Since the end of the semester, the students\u2019 concepts have been viewed by hundreds of analysts, managers, and software developers. In a survey seeking feedback from language analysts, LAS project leaders received nearly 70 responses.<\/p>\n\n\n\n
\u201cThe final prototypes beautifully integrated AI throughout the workflow, pushing the envelope of what might be possible in the world of language analysis,\u201d says Patti Kenney, a language analyst at LAS who gave students feedback on their ideas. <\/p>\n\n\n\n
The challenges that come with understanding the nuances of spoken languages, like regional dialects, slang, and casual conversation, became clear to the students. <\/p>\n\n\n\n
\u201cI didn’t realize that you had to listen so much,\u201d student Diksha Bahirwani says, referring to language analysts who scan voice recordings, often in foreign languages, for important details. \u201cNobody announces what they’re going to talk about before they talk about it.\u201d <\/p>\n\n\n\n
In the real world, designers also usually have an initial concept from which to base their ideas for refinement \u2013 upgrading an old website or improving a roadway intersection, for example. Because of privacy restrictions, however, Armstrong\u2019s students were not able to view the software and tools currently in use by intelligence analysts.<\/p>\n\n\n\n
\u201cFor designers, we always look at improving a design, and this was like starting from scratch, without any reference to what kind of features you guys use,\u201d Bahirwani says. Students based their interface prototypes on conversations with LAS language analysts and incorporated feedback received from critique sessions.<\/p>\n\n\n\n
\u201cIt was clear the students had come to deeply understand the language analyst workflow and that designing for these workflows from the vantage point of [College of Design building] Brooks Hall \u2013 from the outside in \u2013 contributed to the success of their work,\u201d Kenney says.<\/p>\n\n\n\n
Winston-Salem Computer Science Students Develop Synthetic Data for Cyber Analysts <\/h2>\n\n\n\n
This semester, LAS analysts also partnered with a class of 11 seniors at Winston-Salem State University (WSSU)<\/a> through the Educational Partnership Agreement and\/or Cooperative Research and\/or Development Agreement<\/a>. Their project focused on creating synthetic data knowledge graphs that could improve security within a cyberspace domain by training both cyber analysts and machine learning models. Synthetic data is artificially generated by a computer simulation and works as a stand-in for data from real-world events, which may contain sensitive or private information. <\/p>\n\n\n\n Applying knowledge graphs \u2013 visual displays of relationships between entities \u2013 to the cyber domain helps intelligence analysts better understand and visualize data. <\/p>\n\n\n\n \u201cThese graphs represent objects like cyber attacks, viruses, malware, descriptive information about adversaries, or networks, which can help analysts uncover relationships between objects,\u201d says Al Jarmon, an LAS analyst who collaborated with the students at WSSU. \u201cOur students made restriction-free knowledge graphs that will enable national security tool builders to build better algorithms. \u201d<\/p>\n\n\n\n The students used the computer programming language Python to generate high-quality synthetic knowledge graphs of cyber campaigns based on various input parameters that are exportable to STIX 2.1 (Structured Threat Information eXpression), a language and serialization format used by LAS analysts to exchange cyber threat intelligence. <\/p>\n\n\n\n \u201cThis partnership exposed students to real-world national security mission problem sets, which allowed them to develop interests in continuing collaboration and\/or employment opportunities with NSA,\u201d Jarmon says.<\/p>\n\n\n\n As a capstone research experience, the Senior Design Center of the Computer Science Department<\/a> at NC State assigns real-world problems to groups of graduating seniors during their final semester. This spring, two teams of computer science students tackled LAS-related projects. <\/p>\n\n\n\nNC State Computer Science Students Enhance Data Prioritization and Visualization Prototypes<\/h2>\n\n\n\n
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