Tag Archive for: Learning

High School students learning cyber security training through paid internship with VMI

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LEXINGTON, Va. – The Virginia Military Institute is helping high school students better understand cyber security through a paid internship program.

Seven local high schoolers are currently participating in this fully immersive program and are gaining a better understanding of cyber security by working with VMI Cadets.

The students come from Rockbridge County High School, Parry McCluer High School and a homeschool group. They meet every day after school for two hours to work on two separate projects.

The first project they have been working on is called the Internet of Things Box, which represents the smart interconnected devices people use at home and work. Interconnected devices include items like a web camera, smart outlets, Google Homes or an Alexa.

With this project, the students learned the secrets of the networks and devices, built them by hand and then attempted to hack them.

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“The students are learning new stuff and trying to figure out those hard problems with a little push from my team, but a lot of this is on their own,” said Cole Corson, a VMI student. “They are really self-motivated. They have to go out there and figure out what the solution is to their problem and that’s what I think is the core and the best part about this program. It teaches them how to go find the answer to their problems themselves, and in the pre-science world, computers and the internet help with that a lot.”

The second project students are working on is called the “Turnout” app. This app is designed to provide cadets with notifications that have information about cyber events. Students worked with cadets to learn, design and develop complete software programs.

“Cyber security and programming and all this computer stuff is my hobby,” said Jonas Squires, a homeschool student participating in the program. “It is what I do at home, and so the opportunity to do it here with all sorts of technology that I don’t have access to at home and learn new things was just an opportunity that I couldn’t pass up.”

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This program is in partnership with Virginia Tech. Two Virginia Tech graduate students brought innovative tools to the internship site.

This experience is allowing a younger…

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Engineering seminar: Cyber Storm Tracker — Using Machine Learning for Cyber Log Data

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Dr. Glenn A. Fink, a senior cyber sercurity researcher with Pacific Northwest National Laboratory (PNNL), will give the talk.

Cyber logs are not human language, but of all the common data types used in machine learning (ML), natural language is the closest. But cyber log data is very different from natural lanuage. Log lines contains lots of random-looking garbage. IP addresses and other things frequently change definition. Punctuationh is all over the place. Domain names look like Windows Active Directory names, which look like many other cyber “nouns.” And the syntax and semantics of phrases and terms changes from sensor to sensor. This makes cyber data challenging to ingest into ML models. 

Dr. Fink will talk about the work done at PNNL to ingest cyber logs into natural language processing tools using embeddings. He’ll also show how embeddings can be used as coordinates to show how IP addresses change behavior and relate over time. At the end, seminar attendees will understand why there are still not many true ML methods out there for cyber, and what the major challenges are ahead. 

Dr. Find has worked in computer security, deep learning, visualization, bio-inspired design and human-centric computing at PNNL since 2006. He is the lead inventor of several technologies, including PNNL’s Digital Ants technology, which Scientific American cited as one of 10 “world-changing ideas” in 2010. Digital Ants recently earned an award for Excellence in Technology Transfer from the Federal Laboratory Consortium and was listed as a finalist for an R&D 100 award. His work includes research in bio-inspired, decentralized cyber security and privacy. He has published numerous scientific articles and papers, has edited a book and hosted several workshops on computer security, privacy and the Internet of Things. 

Dr. Fink was a three-year NSF IGERT Graduate Fellow at Virginia Polytechnic Institute and State University, where he completed his Ph.D. in computer science in 2006. Dr. Fink’s dissertation, “Visual Correlation of Network Traffic and Host Processes,” fostered the Hone technology that currently is an open-source software project. Dr. Fink was a software…

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Understanding cybersecurity from machine learning POV

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Cybersecurity has undergone massive shifts technology-wise, led by data science. The extraction of security incident patterns or insights from cybersecurity data and building data-driven models on it is the key to making a security system automated and intelligent.

Cybersecurity data science is a phenomenon where the data and analytics acquired from relevant cybersecurity sources suit the data-driven patterns that give more effective security solutions. The concept of cybersecurity data science makes the computing process more actionable and intelligent when compared to traditional ones in cybersecurity. Therefore, an ML-based multi-layered framework for cybersecurity modelling is sought after today.

Today, companies depend more on digitalisation and Internet-of-Things (IoT) after various security issues like unauthorised access, malware attack, zero-day attack, data breach, denial of service (DoS), social engineering or phishing surfaced at a significant rate. Cybercrime causes disastrous and sometimes irreversible financial losses that affect both organisations and individuals. A data breach costs $8.19 million in the United States and $3.9 million on an average, according to an IBM report. Meanwhile, the annual cost for the global economy from cybercrime is $400 billion. 

What is cybersecurity data science?

Data science brought about a global change in various industries. However, it has become an important segment for the future of robust cybersecurity systems and services. This comes after cybersecurity has become all about data. For example, while detecting cyber threats, it analyses security data in files, logs, network packets, or other sources. Commonly, security professionals did not use data science to detect cyber threats. Instead, they used file hashes, custom-written rules, and manually defined heuristics.

Although it has its own merits, it requires a lot of manual labour to keep up with the ever-changing threat landscape. On the other hand, data science can change the industry with machine learning algorithms that can be used to extract insights of security event patterns from training data for detection and prevention. It can be used to detect…

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Computer Security for Everyone

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