scholarly journals A False Negative Study of the Steganalysis Tool Stegdetect

2020 ◽  
Vol 10 (22) ◽  
pp. 8188
Author(s):  
Benjamin Aziz ◽  
Jeyong Jung ◽  
Julak Lee ◽  
Yong-Tae Chun

In this study, we evaluated one of the modern automated steganalysis tools, Stegdetect, to study its false negative rates when analysing a bulk of images. In so doing, we used JPHide method to embed a randomly generated messages into 2000 JPEG images. The aim of this study is to help digital forensics analysts during their investigations by means of providing an idea of the false negative rates of Stegdetect. This study found that (1) the false negative rates depended largely on the tool’s sensitivity values, (2) the tool had a high false negative rate between the sensitivity values from 0.1 to 3.4 and (3) the best sensitivity value for detection of JPHide method was 6.2. It is therefore recommended that when analysing a huge bulk of images forensic analysts need to take into consideration sensitivity values to reduce the false negative rates of Stegdetect.

2018 ◽  
Author(s):  
Benjamin Aziz ◽  
Jeyong Jung

Steganography and Steganalysis in recent years have become an important area of research involving dierent applications. Steganography is the process of hiding secret data into any digital media without any signicant notable changes in a cover object, while steganalysis is the process of detecting hiding content in the cover object. In this study, we evaluated one of the modern automated steganalysis tools, Stegdetect, to study its false negative rates when analysing a bulk of images. In so doing, we used JPHide method to embed a randomly generated messages into 2000 JPEG images. The aim of this study is to help digital forensics analysts during their investigations by means of providing an idea of the false negative rates of Stegdetect. This study found that (1) the false negative rates depended largely on the tool's sensitivity values, (2) the tool had a high false negative rate between the sensitivity values from 0.1 to 3.4 and (3) the best sensitivity value for detection of JPHide method was 6.2. It is recommended that when analysing a huge bulk of images forensic analysts need to take into consideration sensitivity values to reduce the false negative rates of Stegdetect.


2018 ◽  
Author(s):  
Benjamin Aziz ◽  
Jeyong Jung

Steganography and Steganalysis in recent years have become an important area of research involving dierent applications. Steganography is the process of hiding secret data into any digital media without any signicant notable changes in a cover object, while steganalysis is the process of detecting hiding content in the cover object. In this study, we evaluated one of the modern automated steganalysis tools, Stegdetect, to study its false negative rates when analysing a bulk of images. In so doing, we used JPHide method to embed a randomly generated messages into 2000 JPEG images. The aim of this study is to help digital forensics analysts during their investigations by means of providing an idea of the false negative rates of Stegdetect. This study found that (1) the false negative rates depended largely on the tool's sensitivity values, (2) the tool had a high false negative rate between the sensitivity values from 0.1 to 3.4 and (3) the best sensitivity value for detection of JPHide method was 6.2. It is recommended that when analysing a huge bulk of images forensic analysts need to take into consideration sensitivity values to reduce the false negative rates of Stegdetect.


2021 ◽  
Vol 106 ◽  
pp. 106582
Author(s):  
Alex Niu ◽  
Bo Ning ◽  
Francisco Socola ◽  
Hana Safah ◽  
Tim Reynolds ◽  
...  

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A225-A225
Author(s):  
C D Morse ◽  
S Meissner ◽  
L Kodali

Abstract Introduction Sleep apnea is a serious disorder associated with numerous health conditions. In clinical practice, providers order screening home sleep testing (HST) for obstructive sleep apnea (OSA); however, there is limited research about the negative predictive value (NPV) and false negative rate of this test. Providers may not understand HST limitations; therefore, what is the NPV and false negative rate in clinical practice? Methods A retrospective study of non-diagnostic HST is conducted in a Northeastern US rural community sleep clinic. The study population includes adult patients ≥ 18 years old who underwent HST from 2016-2019. The non-diagnostic HST result is compared to the gold standard, the patient’s nocturnal polysomnogram (NPSG). The results provide the NPV (true negative/total) and false negative (true positive/total) for the non-diagnostic HST. Results We identified 211 potential patients with a mean age of 43 years, of which 67% were female. Of those, 85% (n=179) underwent NPSG, with the others declining/delaying testing or lost to follow up. The non-diagnostic HST showed 15.6% NPV for no apnea using AHI<5 and 8.4% NPV using respiratory disturbance index (tRDI)<5. The false negative rate for AHI/tRDI was 84.4% and 91.6%, respectively. The AHI for positive tests ranged from 5-89 per hour (mean AHI 14.9/tRDI 16/hour), of which OSA was identified with an elevated AHI (≥5) ranging from 54.2% mild, 21.8% moderate, and 8.4% severe. Conclusion The high false negative rate of the HST is alarming. Some providers and patients may forgo NPSG after non-diagnostic HST due to a lack of understanding for the HST’s limitations. Knowing that the non-diagnostic HST is a very poor predictor of no sleep apnea will help providers advise patients appropriately for the necessity of the NPSG. The subsequent NPSG provides an accurate diagnosis and, therefore, an informed decision about pursuing or eschewing sleep apnea treatment. Support none


2016 ◽  
Vol 150 (1) ◽  
pp. 283-284 ◽  
Author(s):  
Glenn S. Gerhard ◽  
Christopher D. Still ◽  
Johanna K. DiStefano

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