Kyoto University · Computer Science
Naveed Ahmed Azam 교수의 연구실은 암호학 및 분자생물정보학 분야에서 탄탄한 연구 기반을 구축하고 있습니다. 주로 타원곡선 기반 암호화 기법을 활용해 고성능·경량화된 S-박스 생성 및 이미지 암호화 기술을 개발하며, 특히 유한환 위의 타원곡선을 응용한 보안성 높은 암호 시스템에 초점을 맞추고 있습니다. 또한, 화학 구조 분석과 약물 설계에 응용되는 역양적 QSAR/QSPR 기반의 그래프 기반 분석 프레임워크 개발도 진행 중입니다. 연구는 실용성과 보안성, 계산 효율성을 동시에 확보하는 데 목적이 있습니다.
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Elliptic curves (ECs) are considered as one of the highly secure structures against modern computational attacks. In this paper, we present an efficient method based on an ordered isomorphic EC for the generation of a large number of distinct, mutually uncorrelated, and cryptographically strong injective S-boxes. The proposed scheme is characterized in terms of time complexity and the number of the distinct S-boxes. Furthermore, rigorous analysis and comparison of the newly developed method with
Image encryption based on elliptic curves (ECs) is emerging as a new trend in cryptography because it provides high security with a relatively smaller key size when compared with well-known cryptosystems. Recently, it has been shown that the cryptosystems based on ECs over finite rings may provide better security because they require the computational cost for solving the factorization problem and the discrete logarithm problem. Motivated by this fact, we proposed a novel image encryption scheme
Recently, highly dynamic substitution box (S-box) generators are widely used in cryptosystems to improve the security against modern computational attacks. However, generating S-boxes is computationally costly, and frequently generating them slows down the encryption process and hence limits the encryption throughput. This fact necessitates developing new S-box generators that can provide optimal security with minimum computation cost. We propose a novel S-box generator based on a deterministic
Developing a substitution-box (S-box) generator that can efficiently generate a highly dynamic S-box with good cryptographic properties is a hot topic in the field of cryptography. Recently, elliptic curve (EC)-based S-box generators have shown promising results. However, these generators use large ECs to generate highly dynamic S-boxes and thus may not be suitable for lightweight cryptography, where the computational power is limited. The aim of this paper is to develop and implement such an S-
This paper presents a novel image encryption technique based on multiple right translated AES Gray S-boxes (RTSs) and phase embedding technique. First of all, a secret image is diffused with a fuzzily selected RTS. The fuzzy selection of RTS is variable and depends upon pixels of the secret image. Then two random masks are used to enhance confusion in the spatial and frequency domains of the diffused secret image. These random masks are generated by applying two different RTSs on a host image. T
Analysis of chemical graphs is becoming a major research topic in computational molecular biology due to its potential applications to drug design. One of the major approaches in such a study is inverse quantitative structure activity/property relationship (inverse QSAR/QSPR) analysis, which is to infer chemical structures from given chemical activities/properties. Recently, a novel two-phase framework has been proposed for inverse QSAR/QSPR, where in the first phase an artificial neural network
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