This class discusses stealth malware techniques used on Windows. Rootkits are a type of stealth malware that try to hide their presence, and this class shows the data structures they manipulate to achieve this.
Rootkits are a class of malware which are dedicated to hiding the attacker’s presence on a compromised system. This class will focus on understanding how rootkits work, and what tools can be used to help find them.
This will be a very hands-on class where we talk about specific techniques which rootkits use, and then do labs where we show how a proof of concept rootkit is able to hide things from a defender. Example techniques include
•Import Address Table (IAT) hooking
•System Call Table/System Service Descriptor Table (SSDT) hooking
•Interrupt Descriptor Table (IDT) hooking
•Direct Kernel Object Manipulation (DKOM)
•Kernel Object Hooking (KOH)
•IO Request Packet (IRP) filtering
•Hiding files/processes/open ports
•Compromising the Master Boot Record (MBR) to install a “bootkit”
The class will help the student learn which tools to use to look for rootkits on Windows systems, how to evaluate the breadth of a tool’s detection capabilities, and how to interpret tool results.
This class is structured so that students are given a homework to detect rootkits *before* they have taken the class. This homework is given in the context of the following scenario:
“You, being the only ‘security person’ in the area, have been called in to
examine a running Windows server because "it's acting funny." They don't
care that you like Mac/Linux/BSD/Plan9 better, you need to look at it! You
are solemnly informed that this is system is mission critical and can only
be rebooted if absolutely necessary. You must investigate whether any sort
of compromise has taken place on the system, with minimal impact to the
mission. What do you do? What DO you DO?”
The homework is then for the student to use any means at their disposal to write up answers to the following questions: “What malicious changes were made to the system?”, “What tools did you use to detect the changes?”, “How can you remove the changes?”. The students’ answers are then anonymized and shared with the rest of the class afterwards, so that they can see how others approached the problem, and learn from their techniques. The anonymization of the homework before distribution is important so that students know that even though they don’t know, and aren’t expected to know, anything about the area yet, their entry will not be judged by other students.
Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.
A free online course for primary and secondary school teachers who are tackling the Computing curriculum in England. This free online course aims to help teachers in primary and secondary schools, especially those who previously taught other subjects including ICT. It was originally created by UEA with sponsorship from Computing at School (CAS) and BT. CAS have asked the National STEM Learning Centre to host a fourth run of this successful course.
This course introduces the basics of Digital Signal Processing and computational acoustics, motivated by the vibrational physics of real-world objects and systems. We will build from a simple mass-spring and pendulum to demonstrate oscillation, how to simulate those systems in the computer, and also prove that simple oscillation behaves as a sine wave. From that we move to plucked strings and struck bars, showing both solutions as combined traveling waves and combined sine wave harmonics.
This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera.
O curso apresenta uma introdução aos processadores multicore de uma forma acessível, sem que haja a necessidade de conhecimentos prévios na área de ciência da computação. A partir desta introdução serão feitas relações com outras áreas da computação, de forma a despertar o interesse do aluno para os diferentes cursos oferecidos pela Faculdade de Informática da PUCRS.
The impact of technology and networks on our lives, culture, and society continues to increase. The very fact that you can take this course from anywhere in the world requires a technological infrastructure that was designed, engineered, and built over the past sixty years. To function in an information-centric world, we need to understand the workings of network technology. This course will open up the Internet and show you how it was created, who created it and how it works. Along the way we will meet many of the innovators who developed the Internet and Web technologies that we use today.
This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple. These applications will involve windows whose contents are graphical and respond to buttons, the keyboard and the mouse.
A computer science principles course for anyone who wants to learn how to translate ideas into code. Discover the big ideas and thinking practices in computer science plus learn how to code using one of the friendliest programming languages, Snap! (based on Scratch).
This two-part course builds upon the programming skills that you learned in our Introduction to Interactive Programming in Python course. We will augment those skills with both important programming practices and critical mathematical problem solving skills. These skills underlie larger scale computational problem solving and programming.