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We propose a novel computer architectural concept of instruction overloading to support block ciphers. Instead of adding new instructions, we extend only the execution of some existing instructions. The proposed method allows a central processing unit core to execute different operations for the same instructions, depending on the address of the data, similar to operator overloading in object-oriented languages. We first present an extension for the AES algorithm, then we demonstrate its enhanced applicability with two further extensions supporting multiple block ciphers and hardware masking. The first extension for AES is also applicable to add/AND-rotate-XOR-based block ciphers such as SIMON. The AES and SIMON encryption speed, on this extended core, is at least doubled and is significantly less affected by memory latency. In addition, the AES encryption code requires only 18% of the memory of the previous software implementation. The second extension can further support various block ciphers defined over GF(28), and the SM4 encryption speed is increased by at least 182%. The third extension provides correlation power analysis (CPA) resistance with a 66.6% area overhead but almost no speed overhead, whereas a typical software anti-CPA AES implementation requires at least hundreds of times the execution time.

Autonomous driving and its real-world implementation have been among the most actively studied topics in the past few years. In recent years, this growth has been accelerated by the development of advanced deep learning-based data processing technologies. Moreover, large automakers manufacture vehicles that can achieve partially or fully autonomous driving for driving on real roads. However, self-driving cars are limited to some areas with multi-lane roads, such as highways, and self-driving cars that drive in urban areas or residential complexes are still in the development stage. Among autonomous vehicles for various purposes, this paper focused on the development of autonomous vehicles for garbage collection in residential areas. Since we set the target environment of the vehicle as a residential complex, there is a difference from the target environment of a general autonomous vehicle. Therefore, in this paper, we defined ODD, including vehicle length, speed, and driving conditions for the development vehicle to drive in a residential area. In addition, to recognize the vehicle’s surroundings and respond to various situations, it is equipped with various sensors and additional devices that can notify the outside of the vehicle’s state or operate it in an emergency. In addition, an autonomous driving system capable of object recognition, lane recognition, route planning, vehicle manipulation, and abnormal situation detection was configured to suit the vehicle hardware and driving environment configured in this way. Finally, by performing autonomous driving in the actual experimental section with the developed vehicle, it was confirmed that the function of autonomous driving in the residential area works appropriately. Moreover, we confirmed that this vehicle would support garbage collection works through the experiment of work efficiency.

Montgomery reduction is a well-known optimization technique for modular reduction over prime fields. However, it has rarely been used for national institute of standards and technology (NIST) prime fields, because the special structure of NIST primes enables fast reduction that requires fewer computations than Montgomery reduction. In this study, we rediscover the Montgomery reduction for NIST primes and propose a new modular reduction method by applying partial modular reduction to Montgomery reduction. Using this new modular reduction method and other optimization techniques, such as pipelining and parallel processing, we propose an efficient elliptic curve cryptography (ECC) coprocessor over NIST prime fields. The implementation results indicate that the proposed coprocessor can perform one elliptic curve point multiplication in 0.055 ms with only 194.7 k gate counts. This is a considerably higher speed per area compared to previous research.

Quantum computing is a game-changing technology that affects modern cryptography and security systems including distributed energy resources (DERs) systems. Since the new quantum era is coming soon in 5–10 years, it is crucial to prepare and develop quantum-safe DER systems. This paper provides a comprehensive review of vulnerabilities caused by quantum computing attacks, potential defense strategies, and remaining challenges for DER networks. First, new security vulnerabilities and attack models of the cyber-physical DER systems caused by quantum computing attacks are explored. Moreover, this paper introduces potential quantum attack defense strategies including Quantum Key Distribution (QKD) and Post-Quantum Cryptography (PQC), which can be applied to DER networks and evaluates defense strategies. Finally, remaining research opportunities and challenges for next-generation quantum-safe DER are discussed.

In 2020 and 2021, humanity lived in fear due to the COVID-19 pandemic. However, with the development of artificial intelligence technology, mankind is attempting to tackle many challenges from currently unpredictable epidemics. Korean society has been exposed to various infectious diseases since the Korean War in 1950, and to overcome them, the six most serious cases in National Notifiable Infectious Diseases (NNIDs) category I were defined. Although most infectious diseases have been overcome, viral hepatitis A has been on the rise in Korean society since 2010. Therefore, in this paper, the prediction of viral hepatitis A, which is rapidly spreading in Korean society, was predicted by region using the deep learning technique and a publicly available dataset. For this study, we gathered information from five organizations based on the open data policy: Korea Centers for Disease Control and Prevention (KCDC), National Institute of Environmental Research (NIER), Korea Meteorological Agency (KMA), Public Open Data Portal, and Korea Environment Corporation (KECO). Patient information, water environment information, weather information, population information, and air pollution information were acquired and correlations were identified. Next, an epidemic outbreak prediction was performed using data preprocessing and 3D LSTM. The experimental results were compared with various machine learning methods through RMSE. In this paper, we attempted to predict regional epidemic outbreaks of hepatitis A by linking the open data environment with deep learning. It is expected that the experimental process and results will be used to present the importance and usefulness of establishing an open data environment.

