On Security Analysis of Recent Password Authentication and Key Agreement Schemes Based on Elliptic Curve Cryptography

Secure and efficient mutual authentication and key agreement schemes form the basis for any robust network communication system. Elliptic Curve Cryptography (ECC) has emerged as one of the most successful Public Key Cryptosystem that efficiently meets all the security challenges. Comparison of ECC with other Public Key Cryptosystems (RSA, Rabin, ElGamal) shows that it provides equal level of security for a far smaller bit size, thereby substantially reducing the processing overhead. This makes it suitable for constrained environments like wireless networks and mobile devices as well as for security sensitive applications like electronic banking, financial transactions and smart grids. With the successful implementation of ECC in security applications (e-passports, e-IDs, embedded systems), it is getting widely commercialized. ECC is simple and faster and is therefore emerging as an attractive alternative for providing security in lightweight device, which contributes to its popularity in the present scenario. In this paper, we have analyzed some of the recent password based authentication and key agreement schemes using ECC for various environments. Furthermore, we have carried out security, functionality and performance comparisons of these schemes and found that they are unable to satisfy their claimed security goals

Attribute Based Encryption with Verifiable Time Stamped Decryption

Numerous applications require expanded insurance of private information including access control strategies that are cryptographically authorized. A promising utilization of ABE is adaptable get to control of scrambled information put away in the cloud, utilizing access polices and credited traits related with private keys and ciphertexts. Productivity disadvantages of the current ABE plans is that unscrambling includes costly matching operations and the quantity of such operations develops with the intricacy of the get to approach. The public key generation relying upon the properties of the predetermined content to be encrypted, that will create numerous keys to be utilized to scramble or unscramble the information. Extra private key to be included is the server time stamping with the encryption key to guarantee that the data should not be recovered after particular timeframe. The accompanying paper is depicting a strategies showing how to apply those technique safely and effectively to manage secret data circulated over capacity organize. Security and execution examination demonstrates the proposed plans are provably secure and exceptionally effective

Sharing Data with Secure Advancing ABE method using Timestamp

Numerous applications require expanded insurance of private information including access control strategies that are cryptographically authorized. A promising utilization of ABE is adaptable get to control of scrambled information put away in the cloud, utilizing access polices and credited traits related with private keys and ciphertexts. Productivity disadvantages of the current ABE plans is that unscrambling includes costly matching operations and the quantity of such operations develops with the intricacy of the get to approach. The public key generation relying upon the properties of the predetermined content to be encrypted, that will create numerous keys to be utilized to scramble or unscramble the information. Extra private key to be included is the server time stamping with the encryption key to guarantee that the data should not be recovered after particular timeframe. The accompanying paper is depicting a strategies showing how to apply those technique safely and effectively to manage secret data circulated over capacity organize. Security and execution examination demonstrates the proposed plans are provably secure and exceptionally effective

