When monitoring network traffic, Cybersecurity analysts deal with a gigantic amount of data. If you print data into a hard form, it can be akin’s to a thick phonebook within just one day’s worth of usage. And it’s like finding a needle in a haystack if you detect an abnormality in a haystack.
It’s an ocean of data, said Yan Cai, the senior scientist in CyLab. Yan Cai has been working for years to identify abnormalities in network traffic. He is working on many ways to create as many solutions as possible. In the recent past, Yan Cai with his group developed to build a data visualization tool. This tool was designed to see network patterns, and he also developed a way to listen to the network abnormalities.
Yan Cai and Network Abnormalities
“We needed to explain ordinary and strange examples through music,” Cai says. “The interaction of sonification—utilizing sound to perceptualize information—isn’t new, yet sonification to make information more interesting to the human ear is.”
The scientists explored different avenues regarding a few unique “sound planning/mapping” calculations, changing numeral datasets into music with different songs, harmonies, timing schemes, and beats. For instance, the scientists allocated detailed notes to the ten digits that make up any number found in information: 0, 1, 2, 3, 4, 5, 6, 7, 8, and 9. To address the third and fourth digits of the numerical consistent Pi—4 and 1—they changed the timing scheme of one measure to 4/4 and the accompanying measure to 1/4.
We know, with all this technical information, it may sound not very easy to you. But you do not need to be a trained musician to listen to the abnormalities or these music changes.
The group made music utilizing network traffic information from a genuine malware conveyance organization and introduced the music to non-artists. They tracked down that non-artists had the option to precisely perceive changes in pitch when played on various instruments.
“We are making music, however transforming dynamic information into something that people can measure,” the writers write in their examination.
Yan Cai Predicting Future of Turning Network Traffic Data into Music
Cai says his vision is that sometime in the future, an examiner will want to investigate online protection information with augmented reality goggles introducing the perception of the organization space. At the point when the investigator draws nearer to an individual information point or a bunch of information, music addressing that information would continuously turn out to be more discernible.
“The thought is to utilize the entirety of people’s tactile channels to investigate this digital logical space,” Cai says.
Co-creators Jakub Polaczyk (left) and Katelyn Croft (right) were the two understudies of Cai’s and graduated from Carnegie Mellon’s College of Fine Arts.
While Cai himself is anything but a prepared artist, his two co-creators on the examination are. Jakub Polaczyk and Katelyn Croft were once understudies in Carnegie Mellon University’s College of Fine Arts. Polaczyk got his Artist Diploma in Composition in 2013 and is presently an honour winning arranger situated in New York City. Croft earned her graduate degree in harp execution in 2020 and is in Taiwan considering the impact of Western music on Asian music.
Before graduating in 2020, Croft worked in Cai’s lab on a virtual presentation project. Polaczyk took Cai’s University-wide course, “Innovativeness,” in 2011, and the two have teamed up from that point forward.
“It has been an enjoyable coordinated effort,” Cai says. “This sort of cross-disciplinary cooperation truly embodies CMU’s qualities.”
CyLab scientists make network traffic perception instruments to help defeat digital assaults.
That’s all for Civic FItness today’s article on “Turning Network Traffic Data into Music.” It’s a technology that is worth looking for to improve in the future.