Publications

@article{biswas_recognition_2017,

title = {Recognition of service domains on TOR dark net using perceptual hashing and image classification techniques},

author = {Rubel Biswas and Eduardo Fidalgo and Enrique Alegre},

url = {https://ieeexplore.ieee.org/abstract/document/8372164},

year  = {2017},

date = {2017-01-01},

journal = {8th International Conference on Imaging for Crime Detection and Prevention (ICDP 2017)},

pages = {7–12},

abstract = {This paper presents a framework for identifying services on the TOR network, leveraging image content to categorize various activities such as file-sharing, ransomware, and counterfeit goods. The authors introduce the DUSI (Darknet Usage Service Images) dataset, which includes snapshots from active TOR domains across six service categories. Two pipelines were evaluated: one using Perceptual Hashing and another using Bag of Visual Words (BoVW) with SVM classifiers. The Perceptual Hashing approach achieved the highest accuracy of 99.38%, making it the recommended method for detecting TOR services based on image snapshots.},

note = {Publisher: IET},

keywords = {Darknet Detection, Image classification, perceptual hashing, TOR},

pubstate = {published},

tppubtype = {article}

}