Presentation Attacks in Palmprint Recognition Systems

Yue Sun,Changkun Wang 한국멀티미디어학회 2022 The journal of multimedia information system Vol.9 No.2

Background: A presentation attack places the printed image or displayed video at the front of the sensor to deceive the biometric recognition system. Usually, presentation attackers steal a genuine user’s biometric image and use it for presentation attack. In recent years, reconstruction attack and adversarial attack can generate high-quality fake images, and have high attack success rates. However, their attack rates degrade remarkably after image shooting. Methods: In order to comprehensively analyze the threat of presentation attack to palmprint recognition system, this paper makes six palmprint presentation attack datasets. The datasets were tested on texture coding-based recognition methods and deep learning-based recognition methods. Results and conclusion: The experimental results show that the presentation attack caused by the leakage of the original image has a high success rate and a great threat; while the success rates of reconstruction attack and adversarial attack decrease significantly.

딥러닝 기반의 알려진 평문 공격을 통한 S-PRESENT 분석

임세진(Se-jin Lim),김현지(Hyun-Ji Kim),장경배(Kyung-Bae Jang),강예준(Yea-jun Kang),김원웅(Won-Woong Kim),양유진(Yu-Jin Yang),서화정(Hwa-Jeong Seo) 한국정보보호학회 2023 정보보호학회논문지 Vol.33 No.2

암호 분석은 알려진 평문 공격, 차분 분석, 부채널 분석 등과 같이 다양한 기법으로 수행될 수 있다. 최근에는 딥러닝을 암호 분석에 적용하는 연구들이 제안되고 있다. 알려진 평문 공격(Known-plaintext Attack)은 알려진 평문과 암호문 쌍을 사용하여 키를 알아내는 암호 분석 기법이다. 본 논문에서는 딥러닝 기술을 사용하여 경량 블록암호 PRESENT의 축소 버전인 S-PRESENT에 대해 알려진 평문 공격을 수행한다. 축소된 경량 블록 암호에 대해 수행된 최초의 딥러닝 기반의 알려진 평문 공격이라는 점에서 본 논문은 의의가 있다. 성능 향상 및 학습속도 개선을 위해 Skip connection, 1x1 Convolution과 같은 딥러닝 기법을 적용하였다. 암호 분석에는 MLP(Multi-Layer Perceptron)와 1D, 2D 합성곱 신경망 모델을 사용하여 최적화하였으며, 세 모델의 성능을 비교한다. 2D 합성곱 신경망에서 가장 높은 성능을 보였지만 일부 키공간까지만 공격이 가능했다. 이를 통해 MLP모델과 합성곱 신경망을 통한 알려진 평문 공격은 공격 가능한 키 비트에 제한이 있음을 알 수 있다. Cryptanalysis can be performed by various techniques such as known plaintext attack, differential attack, side-channel analysis, and the like. Recently, many studies have been conducted on cryptanalysis using deep learning. A known-plaintext attack is a technique that uses a known plaintext and ciphertext pair to find a key. In this paper, we use deep learning technology to perform a known-plaintext attack against S-PRESENT, a reduced version of the lightweight block cipher PRESENT. This paper is significant in that it is the first known-plaintext attack based on deep learning performed on a reduced lightweight block cipher. For cryptanalysis, MLP (Multi-Layer Perceptron) and 1D and 2D CNN(Convolutional Neural Network) models are used and optimized, and the performance of the three models is compared. It showed the highest performance in 2D convolutional neural networks, but it was possible to attack only up to some key spaces. From this, it can be seen that the known-plaintext attack through the MLP model and the convolutional neural network is limited in attackable key bits.