생물학적 서열 데이터에 대한 표현 학습

학위논문(박사) -- 서울대학교대학원 : 공과대학 전기·정보공학부, 2021.8. 윤성로.As we are living in the era of big data, the biomedical domain is not an exception. With the advent of technologies such as next-generation sequencing, developing methods to capitalize on the explosion of biomedical data is one of the most major challenges in bioinformatics. Representation learning, in particular deep learning, has made significant advancements in diverse fields where the artificial intelligence community has struggled for many years. However, although representation learning has also shown great promises in bioinformatics, it is not a silver bullet. Off-the-shelf applications of representation learning cannot always provide successful results for biological sequence data. There remain full of challenges and opportunities to be explored. This dissertation presents a set of representation learning methods to address three issues in biological sequence data analysis. First, we propose a two-stage training strategy to address throughput and information trade-offs within wet-lab CRISPR-Cpf1 activity experiments. Second, we propose an encoding scheme to model interaction between two sequences for functional microRNA target prediction. Third, we propose a self-supervised pre-training method to bridge the exponentially growing gap between the numbers of unlabeled and labeled protein sequences. In summary, this dissertation proposes a set of representation learning methods that can derive invaluable information from the biological sequence data.우리는 빅데이터의 시대를 맞이하고 있으며, 의생명 분야 또한 예외가 아니다. 차세대 염기서열 분석과 같은 기술들이 도래함에 따라, 폭발적인 의생명 데이터의 증가를 활용하기 위한 방법론의 개발은 생물정보학 분야의 주요 과제 중의 하나이다. 심층 학습을 포함한 표현 학습 기법들은 인공지능 학계가 오랫동안 어려움을 겪어온 다양한 분야에서 상당한 발전을 이루었다. 표현 학습은 생물정보학 분야에서도 많은 가능성을 보여주었다. 하지만 단순한 적용으로는 생물학적 서열 데이터 분석의 성공적인 결과를 항상 얻을 수는 않으며, 여전히 연구가 필요한 많은 문제들이 남아있다. 본 학위논문은 생물학적 서열 데이터 분석과 관련된 세 가지 사안을 해결하기 위해, 표현 학습에 기반한 일련의 방법론들을 제안한다. 첫 번째로, 유전자가위 실험 데이터에 내재된 정보와 수율의 균형에 대처할 수 있는 2단계 학습 기법을 제안한다. 두 번째로, 두 염기 서열 간의 상호 작용을 학습하기 위한 부호화 방식을 제안한다. 세 번째로, 기하급수적으로 증가하는 특징되지 않은 단백질 서열을 활용하기 위한 자기 지도 사전 학습 기법을 제안한다. 요약하자면, 본 학위논문은 생물학적 서열 데이터를 분석하여 중요한 정보를 도출할 수 있는 표현 학습에 기반한 일련의 방법론들을 제안한다.1 Introduction 1 1.1 Motivation 1 1.2 Contents of Dissertation 4 2 Background 8 2.1 Representation Learning 8 2.2 Deep Neural Networks 12 2.2.1 Multi-layer Perceptrons 12 2.2.2 Convolutional Neural Networks 14 2.2.3 Recurrent Neural Networks 16 2.2.4 Transformers 19 2.3 Training of Deep Neural Networks 23 2.4 Representation Learning in Bioinformatics 26 2.5 Biological Sequence Data Analyses 29 2.6 Evaluation Metrics 32 3 CRISPR-Cpf1 Activity Prediction 36 3.1 Methods 39 3.1.1 Model Architecture 39 3.1.2 Training of Seq-deepCpf1 and DeepCpf1 41 3.2 Experiment Results 44 3.2.1 Datasets 44 3.2.2 Baselines 47 3.2.3 Evaluation of Seq-deepCpf1 49 3.2.4 Evaluation of DeepCpf1 51 3.3 Summary 55 4 Functional microRNA Target Prediction 56 4.1 Methods 62 4.1.1 Candidate Target Site Selection 63 4.1.2 Input Encoding 64 4.1.3 Residual Network 67 4.1.4 Post-processing 68 4.2 Experiment Results 70 4.2.1 Datasets 70 4.2.2 Classification of Functional and Non-functional Targets 71 4.2.3 Distinguishing High-functional Targets 73 4.2.4 Ablation Studies 76 4.3 Summary 77 5 Self-supervised Learning of Protein Representations 78 5.1 Methods 83 5.1.1 Pre-training Procedure 83 5.1.2 Fine-tuning Procedure 86 5.1.3 Model Architecturen 87 5.2 Experiment Results 90 5.2.1 Experiment Setup 90 5.2.2 Pre-training Results 92 5.2.3 Fine-tuning Results 93 5.2.4 Comparison with Larger Protein Language Models 97 5.2.5 Ablation Studies 100 5.2.6 Qualitative Interpreatation Analyses 103 5.3 Summary 106 6 Discussion 107 6.1 Challenges and Opportunities 107 7 Conclusion 111 Bibliography 113 Abstract in Korean 130박

Efficient and Provably-secure Certificateless Strong Designated Verifier Signature Scheme without Pairings

