Visible to the public Science of Security VO

UPDATED 2022 Summer Internship Program in Science of Security (SIP-SoS) - Accepting Applications
The National Security Agency (NSA) Summer Internship Program in Science of Security (SoS) is for undergraduate and graduate students currently enrolled at U.S. universities and colleges. The program provides an opportunity for exceptional science, technology, engineering, and math (STEM) students to work directly with NSA...
UPDATED 2022 Summer Internship Program in Science of Security (SIP-SoS) - Accepting Applications
Summer 2021 SoS Quarterly Lablet Meeting
Summer 2021 SoS Quarterly Lablet Meeting The Summer 2021 Science of Security and Privacy (SoS) Quarterly Lablet meeting was hosted virtually by Carnegie Mellon University (CMU) on July 13-14, 2021. The virtual attendees from the government and the six SoS Lablets were welcomed by Jonathan Aldrich, the Principal...
Summer 2021 SoS Quarterly Lablet Meeting
SoS Musings #50 - Moving Automotive Cybersecurity into the Fast Lane
SoS Musings #50 - Moving Automotive Cybersecurity into the Fast Lane Connected and autonomous vehicles offer benefits, but they also introduce significant cybersecurity risks that can lead to the loss of life on the road. As vehicles increase in connectivity, they become more vulnerable to being hacked, manipulated,...
SoS Musings #50 - Moving Automotive Cybersecurity into the Fast Lane
Spotlight on Lablet Research #21 - Principles of Secure BootStrapping for IoT
Spotlight on Lablet Research #21 - Principles of Secure BootStrapping for IoT Lablet: North Carolina State University Sub-Lablet: Purdue University This research project, which concluded in March 2021, was motivated by the fact that IoT devices need trust and secure communication--trust between devices and...
Spotlight on Lablet Research #21 - Principles of Secure BootStrapping for IoT
Upcoming Events Worth Checking Out
The lastest information on all upcoming science of security related events.
Upcoming Events Worth Checking Out
Alexandre Bayen is a driving force behind mixed-autonomy traffic
Coordinated automation could improve traffic flow, boost efficiency, and slash emissions. A combination of machine learning, big data, and Amazon Web Services is making this future possible. By Sean O'Neill | August 23, 2021 The smooth-flowing traffic of the future is just around the corner. Advances in vehicle...
Alexandre Bayen is a driving force behind mixed-autonomy traffic
Cyber Scene #59 - Cyber Around the World
Cyber Scene #59 - Cyber Around the World Ill-gotten cyber gains continue to extend their reach. This month's Cyber Scene starts in Asia but moves around the world. Brand new to Cyber Scene is the inclusion of Taliban, which also is playing a cyber role in making Southeast Asian history today. As there is not yet any...
Cyber Scene #59 - Cyber Around the World
Cybersecurity Snapshots #21 - Do You Know Where Your QR Code Is Taking You?
Cybersecurity Snapshots #21 - Do You Know Where Your QR Code Is Taking You? For some time, QR codes were mainly used in industrial environments to help keep track of inventory and production. They later gained popularity among advertisers because it was easier for consumers to scan a code than to type a long URL. But...
Cybersecurity Snapshots #21 - Do You Know Where Your QR Code Is Taking You?

Visible to the public 

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    • Cross Platform IoT-Malware Family Classification Based on Printable Strings
      Abstract: In this era of rapid network development, Internet of Things (IoT) security considerations receive a lot of attention from both the research and commercial sectors. With limited computation resource, unfriendly interface, and poor software implementation, legacy IoT devices are vulnerable to many... more
    • Malware Classification Framework Using Convolutional Neural Network
      Abstract: Cyber-security is facing a huge threat from malware and malware mass production due to its mutation factors. Classification of malware by their features is necessary for the security of information technology (IT) society. To provide security from malware, deep neural networks (DNN) can offer a... more
    • Malware Detection Amp; Classification Using Machine Learning
      Abstract: With fast turn of events and development of the web, malware is one of major digital dangers nowadays. Henceforth, malware detection is an important factor in the security of computer systems. Nowadays, attackers generally design polymeric malware [1], it is usually a type of malware [2] that... more
    • Malware Classification Using Recurrence Plots and Deep Neural Network
      Abstract: In this paper, we introduce a method for visualizing and classifying malware binaries. A malware binary consists of a series of data points of compiled machine codes that represent programming components. The occurrence and recurrence behavior of these components is determined by the common tasks... more
    • Malware Family Classification Using Active Learning by Learning
      Abstract: In the past few years, the malware industry has been thriving. Malware variants among the same malware family shared similar behavioural patterns or signatures reflecting their purpose. We propose an approach that combines support vector machine (SVM) classifiers and active learning by learning (... more
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