SECURE IT Academy
SECURE IT Academy
The Iribe Initiative for Inclusion and Diversity at the University of Maryland, College Park, and North Carolina State University is pleased to offer a Cybersecurity Summer Academy experience at both institutions.
About
SECURE IT is a one-week-long, non-residential Cybersecurity summer academy held at the University of Maryland-College Park, and at North Carolina State University. The camp will be offered to rising 6th, 7th, and 8th graders. Students will Master the Realm of Cybersecurity: In an age where digital threats abound, become a defender of the virtual realm. Learn the strategies and techniques to defeat cyber attacks, secure networks, and protect sensitive data. Delve into ethical hacking, encryption, and cybersecurity careers.
We are proud to present our SECURE IT Cybersecurity workshops series for middle schoolers to learn to think like a cyber detective and employ design thinking to protect the things that they interact with daily (smart technologies, wearables, internet sites). During this workshop, students will use creative problem-solving to design, code, and protect various systems designed to help people across many fields.
SECURE IT Cybersecurity workshops are free private workshops hosted in person for rising 6th,7th, and 8th graders. Each student will attend once a month during the school year, and will present their project at Maryland Day this April 2024! Register for Fall 2023 workshops here: https://umdsurvey.umd.
Typical Camp Day
- 9:00-12:00 pm Classroom Instruction
12:15-1:15 pm Lunch
1:30-3:45 pm Classroom Instruction
3:45-4:00 pm Dismissal
*Field trips and guest speakers are scheduled during Classroom Instruction time blocks.
Typical Workshop Day
12:00 pm-2:00 pm Classroom Instruction
*Students will work on their projects during Classroom Instruction time blocks*
Cybersecurity Education
- K-12 Cybersecurity education curriculum instruction by current UMD undergrad or graduate students
- Guest Speakers by UMD professors and cybersecurity industry professionals
- Field trip to cybersecurity industry leaders where students are introduced to people, topics, and career opportunities while exploring the facility
Personal Growth
- Small group presentations with peers
- Sharpen cyber skills and interactions with day-to-day technology
- Social activities with peers
Hands-on Experience
- Small-group research projects led by current undergraduate or graduate students; projects are security focused
- Group presentations showcasing work at the end of the program
Applications for Summer 2024 will open January 2024!
Target Participants: Rising 6th - 8th Graders
- Date: TBA
- Cost: $450
- Applicant must be able to attend the full week.
- Applicant must be a rising 6th, 7th, or 8th grader.
- Applicant will be required to submit family and student information.
- Financial Assistance is available for those with displayed need by completing our Scholarship Application.
- Must submit academic transcripts (unofficial transcripts are welcome for application review).
- Email addresses must be provided for teacher recommendation section of the application, this is required.
Dates & Links
Program Date and Quick Info
Dates: TBD
1-week nonresidential program experience
Target Student: Rising 6th, 7th, and 8th graders (focus on the DC, MD, and VA areas)
2024 I4C Summer Academy applications will be live in January!
Scholarships
Scholarship Applications for Summer 2024 will open in February 2024
Need-based scholarships are available for eligible students living in D.C., Virginia, and Maryland
2023-2024 Fall Cybersecurity Workshops are live now!
Register for workshops here: https://umdsurvey.umd.
Secure Software Supply Chain Center
S3C2
Explore our Secure Software Supply Chain Center Website to learn about our projects, research, and more.
Generative Adversarial Networks (GANs) is a modern machine learning technique to produce realistic but fake samples. GANs have two AI components, often modeled as deep neural networks, that play a zero-sum game to improve each other’s performance.
Learning a probability model from data is a key challenge in machine learning and statistics. A classical approach to this problem is to fit (approximately) an explicit probability model to the training data via a maximum likelihood estimation. However, there has been another approach to this problem using Generative Adversarial Networks (GANs). GANs view this problem as a game between two sets of functions: a generator whose goal is to generate fake samples that are close to the real data training samples and a discriminator whose goal is to distinguish between the real and fake samples. In this project, we aim to train some of the state-of-the-art GAN architectures on image datasets and produce fake but believable images. Through this, students will gain some familiarity with Python and PyTorch.
Researchers
Assistant Professor, UMD Department of Computer Science
Graduate Student
Imagine that you are searching for a lost person in a forested environment. Or you are a first-responder searching for a survivor to rescue after a disaster. Searching for people or objects in the physical world is an important task in many societally important scenarios. In many of these scenarios, robots that are equipped with appropriate sensors (e.g., RGB and thermal cameras) can be used as scouts. These robots can assist human searchers, multiply their capabilities since they can operate tirelessly, and can reduce the risk to human lives especially when searching in unknown, potentially dangerous environments. In this project, we will develop algorithms for efficiently searching with a team of robots. https://youtu.be/BjJ2IhITya8
Researchers
Assistant Professor, UMD Department of Computer Science
Graduate Student
Graduate Student...
Register
2024 I4C Summer Academy applications are live in January 2024!
2023-2024 Cybersecurity Workshops are live now!
Register for workshops here: https://umdsurvey.umd.