비트 순열 기반 블록암호의 비선형 불변 공격저항성 연구

정건상,김성겸,홍득조,성재철,홍석희 한국정보보호학회 2020 정보보호학회논문지 Vol.30 No.3

Nonlinear Invariant Attack is an attack that should be considered when constructing lightweight block ciphers withrelatively simple key schedule. A shortcut to prove a block cipher’s resistance against nonlinear invariant attack is checkingthe smallest dimension of linear layer-invariant linear subspace which contains all known differences between round keys isequal to the block size. In this paper, we presents the following results. We identify the structure and number of optimalbit-permutations which require only one known difference between round keys for a designer to show that the correspondingblock cipher is resistant against nonlinear invariant attack. Moreover, we show that PRESENT-like block ciphers need atleast two known differences between round keys by checking all PRESENT-like bit-permutations. Additionally, we verify that the variants of PRESENT-like bit-permutations requiring the only two known differences between round keys do not conflictwith the resistance against differential attack by comparing the best differential trails. Finally, through the distribution of theinvariant factors of all bit-permutations that maintain BOGI logic with GIFT S-box, GIFT-variant block ciphers require atleast 8 known differences between round keys for the resistance. 비선형 불변 공격은 비교적 간단한 구조의 키 스케줄을 갖는 경량 블록암호에서 필수적으로 고려되어야 할 공격이다. 간단한 구조의 키 스케줄을 갖는 경량 블록암호가 비선형 불변 공격에 저항성을 보이는 방법으로 가장 잘 알려진 것은 라운드 키 간의 차분 중 알려진 것들의 집합에서 선형계층에 대해 불변인 최소의 선형공간의 크기가 블록크기와 같은지를 확인하는 것이다. 본 논문에서는 다음과 같은 연구 결과를 제시한다. 설계자 관점에서 비트 순열을선형계층으로 사용하는 SPN 구조 경량 블록암호는 라운드 키 간의 차분의 종류가 한가지여도 비선형 불변 공격에안전할 수 있음을 증명하고, 그러한 비트 순열의 형태와 개수를 제안한다. 또한, PRESENT 구조 블록암호는 비선형 불변 공격에 저항성을 갖기 위해 적어도 두 종류의 라운드 키 간의 차분이 필요함을 전수조사를 통해 보이며, 두종류의 라운드 키 간의 차분을 필요로 하는 비트 순열을 사용해도 차분 공격에 대한 저항성이 오히려 증가할 수 있음을 보인다. 마지막으로 GIFT의 S-box를 사용하면서 BOGI 설계 논리를 유지하는 모든 비트 순열의 불변 성분분포를 통해, 변형된 GIFT 구조 블록암호는 비선형 불변 공격에 저항성을 갖기 위해 적어도 8종류의 라운드 키 간의 차분이 필요함을 보인다.

홍채 표현 공격 탐지(Iris PAD)에 강인한 위조 홍채인식 방어 시스템에 관한 연구

백영현 대한전자공학회 2023 전자공학회논문지 Vol.60 No.1

Iris presentation attack detection (PAD) technology plays an important role in enhancing the security of access control systems that use iris recognition among biometric access authentication facilities. This study examines a fake iris recognition defense system that provides a strong defense against fake iris recognition attacks. Accurate pupil region detection through preprocessing is required to reduce errors when implementing PAD for identifying a fake iris. Iris PAD was designed to analyze whether instructions were implemented according to random blink attempts by an administrator and to determine the number of blinks and the presence or absence of the pupil in a given period. In a simulation, the pupil region of the iris of 100 was accurately detected in an external light environment. The experimental results showed that the proposed method accurately detected a fake iris.

Presentation Attack Detection (PAD) for Iris Recognition System on Mobile Devices-A Survey

Motwakel, Abdelwahed,Hilal, Anwer Mustafa,Hamza, Manar Ahmed,Ghoneim, Hesham E. International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.12

The implementation of iris biometrics on smartphone devices has recently become an emerging research topic. As the use of iris biometrics on smartphone devices becomes more widely adopted, it is to be expected that there will be similar efforts in the research community to beat the biometric by exploring new spoofing methods and this will drive a corresponding requirement for new liveness detection methods. In this paper we addresses the problem of presentation attacks (Spoofing) against the Iris Recognition System on mobile devices and propose novel Presentation Attack Detection (PAD) method which suitable for mobile environment.

Presentation Attack Detection (PAD) for Iris Recognition System on Mobile Devices-A Survey

Motwakel, Abdelwahed,Hilal, Anwer Mustafa,Hamza, Manar Ahmed,Ghoneim, Hesham E. International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.spc12

The implementation of iris biometrics on smartphone devices has recently become an emerging research topic. As the use of iris biometrics on smartphone devices becomes more widely adopted, it is to be expected that there will be similar efforts in the research community to beat the biometric by exploring new spoofing methods and this will drive a corresponding requirement for new liveness detection methods. In this paper we addresses the problem of presentation attacks (Spoofing) against the Iris Recognition System on mobile devices and propose novel Presentation Attack Detection (PAD) method which suitable for mobile environment.

Multi-modal Authentication Using Score Fusion of ECG and Fingerprints

권영빈,김재성 한국정보통신학회 2020 Journal of information and communication convergen Vol.18 No.2

Biometric technologies have become widely available in many different fields. However, biometric technologies using existing physical features such as fingerprints, facial features, irises, and veins must consider forgery and alterations targeting them through fraudulent physical characteristics such as fake fingerprints. Thus, a trend toward next-generation biometric technologies using behavioral biometrics of a living person, such as bio-signals and walking characteristics, has emerged. Accordingly, in this study, we developed a bio-signal authentication algorithm using electrocardiogram (ECG) signals, which are the most uniquely identifiable form of bio-signal available. When using ECG signals with our system, the personal identification and authentication accuracy are approximately 90% during a state of rest. When using fingerprints alone, the equal error rate (EER) is 0.243%; however, when fusing the scores of both the ECG signal and fingerprints, the EER decreases to 0.113% on average. In addition, as a function of detecting a presentation attack on a mobile phone, a method for rejecting a transaction when a fake fingerprint is applied was successfully implemented.

