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Subject: Machine Learning

The Vectors of Code: On Machine Learning for Software

The Vectors of Code: On Machine Learning for Software

• SEI Blog
Zachary Kurtz

This blog post provides a light technical introduction on machine learning (ML) for problems of computer code, such as detecting malicious executables or vulnerabilities in source code. Code vectors enable ML practitioners to tackle code problems that were previously approachable only with highly-specialized software engineering knowledge. Conversely, code vectors can help software analysts to leverage general, off-the-shelf ML tools without needing to become ML experts. In this post, I introduce some use cases for ML...

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Deep Learning and Satellite Imagery: DIUx Xview Challenge

Deep Learning and Satellite Imagery: DIUx Xview Challenge

• SEI Blog
Ritwik Gupta

In 2017 and 2018, the United States witnessed a milestone year of climate and weather-related disasters from droughts and wildfires to cyclones and hurricanes. Increasingly, satellites are playing an important role in helping emergency responders assess the damage of a weather event and find victims in its aftermath. Most recently satellites have tracked the devastation wrought by the California wildfires from space. The United States military, which is often the first on the scene of...

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Improving Assessments for Cybersecurity Training

Improving Assessments for Cybersecurity Training

• SEI Blog
April Galyardt

The CERT Cyber Workforce Development Directorate conducts training in cyber operations for the DoD and other government customers as part of its commitment to strengthen the nation's cybersecurity workforce. A part of this work is to develop capabilities that better enable DoD cyber forces to "to train as you fight" such as setting up high-fidelity simulation environments for cyber forces to practice skills including network defense, incident response, digital forensics, etc. However, cybersecurity is a...

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Translating Between Statistics and Machine Learning

Translating Between Statistics and Machine Learning

• SEI Blog
Zachary Kurtz

Statistics and machine learning often use different terminology for similar concepts. I recently confronted this when I began reading about maximum causal entropy as part of a project on inverse reinforcement learning. Many of the terms were unfamiliar to me, but as I read closer, I realized that the concepts had close relationships with statistics concepts. This blog post presents a table of connections between terms that are standard in statistics and their related counterparts...

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Data-Driven Management of Technical Debt

Data-Driven Management of Technical Debt

• SEI Blog
Ipek Ozkaya

This post was co-authored by Robert Nord. Technical debt communicates the tradeoff between the short-term benefits of rapid delivery and the long-term value of developing a software system that is easy to evolve, modify, repair, and sustain. Like financial debt, technical debt can be a burden or an investment. It can be a burden when it is taken on unintentionally without a solid plan to manage it; it can also be part of an intentional...

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Deep Learning: Going Deeper toward Meaningful Patterns in Complex Data

Deep Learning: Going Deeper toward Meaningful Patterns in Complex Data

• SEI Blog
Carson Sestili

In a previous blog post, we addressed how machine learning is becoming ever more useful in cybersecurity and introduced some basic terms, techniques, and workflows that are essential for those who work in machine learning. Although traditional machine learning methods are already successful for many problems, their success often depends on choosing and extracting the right features from a dataset, which can be hard for complex data. For instance, what kinds of features might be...

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Video Summarization: Using Machine Learning to Process Video from Unmanned Aircraft Systems

Video Summarization: Using Machine Learning to Process Video from Unmanned Aircraft Systems

• SEI Blog
Kevin Pitstick

As the use of unmanned aircraft systems (UASs) increases, the volume of potentially useful video data that UASs capture on their missions is straining the resources of the U.S. military that are needed to process and use this data. This publicly released video is an example of footage captured by a UAS in Iraq. The video shows ISIS fighters herding civilians into a building. U.S. forces did not fire on the building because of the...

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Revealing True Emotions Through Micro-Expressions: A Machine Learning Approach

Revealing True Emotions Through Micro-Expressions: A Machine Learning Approach

• SEI Blog
Satya Venneti

Micro-expressions--involuntary, fleeting facial movements that reveal true emotions--hold valuable information for scenarios ranging from security interviews and interrogations to media analysis. They occur on various regions of the face, last only a fraction of a second, and are universal across cultures. In contrast to macro-expressions like big smiles and frowns, micro-expressions are extremely subtle and nearly impossible to suppress or fake. Because micro-expressions can reveal emotions people may be trying to hide, recognizing micro-expressions can...

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Machine Learning and Insider Threat

Machine Learning and Insider Threat

• SEI Blog
Daniel Costa

As organizations' critical assets have become digitized and access to information has increased, the nature and severity of threats has changed. Organizations' own personnel--insiders--now have greater ability than ever before to misuse their access to critical organizational assets. Insiders know where critical assets are, what is important, and what is valuable. Their organizations have given them authorized access to these assets and the means to compromise the confidentiality, availability, or integrity of data. As organizations...

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Machine Learning in Cybersecurity

Machine Learning in Cybersecurity

• SEI Blog
Eliezer Kanal

The year 2016 witnessed advancements in artificial intelligence in self-driving cars, language translation, and big data. That same time period, however, also witnessed the rise of ransomware, botnets, and attack vectors as popular forms of malware attack, with cybercriminals continually expanding their methods of attack (e.g., attached scripts to phishing emails and randomization), according to Malware Byte's State of Malware report. To complement the skills and capacities of human analysts, organizations are turning to machine...

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What Ant Colonies Can Teach Us About Securing the Internet

What Ant Colonies Can Teach Us About Securing the Internet

• SEI Blog
William Casey

In cyber systems, the identities of devices can easily be spoofed and are frequent targets of cyber-attacks. Once an identity is fabricated, stolen or spoofed it may be used as a nexus to systems, thus forming a Sybil Attack. To address these and other problems associated with identity deception researchers at the Carnegie Mellon University Software Engineering Institute, New York University's Tandon School of Engineering and Courant Institute of Mathematical Sciences, and the University of...

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Using Machine Learning to Detect Malware Similarity

Using Machine Learning to Detect Malware Similarity

• SEI Blog
Sagar Chaki

Malware, which is short for "malicious software," consists of programming aimed at disrupting or denying operation, gathering private information without consent, gaining unauthorized access to system resources, and other inappropriate behavior. Malware infestation is of increasing concern to government and commercial organizations. For example, according to the Global Threat Report from Cisco Security Intelligence Operations, there were 287,298 "unique malware encounters" in June 2011, double the number of incidents that occurred in March. To help...

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