother learning experience, as each course builds on the knowledge and skills developed in the previous ones. However, you are not required to follow a specific order, and you can take the courses in the order that best suits your needs and prior knowledge.

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.