Title slide: "Detecting Mobile Steganography Using Random Tests" with author names and university affiliations.

Title page from Seth Pierre’s presentation


Seth Pierre
Seth Pierre

Seth Pierre, an undergraduate student in electrical engineering at Iowa State University, received a Best Presentation Award at the International Conference on Forensic Inference and Statistics. He virtually presented Detecting Steganography from Mobile Stego Apps Using Random Statistical Properties on Jan. 21.

Pierre’s presentation described a proof-of-concept for detecting unencrypted payload, or secret messages, hidden inside an image created by any mobile steganography app. A method was developed that applies a test of randomness to the bit sequences in an image and could be a first step towards producing a stego-detection tool for mobile images.

This project was led by Center for Statistics and Applications in Forensic Evidence (CSAFE) researchers including Pierre; Li Lin, a postdoctoral research association in mathematics; Abby Martin, a graduate student in mathematics; and Jennifer Newman, a professor of mathematics.

“I feel so fortunate to have had the chance to be a part of the ICFIS 2021. In addition to collaborating with and learning from other professionals and students within the industry, I was awarded the Best Presentation Award,” said Pierre.” Special thanks to CSAFE for presenting me with so many opportunities and the College of Engineering for providing me exceptional curriculum and professors to learn from at Iowa State.”

Pierre’s presentation was selected for the award by the session chair and the program committee based on a review of the abstract and the quality of the presentation. The award was announced after the conference.

View Pierre’s presentation at https://forensicstats.org/wp-content/uploads/2021/02/pierre_seth_icfis2021presentation.pdf.

For more information about CSAFE’s work on digital evidence, including steganography forensics, visit https://forensicstats.org/digital-evidence/.

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