• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4076-4092
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• 2019

Nowadays, most users access internet through mobile applications. The common way to authenticate users through websites forms is using passwords; while they are efficient procedures, they are subject to guessed or forgotten and many other problems. Additional multi modal authentication procedures are needed to improve the security. Behavioral authentication is a way to authenticate people based on their typing behavior. It is used as a second factor authentication technique beside the passwords that will strength the authentication effectively. Keystroke dynamic rhythm is one of these behavioral authentication methods. Keystroke dynamics relies on a combination of features that are extracted and processed from typing behavior of users on the touched screen and smart mobile users. This Research presents a novel analysis in the keystroke dynamic authentication field using two features categories: timing and no timing combined features. The proposed model achieved lower error rate of false acceptance rate with 0.1%, false rejection rate with 0.8%, and equal error rate with 0.45%. A comparison in the performance measures is also given for multiple datasets collected in purpose to this research.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.417-420
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• 2014

Importance of security system to prevent recently increased financial security accident is increasing. Biometric system between the security systems is focused. Fingerprint recognition has many useful aspects such as security, reliability and portability. In this treatise, fingerprint recognition technique is realized by using artificial neural network. Artificial Neural Network(ANN) is a mathematics learning model that makes specific patterns that a program can recognize to show a nerve network's characteristic on a computer. Input fingerprint images have a preprocessing process such as equalization, binarization and thinning. We extract minutiae feature in the images and program can recognize a fingerprint through ANN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.131-146
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• 2021

Multimodal biometric-based recognition has been an active topic because of its higher convenience in recent years. Due to high user convenience of finger, finger-based personal identification has been widely used in practice. Hence, taking Finger-Print (FP), Finger-Vein (FV) and Finger-Knuckle-Print (FKP) as the ingredients of characteristic, their feature representation were helpful for improving the universality and reliability in identification. To usefully fuse the multimodal finger-features together, a new robust representation algorithm was proposed based on hierarchical model. Firstly, to obtain more robust features, the feature maps were obtained by Gabor magnitude feature coding and then described by Local Binary Pattern (LBP). Secondly, the LGBP-based feature maps were processed hierarchically in bottom-up mode by variable rectangle and circle granules, respectively. Finally, the intension of each granule was represented by Local-invariant Gray Features (LGFs) and called Hierarchical Local-Gabor-based Gray Invariant Features (HLGGIFs). Experiment results revealed that the proposed algorithm is capable of improving rotation variation of finger-pose, and achieving lower Equal Error Rate (EER) in our homemade database.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.319-331
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• 2022

The latest global COVID-19 pandemic has made the use of facial masks an important aspect of our lives. People are advised to cover their faces in public spaces to discourage illness from spreading. Using these face masks posed a significant concern about the exactness of the face identification method used to search and unlock telephones at the school/office. Many companies have already built the requisite data in-house to incorporate such a scheme, using face recognition as an authentication. Unfortunately, veiled faces hinder the detection and acknowledgment of these facial identity schemes and seek to invalidate the internal data collection. Biometric systems that use the face as authentication cause problems with detection or recognition (face or persons). In this research, a novel model has been developed to detect and recognize faces and persons for authentication using scale invariant features (SIFT) for the whole segmented face with an efficient local binary texture features (DLBP) in region of eyes in the masked face. The Fuzzy C means is utilized to segment the image. These mixed features are trained significantly in a convolution neural network (CNN) model. The main advantage of this model is that can detect and recognizing faces by assigning weights to the selected features aimed to grant or provoke permissions with high accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.591-608
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• 2023

