Please review all events below for early registration as events are arranged by closest upcoming date!
Can You Crack the Code? 4th annual Codebreaker Challenge
Date/Time: The challenge will begin on 9 Sep 2016 at 9 pm ET and ends 31 Dec 2016 at midnight.
Register: Students should register on the site using their .edu email addresses. The challenge will be hosted at https://codebreaker.Ltsnet.net
Contact: For support or questions, send email to firstname.lastname@example.org
This Fall, NSA is launching its 4th annual Codebreaker Challenge. It is a hands-on software reverse engineering challenge where students work to complete mission-focused objectives to push their school to the top of the competition leaderboard. The theme for this year's challenge is "countering Improvised Explosive Devices (IEDs)". Students are given six tasks of increasing difficulty that culminate in developing the capability to permanently disable fictional IED software in a fictional scenario. Feedback from previous challenges indicated students learned a great deal from participating, so with your help, we encourage as much student participation as possible! Here are the pertinent details:
-Small tokens of recognition will be awarded to the first 50 students that complete the challenge nation-wide. In the past, some universities chose to offer additional incentives (extra-credit in a relevant course, an award for the first students to solve the challenge within a department, etc.) We encourage your department to do this if possible! -Links to software reverse engineering lectures and other educational material can be found on the site.
We hope to have several virtual tech talks over the course of the semester where we will provide an overview of the 2016 challenge, present reverse engineering techniques, and walk through the solution to the challenge from last year. We will also answer questions students may have about the challenge. The dates and times of these tech talks will be made available on the challenge site.
CAE Tech Talk: Double Header
Date/Time: 20 Oct 2016. Multimedia Forensics - Using Mathematics and Machine Learning to Determine and Image's Source and Authenticity (1:10-1:50 pm ET) and Towards Automatic Extraction, Synthesis, and Prediction of Cyber Attack Scenarios (2:00-2:40 pm ET)
Location:https://capitol.adobeconnect.com/cae_tech_talk/ Just log in as “Guest” and enter your name. No password required.
Contact: For questions on CAE Tech Talk, please send email to CAETechTalk@nsa.gov
Mark your calendars and come join your friends in the CAE community for a Tech Talk. We are a warm group that shares technical knowledge. CAE Tech Talks are free and conducted live in real-time over the Internet, so no travel is required. You can attend from just about anywhere (office, home, etc.) Capitol Technology University (CTU) hosts the presentations using their online delivery platform (Adobe Connect) which employs slides, VOIP, and chat for live interaction. Just log in as “Guest” and enjoy the presentation(s).
CAE Tech Talks are also recorded. CTU will post a recording of the live presentations on its website: https://capitol.instructure.com/courses/510/external_tools/66
Below is a description of the presentation(s) and logistics of attendance:
Multimedia Forensics - Using Mathematics and Machine Learning to Determine and Image's Source and Authenticity
Time: 1:10-1:50 pm ET
Audience Skill Level: All Levels
Presenter: Dr. Matt Stamm (Drexel University)
Digital images play a critical role in today's society. They are frequently used by news agencies during reporting, as evidence during criminal investigations, and as intelligence in many military and defense scenarios. This proves problematic since an information attacker can easily create perceptually realistic forgeries using editing tools such as Adobe Photoshop.
In this talk, I will discuss several multimedia forensic algorithms capable of determining if an image has been manipulated that we have developed at the Multimedia and Information Security Lab (MISL) here at Drexel. Instead of relying on extrinsic security measures such as cryptography, these techniques identify image manipulations and forgeries by exploiting the intrinsic fingerprints left in digital media by editing operations. Additionally, I will discuss how multimedia forensic techniques can determine the source of an image by utilizing traces left in an image by its source camera instead of unreliable or easily falsifiable information sources such as metadata.
Towards Automatic Extraction, Synthesis, and Prediction of Cyber Attack Scenarios
Time: 2:00-2:40 pm ET
Audience Skill Level: All Levels
Presenter: Dr. Jay Yang (Rochester Institute of Technology)
Cyber attacks to enterprise networks have moved into an era where both attackers and security analysts utilize complex strategies to confuse and mislead one another. Critical attacks often take multitudes of reconnaissance, exploitations, and obfuscation techniques to achieve the goal of cyber espionage and/or sabotage. The discovery and detection of new exploits, though needing continuous efforts, is no longer sufficient. This talk will discuss some of the recent research efforts that build upon and beyond the conventional intrusion detection systems. Specifically, we will present our approaches on learning and predicting attack patterns based on IDS alerts, extracting emerging attack behaviors using semi- supervised learning, modeling and analyzing attack obfuscation, and simulating cyber attack scenarios for diverse attack behaviors and network configurations. This collection of works aims at automatically recognizing and synthesizing models to represent how cyber attacks may transpire in well protected enterprise networks.