@article{ART003348213},
author={Park Byeongchan and Youngmo Kim},
title={A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments},
journal={ Journal of Software Forensics},
issn={3092-541X},
year={2026},
volume={22},
number={2},
pages={79-91},
doi={10.29056/jsf.2026.06.08}
TY - JOUR
AU - Park Byeongchan
AU - Youngmo Kim
TI - A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments
JO - Journal of Software Forensics
PY - 2026
VL - 22
IS - 2
PB - Korea Software Assessment and Valuation Society
SP - 79
EP - 91
SN - 3092-541X
AB - As online video distribution continues to expand, unauthorized video provision and retransmission through illegal OTT sites and illegal betting-related streaming sites have become increasingly widespread.
Videos provided in illegal streaming environments are often not reproduced in their original form. Instead, they frequently include various transformation factors such as subtitle insertion, logo and watermark overlays, screen cropping, resolution degradation, re-encoding, screen recording, advertisement banners, player UI exposure, and overlays of game and betting-related information. These transformations may weaken the visual characteristics and temporal correspondence of the original video, thereby affecting video detection performance. This paper analyzes video transformation types observed in illegal streaming environments and proposes robustness evaluation criteria for video detection. The transformation types are classified into visual transformations, structural editing transformations, service interface overlays, live-streaming environment transformations, acquisition and retransmission environment transformations, and composite transformations. In addition, the influence of each transformation type on video detection is examined, and detailed evaluation parameters and level-based criteria are presented.
KW - Illegal Streaming Environment;Video Transformation Types;Video Detection;Robustness Evaluation Criteria;Illegal OTT;Illegal Retransmission
DO - 10.29056/jsf.2026.06.08
ER -
Park Byeongchan and Youngmo Kim. (2026). A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments. Journal of Software Forensics, 22(2), 79-91.
Park Byeongchan and Youngmo Kim. 2026, "A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments", Journal of Software Forensics, vol.22, no.2 pp.79-91. Available from: doi:10.29056/jsf.2026.06.08
Park Byeongchan, Youngmo Kim "A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments" Journal of Software Forensics 22.2 pp.79-91 (2026) : 79.
Park Byeongchan, Youngmo Kim. A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments. 2026; 22(2), 79-91. Available from: doi:10.29056/jsf.2026.06.08
Park Byeongchan and Youngmo Kim. "A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments" Journal of Software Forensics 22, no.2 (2026) : 79-91.doi: 10.29056/jsf.2026.06.08
Park Byeongchan; Youngmo Kim. A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments. Journal of Software Forensics, 22(2), 79-91. doi: 10.29056/jsf.2026.06.08
Park Byeongchan; Youngmo Kim. A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments. Journal of Software Forensics. 2026; 22(2) 79-91. doi: 10.29056/jsf.2026.06.08
Park Byeongchan, Youngmo Kim. A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments. 2026; 22(2), 79-91. Available from: doi:10.29056/jsf.2026.06.08
Park Byeongchan and Youngmo Kim. "A Study on Video Transformation Type Analysis and Robustness Evaluation Criteria for Illegal Streaming Environments" Journal of Software Forensics 22, no.2 (2026) : 79-91.doi: 10.29056/jsf.2026.06.08
