• Imaging Science in Dentistry
• /
• v.43 no.1
• /
• pp.1-6
• /
• 2013

Purpose: This study investigated the possible correlation between the mineralization of the second molars and the chronological age of a sample population of the state of Paraiba, Brazil. Materials and Methods: One thousand eight hundred fifty-four digitized panoramic images using a scanner of a private dental radiology service were obtained in six months. Of these, 457 were selected from patients aged 4.6 to 16 years who met certain criteria. The images were assessed twice by a radiologist with 5 years experience. A minimum interval of 30 days between the evaluations of the same patient was established. To analyze the relationship between chronological age, calcification level proposed by Demirjian et al in 1973, gender, and tooth, a multiple linear regression model was adjusted, taking age as the response variable (p<0.05). Results: The gender and calcification level were significantly correlated with the age of the patients (p<0.05). There was a significant difference between the average age of the patients' upper teeth compared to the lower ones in both genders (p<0.05). The dental development occurred earlier in female individuals than in male ones, and there was no significant difference between the right and left second permanent molars. Conclusion: It was observed that ethnic variables are related to certain parameters of age and sex identification in the Brazilian population, providing important information for forensic evaluations.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.19 no.5
• /
• pp.151-166
• /
• 2009

To prove the integrity of digital evidence on the investigation procedure, the data which is using the MD 5(Message Digest 5) hash-function algorithm has to be discarded, if the integrity was damaged on the investigation. Even though a proof restoration of the deleted area is essential for securing the proof regarding a main phase of a case, it was difficult to secure the decisive evidence because of the damaged evidence data due to the difference between the overall hash value and the first value. From this viewpoint, this paper proposes the novel model for the mobile forensic procedure, named as "E-Finder(Evidence Finder)", to ,solve the existing problem. The E-Finder has 5 main phases and 15 procedures. We compared E-Finder with NIST(National Institute of Standards and Technology) and Tata Elxsi Security Group. This paper thus achieved the development and standardization of the investigation methodology for the mobile forensics.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.1
• /
• pp.77-88
• /
• 2022

With the development and popularization of drone manufacturing technology, the drone market, which was mainly focused on industry, agriculture, and military, is also showing great growth in individual and commercial markets. Among them, DJI has a high share in the personal and commercial drone market, and accordingly, forensic analysis of DJI drones is drawing attention. In particular, when stealing and analyzing drones used in criminal acts, a technology to interpret flight logs recording drone flight paths and hardware information is needed, which inevitably applies drone models due to differences in decryption methods. Therefore, when an unidentified drone is acquired from the perspective of a digital forensic investigator, a clear classification of a drone model to which analysis can be applied is required. This paper proposes a method of extracting and analyzing artifacts of DJI drones through forensics, and analyzes media data analysis and flight log analysis results and decryption methods for three drone models with different release years of DJI. Finally, drones in the DJI product line are classified according to whether the commercialized DJI drone flight log is decrypted.

• Imaging Science in Dentistry
• /
• v.53 no.3
• /
• pp.221-227
• /
• 2023

Purpose: This study was performed to develop a linear regression model using the pulp-to-tooth volume ratio (PTVR) ratio of the maxillary canine, assessed through cone-beam computed tomography (CBCT) images, to predict chronological age (CA) in Indonesian adults. Materials and Methods: A sample of 99 maxillary canines was collected from patients between 20 and 49.99 years old. These samples were obtained from CBCT scans taken at the Universitas Padjadjaran Dental Hospital in Indonesia between 2018 and 2022. Pulp volume (PV) and tooth volume (TV) were measured using ITK-SNAP, while PTVR was calculated from the PV/TV ratio. Using RStudio, a linear regression was performed to predict CA using PTVR. Additionally, correlation and observer agreement were assessed. Results: The PTVR method demonstrated excellent reproducibility, and a significant correlation was found between the PTVR of the maxillary canine and CA(r= -0.74, P<0.01). The linear regression analysis showed an R² of 0.58, a root mean square error of 5.85, and a mean absolute error of 4.31. Conclusion: Linear regression using the PTVR can be effectively applied to predict CA in Indonesian adults between 20 and 49.99 years of age. As models of this type can be population-specific, recalibration for each population is encouraged. Additionally, future research should explore the use of other teeth, such as molars.

• ETRI Journal
• /
• v.39 no.3
• /
• pp.398-405
• /
• 2017

In this paper, an artificial stereo extension method that creates stereophonic sound from a mono sound source is proposed. The proposed method first trains deep neural networks (DNNs) that model the nonlinear relationship between the dominant and residual signals of the stereo channel. In the training stage, the band-wise log spectral magnitude and unwrapped phase of both the dominant and residual signals are utilized to model the nonlinearities of each sub-band through deep architecture. From that point, stereo extension is conducted by estimating the residual signal that corresponds to the input mono channel signal with the trained DNN model in a sub-band domain. The performance of the proposed method was evaluated using a log spectral distortion (LSD) measure and multiple stimuli with a hidden reference and anchor (MUSHRA) test. The results showed that the proposed method provided a lower LSD and higher MUSHRA score than conventional methods that use hidden Markov models and DNN with full-band processing.

