To Stop Hackers, Learn to Think Like a Hacker

In February 2018, the largest distributed-denial-of-service (DDoS) attack ever recorded affected GitHub, a repository of code and programming knowledge. The following week in early March that record was broken by another DDoS attack. A similar incident recorded by Amazon Web Services in February 2020 broke that record.

It’s not just the scale of threats that cybersecurity professionals today must deal with, but also the complexity. Over the past decade, the information security community has seen a rise in advanced persistent threats (APTs) — attacks that take place over a long period of time because the attacker is focused on collecting sensitive data for the duration of months and even years. These attacks utilize a mixture of hacking, malware, social engineering and other tactics to gain increased levels of access to sensitive systems; in 2019, multiple APTs were discovered targeting government organizations, consumers and businesses alike.

The online Master of Engineering in Cybersecurity Analytics program prepares graduates to step to the forefront of cybersecurity and mitigate the damage caused by incidents like these, as well as classify attacks which experts have yet to identify.

A Cybersecurity Curriculum for Problem Solvers

The online master’s in cybersecurity analytics offers practical experience using cybersecurity and analytics tools to identify and mitigate damage from an array of cyberthreats. The curriculum comprehensively covers traditional methods for intrusion detection and assessing information security risks, while also canvassing new approaches such as semantic analysis of open-source intelligence (e.g., social media).

Some of the key areas covered in the curriculum include:

  • Cyber forensics
  • Network defense
  • Cloud computing security
  • Auditing and intrusion detection
  • Applied cyber data analytics
  • Hardware and software security
  • Security data visualization

The program is designed to establish the foundational technical skills necessary to excel in a cybersecurity career; therefore it is made accessible to individuals who are interested in entering the field. At the same time, experienced professionals will benefit from the opportunity to network with GW’s experienced faculty, share their knowledge with one another and further refine their expertise through practical exercises.

Program Learning Objectives

The cybersecurity analytics master’s degree program equips graduates with a blend of technical and business skills to utilize for identifying cybersecurity problems and creating realistic business solutions. The coursework integrates real-world use cases and practical exercises with learning materials designed to give students experience using information security tools and techniques, while preparing them to excel in a variety of cybersecurity careers, including analyst and managerial information security roles.

For example, some coursework requires students to analyze an organization’s response to a cybersecurity incident and identify what technical and business process solutions could have been implemented to mitigate the damage caused.

The following learning objectives outline the design and structure of the program:

  • Lead organizations in cybersecurity, data analytics and forensics
  • Conduct vulnerability assessment of network applications and operating systems
  • Master fundamentals in upcoming issues in hardware security and address system security holistically
  • Become proficient in developing resilient and defendable networks and emerging IT systems
  • Identify and defend against emergent and advanced persistent threats
  • Demonstrate technological proficiency in secure system/hardware design and cyber resilience
  • Understand the key security components of cloud computing