With the emergence of advanced encryption technologies such as Quantum Cryptography and Full Disk Encryption, an era of strengthening information security has begun. Users respond positively to the advancement of privacy-enhancing technology, on the other hand, investigative agencies have difficulty unveiling the actual truth as they fail to decrypt devices. In particular, unlike past ciphers, encryption methods using biometric information such as fingerprints, iris, and faces have become common and have faced technical limitations in collecting digital evidence. Accordingly, normative solutions have emerged as a major issue. The United States enacted the CLOUD Act with the legal mechanism of 'Contempt of court' and in 2016, the United Kingdom substantiated the Compelled Decryption through the Investigatory Powers Act (IPA). However, it is difficult to enforce Compelled Decryption on individuals in Korea because Korean is highly sensitive to personal information. Therefore, in this paper, we sought a method of introducing a Compelled Decryption that does not contradict the people's legal sentiment through a perception survey of 95 people on the Compelled Decryption. We tried to compare and review the Budapest Convention with major overseas laws such as the United States and the United Kingdom, and to suggest a direction of legislation acceptable to the people in ways to minimize infringement of privacy. We hope that this study will be an effective legal response plan for law enforcement agencies that can normatively overcome the technical limitations of decoding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1049-1065
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• 2023

Recently, with the development of IoT, AI, and mobile terminals, medical information platforms are expanding. The medical information platform can determine a patient's emergency situation, and medical staff can easily access patient information through a mobile terminal. However, in the existing platform, emergency situation decision is delayed, and faster and stronger authentication is required in emergency situations. Therefore, we propose an edge computing-based medical information platform for automatic authentication using patient situations. We design an edge computing-based medical information platform architecture capable of rapid transmission of biometric data of IoT and quick emergency situation decision, and implement the platform data flow in emergency situations. Relying on this platform, we propose the automatic authentication using patient situations. The automatic authentication protects patient information through patient-centered authentication by using the patient's situation as an authentication factor, and enables quick authentication by automatically proceeding with mobile terminal authentication after user authentication in emergencies without user intervention. We compared the proposed platform with existing platforms to show that it can make quick and stable emergency decisions. In addition, comparing the automatic authentication with existing authentication showed that it is fast and protects medical information centered on patient situations in emergency situations.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.349-354
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• 2014

PIN(Personal Identification Number)-based identification method has been used to identify the user of smart cards. However, this type of identification method has several problems. Firstly, PIN can be forgotten by owners of the card. Secondly, PIN can be used by others illegally. Furthermore, the possibility of hacking PIN can be high because this PIN type matching process is performed on terminal. Thus, in this paper we suggest a new identification method which is performed on smart card using face feature information. The proposed identification method uses low-sized face feature vectors and simple matching algorithm in order to get around the limits in computing capability and memory size of smart card.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.169-178
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• 2017

Recently, as the interest rate and necessity for security is growing, the demands for a visitor recognition system are being increased. In order to recognize a visitor in visitor recognition systems, the various biometric methods are used. In this paper, we propose a visitor recognition system based on face recognition. The visitor recognition system improves the face recognition performance by integrating several open APIs as a single algorithm and by performing the ensemble of the recognition results. For the performance evaluation, we collected the face data for about five months and measured the performance of the visitor recognition system. As the results of the performance measurement, the visitor recognition system shows a higher face recognition rate than using a single face recognition API, meeting the requirements on performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.155-164
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• 2004

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user and is able to doface recognition, which is vital for many surveillance-based systems. The advantage of face recognition compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to the decreasing in dimension from image acquisition step and various changes associated with face pose and background. There are many factors that deteriorate performance of face recognition such as thedistance from camera to the face, changes in lighting, pose change, and change of facial expression. In this paper, we implement a new sliding active camera system to prevent various pose variation that influence face recognition performance andacquired frontal face images using PCA and HMM method to improve the face recognition. This proposed face recognition algorithm can be used for intelligent surveillance system and mobile robot system.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.1-10
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• 2016

Information and network technology become the rapid development, so various online services supplied by multimedia systems are provided through the Internet. Because of intrinsic open characteristic on Internet, network systems need to provide the data protection and the secure authentication. So various researchers including Das, An, and Li&Hwang proposed the biometric-based user authentication scheme but they has some security weakness. To solve their problem, Li et al. proposed new scheme using fuzzy extraction, but it is weak on off-line password attack, authentication without biometrics, denial-of-service and insider attack. So, we proposed security enhanced user authentication scheme with key agreement to address the security problem of authentication schemes.