A Comprehensive Study on Key Components of Grayscale-based Deepfake Detection

Seok Bin Son,박성희,이윤규 한국인터넷정보학회 2024 KSII Transactions on Internet and Information Syst Vol.18 No.8

Advances in deep learning technology have enabled the generation of more realistic deepfakes, which not only endanger individuals’ identities but also exploit vulnerabilities in face recognition systems. The majority of existing deepfake detection methods have primarily focused on RGB-based analysis, offering unreliable performance in terms of detection accuracy and time. To address the issue, a grayscale-based deepfake detection method has recently been proposed. This method significantly reduces detection time while providing comparable accuracy to RGB-based methods. However, despite its significant effectiveness, the “key components” that directly affect the performance of grayscale-based deepfake detection have not been systematically analyzed. In this paper, we target three key components: RGB-to-grayscale conversion method, brightness level in grayscale, and resolution level in grayscale. To analyze their impacts on the performance of grayscale-based deepfake detection, we conducted comprehensive evaluations, including component-wise analysis and comparative analysis using real-world datasets. For each key component, we quantitatively analyzed its characteristics’ performance and identified differences between them. Moreover, we successfully verified the effectiveness of an optimal combination of the key components by comparing it with existing deepfake detection methods.

패치기반 컨볼루션 뉴럴 네트워크 특징을 이용한 위조지문 검출

박은수(Eunsoo Park),김원진(Weonjin Kim),이경수(Qiongxiu Li),김정민(Jungmin Kim),김학일(Hakil Kim) 한국정보보호학회 2017 정보보호학회논문지 Vol.27 No.1

최근 모바일 기기에서의 생체인증 시스템의 증가와 출입관리 시스템에서의 위조지문을 이용한 출입 기록 조작으로 인해 위조 지문 검출에 대한 논의가 다시 활발해지고 있다. 본 논문에서는 입력 지문영상을 패치들로 나누고, 각 패치들에 CNN을 적용하여 위조, 생체, 배경의 세 가지로 분류한다. 이 중 배경으로 분류된 패치들을 제외하고 위조와 생체로 분류된 패치들의 수를 세어서 더 많은 패치가 인식된 쪽으로 위조여부를 판단하게 된다. CNN에 배경 클래스를 추가하여 분류하기 때문에, 제안하는 방법은 영상분할과 같은 추가적인 전처리 과정이 필요하지 않다. 제안하는 방법은 LivDet2011, LivDet2013, LivDet2015에 대하여 실험을 진행하였으며 분류결과 3.06%의 평균 오검출을 보여 매우 우수한 성능을 나타냄을 확인하였다. Nowadays, there have been an increasing number of illegal use cases where people try to fabricate the working hours by using fake fingerprints. So, the fingerprint liveness detection techniques have been actively studied and widely demanded in various applications. This paper proposes a new method to detect fake fingerprints using CNN (Convolutional Neural Ntworks) based on the patches of fingerprint images. Fingerprint image is divided into small square sized patches and each patch is classified as live, fake, or background by the CNN. Finally, the fingerprint image is classified into either live or fake based on the voting result between the numbers of fake and live patches. The proposed method does not need preprocessing steps such as segmentation because it includes the background class in the patch classification. This method shows promising results of 3.06% average classification errors on LivDet2011, LivDet2013 and LivDet2015 dataset.

구비설화 속 일생의례 관련 속신(俗信)의 양상과 의식체계

유경자 한국구비문학회 2023 口碑文學硏究 Vol.- No.68

This article examines the aspect and consciousness system of folk beliefs implied in the lifetime ritual found in oral tales. In the story of Sanyukrye, which presents rituals of birthing and raising children, the weak social position of a girl and desire for a talented son are revealed in gija(wish for a son) and the dream of conception. Gija normally involves folk beliefs of devout prayer: that devout prayer for boys leads to talent, but devout prayer for girls leads to disasters. In the conception dream, the dream of a dragon dominates and is revealed as a wish to acquire a talented son. This wish leads to the longevity of the born child, best revealed through the folk beliefs in discourse. Similarly, the wedding story contains the private seeking for self-rescue for the perfect union of couples starting a new life, as well as the wish for the peace of the community. This is best revealed through the folk belief that if a person does not peek into the bridal room, a ghost will and cause the death of the bride. This folk belief secures the legitimacy of the voyeur in the bridal room by inducing the community's interest and efforts toward the perfect union of the bride and groom, who are ignorant of sex, to intervene. Stories of funeral and ancestral rites reflect thoughts related to the present world and belief in reincarnation. The connection with the present world is well established in the fact that, even after death, ancestors survive through the food offered by their descendants as an ancestral rite, and have the authority to intervene and influence the lives of their descendants as members of the family community, and are bound by customs of the living world in the next world as well. These thoughts are embodied through folk belief, where belief in reincarnation is most evident in the behavior of the people who try to confirm the reality of the reincarnation of their ancestors.