Strong designated verifier signature (generally abbreviated to SDVS) allows signers to obtain absolute control over who can verify the signature, while only the designated verifier other than anyone else can verify the validity of a SDVS without being able to transfer the conviction. Certificateless PKC has unique advantages comparing with certificate-based cryptosystems and identity-based PKC, without suffering from key escrow. Motivated by these attractive features, we propose a novel efficient CL-SDVS scheme without bilinear pairings or map-to-point hash operations. The proposed scheme achieves all the required security properties including EUF-CMA, non-transferability, strongness and non-delegatability. We also estimate the computational and communication efficiency. The comparison shows that our scheme outperforms all the previous CL-(S)DVS schemes. Furthermore, the crucial security properties of the CL-SDVS scheme are formally proved based on the intractability of SCDH and ECDL assumptions in random oracle model

Towards an auditable cryptographic access control to high-value sensitive data

We discuss the challenge of achieving an auditable key management for cryptographic access control to high-value sensitive data. In such settings it is important to be able to audit the key management process - and in particular to be able to provide verifiable proofs of key generation. The auditable key management has several possible use cases in both civilian and military world. In particular, the new regulations for protection of sensitive personal data, such as GDPR, introduce strict requirements for handling of personal data and apply a very restrictive definition of what can be considered a personal data. Cryptographic access control for personal data has a potential to become extremely important for preserving industrial ability to innovate, while protecting subject's privacy, especially in the context of widely deployed modern monitoring, tracking and profiling capabilities, that are used by both governmental institutions and high-tech companies. However, in general, an encrypted data is still considered as personal under GDPR and therefore cannot be, e.g., stored or processed in a public cloud or distributed ledger. In our work we propose an identity-based cryptographic framework that ensures confidentiality, availability, integrity of data while potentially remaining compliant with the GDPR framework

Asynchronous distributed private-key generators for identity-based cryptography

An identity-based encryption (IBE) scheme can greatly reduce the complexity of sending encrypted messages over the Internet. However, an IBE scheme necessarily requires a private-key generator (PKG), which can create private keys for clients, and so can passively eavesdrop on all encrypted communications. Although a distributed PKG has been suggested as a way to mitigate this problem for Boneh and Franklin’s IBE scheme, the security of this distributed protocol has not been proven and the proposed solution does not work over the asynchronous Internet. Further, a distributed PKG has not been considered for any other IBE scheme. In this paper, we design distributed PKG setup and private key extraction protocols in an asynchronous communication model for three important IBE schemes; namely, Boneh and Franklin’s IBE, Sakai and Kasahara’s IBE, and Boneh and Boyen’s BB1-IBE. We give special attention to the applicability of our protocols to all possible types of bilinear pairings and prove their IND-ID-CCA security in the random oracle model. Finally, we also perform a comparative analysis of these protocols and present recommendations for their use.

Chosen-Ciphertext Secure Proxy Re-Encryption without Pairing

Office of Research, Singapore Management Universit

A New Practical Identity-Based Encryption System

We present a new practical Identity-Based Encryption (IBE) system that can be another candidate for standard IBE techniques. Our construction is based on a new framework for realizing an IBE trapdoor from pairing-based groups, which is motivated from the `two equation\u27 revocation technique suggested by Lewko, Sahai, and Waters. The new framework enables our IBE system to achieve a tight security reduction to the Decision Bilinear Diffie-Hellman assumption. Due to its the tightness, our system can take as input the shorter size of security parameters than the previous practical BF, SK, and BB$_{1}$ systems, which provides better efficiency to our system in terms of computational cost. With appropriate parametrization at 80-bit security level (considering security loss), our IBE system can obtain 11 times faster decryption than the previous ones and 77 times faster encryption than the BF system. We prove that our system is fully secure against chosen ciphertext attacks in the random oracle model. From computational variant of Naor\u27s observation, we can also suggest a new signature scheme that features a tight security reduction to the Computational Diffie-Hellman assumption and provides strong unforgeability simultaneously