• Computers and Concrete
• /
• v.10 no.4
• /
• pp.331-347
• /
• 2012

This paper describes the varying material model, the analysis method and the software development for reinforced concrete circular columns confined by spiral or hoop transverse steel reinforcement and subjected to eccentric loading. The widely used Mander model of concentric loading is adapted here to eccentric loading by developing an auto-adjustable stress-strain curve based on the eccentricity of the axial load or the size of the compression zone to generate more accurate interaction diagrams. The prediction of the ultimate unconfined capacity is straight forward. On the other hand, the prediction of the actual ultimate capacity of confined concrete columns requires specialized nonlinear analysis. This nonlinear procedure is programmed using C-Sharp to build efficient software that can be used for design, analysis, extreme event evaluation and forensic engineering. The software is equipped with an elegant graphics interface that assimilates input data, detail drawings, capacity diagrams and demand point mapping in a single sheet. Options for preliminary design, section and reinforcement selection are seamlessly integrated as well. Improvements to KDOT Bridge Design Manual using this software with reference to AASHTO LRFD are made.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2019.11a
• /
• pp.58-60
• /
• 2019

Double JPEG compression detection is one of the most important ways of exposing the integrity of the JPEG image in image forensics. Several methods have been proposed for discriminating against the double JPEG image. In this paper, we propose a new method for restoring the JPEG compressed image and making the detector confused by introducing a Generative Adversarial Network (GAN). First, a generator network is designed for restoring the JPEG compressed image and analyzed the quality. Then, the restored image is tested with the double compression detector for evaluating the robustness of the proposed GAN model. The detection accuracy reduces from 98% to 58%.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
• /
• 2006.06a
• /
• pp.403-407
• /
• 2006

완벽한 디지털 범죄 수사를 위해서는 우수한 디지털 포렌식 기술이 우선적으로 요구되겠지만, 범죄수사의 특성상 기술이외에도 법적, 제도적 측면들이 적절하게 조합되어야만 한다. 본 논문에서는 디지털 포렌식의 제도 및 정책적인 면에서 디지털 범죄 수사의 절차가 현실적으로 적용 가능하고, 범죄 해결에 효율적이며 합법성을 유지하면서 진행될 수 있도록 새로운 형태의 디지털 포렌식 절차를 제안하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.11a
• /
• pp.960-963
• /
• 2011

국내에 디지털 포렌식 연구가 시작된 2000년 초반에는 디지털 증거의 취약성에 주의하여 디지털 증거의 보존을 중심으로 조사 분석을 어떻게 할 것인가에 초점을 맞추었다. 이를 통해 수집한 데이터와 분석한 결과를 법적인 증거 자료로 어떻게 인정받을 것인지가 주요 이슈였다. 하지만 최근에는 디지털 포렌식 조사가 일반 민사 형사 사건에 모두 활용되면서 디지털 증거 처리만이 아닌 사건 발생부터 법정 증언까지 고려한 전체 조사 과정을 아우르는 모델로 발전하고 있다. 따라서 이러한 변화에 따르고 국내 환경에 적합한 디지털 포렌식 조사 모델이 필요하다. 본 논문은 국내외 디지털 포렌식 조사 모델에 대한 연구를 살펴보고, 이를 국내 환경에 적합하도록 정립하기 위한 방안을 기술한다.

• International Journal of Computer Science & Network Security
• /
• v.23 no.5
• /
• pp.179-192
• /
• 2023

The widespread use of Cloud Computing, Internet of Things (IoT), and social media in the Information Communication Technology (ICT) field has resulted in continuous and unavoidable cyber-attacks on users and critical infrastructures worldwide. Traditional security measures such as firewalls and encryption systems are not effective in countering these sophisticated cyber-attacks. Therefore, Intrusion Detection and Prevention Systems (IDPS) are necessary to reduce the risk to an absolute minimum. Although IDPSs can detect various types of cyber-attacks with high accuracy, their performance is limited by a high false alarm rate. This study proposes a new technique called Fuzzy Logic - Objective Risk Analysis (FLORA) that can significantly reduce false positive alarm rates and maintain a high level of security against serious cyber-attacks. The FLORA model has a high fuzzy accuracy rate of 90.11% and can predict vulnerabilities with a high level of certainty. It also has a mechanism for monitoring and recording digital forensic evidence which can be used in legal prosecution proceedings in different jurisdictions.