We propose a privacy-preserving face authentication system for smartphones that guarantees security against malicious clients. Using the proposed system, a face feature vector is stored on a remote server in encrypted form. To guarantee security against an honest-but-curious server who may try to learn the private feature vector, we perform a Euclidean distance-based matching score computation on encrypted feature vectors using homomorphic encryption. To provide security against malicious clients, we adopt a blinding technique. We implement the proposed system on a mobile client and a desktop server. Through an experiment with real-world participants, we demonstrate that secure face verification can be completed in real time (within 1.3 s) even when a smartphone is involved, with an Equal Error Rate (EER) of 3.04%. In further experiments with two public face datasets, CFP and ORL, face verification is completed in approximately 1 s with EER of 1.17% and 0.37%, respectively. Our system is two orders of magnitude faster than previous privacy-preserving face verification method with the same security assumptions and functionalities. To achieve this secure real-time computation, we improve the Catalano-Fiore transformation which converts a linear homomorphic encryption scheme into a quadratic scheme, and parallelize the decryption procedure of our system.

NTRUEncrypt is a public key cryptosystem based on hard problems over lattices. The dominant operation in NTRUEncrypt is convolution, i.e., multiplication over a quotient ring of polynomials. Based on the fact that a convolution has a highly regular structure, Lee et al. proposed the sliding window method for fast convolution of binary polynomials in 2013, which was then extended to ternary polynomials for ideal lattices by Akleylek, Alkim, and Tok in 2016. These sliding window methods reduce the cost of a convolution operation using look-up tables that store partial computation results related to repeated coefficient patterns. In this paper, we propose a signed sliding window method with side-channel resistance for NTRUEncrypt. The proposed method considers both positive and negative nonzero coefficients when constructing look-up tables. The new method not only accelerates convolution but also enables the application of power analysis countermeasures effectively. According to the experimental results, the constant-time implementation of the proposed method with timing and power analysis countermeasures accelerates the previously developed secure convolution method by up to 20%.

In many bandwidth-critical environments, including vehicle-to-vehicle and vehicle-to-infrastructure communications, implicit certificates such as elliptic curve Qu-Vanstone (ECQV) are frequently employed as a means to reduce the bandwidth requirement of digital signatures. In these environments, however, certain recipients such as roadside units need to verify signatures for multiple messages within considerably short time periods. In this paper, we propose two efficient methods of reducing the computational costs of signature verification when multiple digital signatures are provided together with the ECQV implicit certificates. The first method achieves this by sharing the intermediate results that are computed when public keys are extracted from ECQV certificates. The second guarantees a further speed improvement by merging the public key extraction processes into a batch signature verification process. We also present an algorithm that adaptively chooses the best verification method for the given signatures in real time. Our experimental results show that the proposed methods allow for a signature verification that is five times faster than existing methods.

With the recent advances in mobile technologies, biometric verification is being adopted in many smart devices as a means for authenticating their owners. As biometric data leakage may cause stringent privacy issues, many proposals have been offered to guarantee the security of stored biometric data, i.e., biometric template. One of the most promising solutions is the use of a remote server that stores the template in an encrypted form and performs a biometric comparison on the ciphertext domain, using recently proposed functional encryption (FE) techniques. However, the drawback of this approach is that considerable computation is required for the inner-pairing product operation used for the decryption procedure of the underlying FE, which is performed in the authentication phase. In this paper, we propose an enhanced method to accelerate the inner-pairing product computation and apply it to expedite the decryption operation of FE and for faster remote biometric verification. The following two important observations are the basis for our improvement—one of the two arguments for the decryption operation does not frequently change over authentication sessions, and we only need to evaluate the product of multiple pairings, rather than individual pairings. From the results of our experiments, the proposed method reduces the time required to compute an inner-pairing product by 30.7%, compared to the previous best method. With this improvement, the time required for biometric verification is expected to decrease by up to 10.0%, compared to a naive method.

The rapidly increasing expansion of distributed energy resources (DER), such as renewable energy systems and energy storage systems into the electric power system and the integration of advanced information and communication technologies enable DER owners to participate in the electricity market for grid services. For more efficient and reliable power system operation, the concept of peer-to-peer (P2P) energy trading has recently been proposed. The adoption of blockchain technology in P2P energy trading has been considered to be the most promising solution enabling secure smart contracts between prosumers and users. However, privacy concerns arise because the sensitive data and transaction records of the participants, i.e., the prosumers and the distribution system operator (DSO), become available to the blockchain nodes. Many efforts have been made to resolve this issue. A recent breakthrough in a P2P energy trading system on an Ethereum blockchain is that all bid values are encrypted using functional encryption and peer matching for trading is performed securely on these encrypted bids. Their protocol is based on a method that encodes integers to vectors and an algorithm that securely compares the ciphertexts of these vectors. However, the comparison method is not very efficient in terms of the range of possible bid values because the amount of computation grows linearly according to the size of this range. This paper addresses this challenge by proposing a new bid encoding algorithm called dual binary encoding, which dramatically reduces the amount of computation as it is only proportional to the square of the logarithm of the size of the encoding range. Moreover, we propose a practical mechanism for rebidding the remaining amount caused when the amounts from the two matching peers are not equal. Finally, the feasibility of the proposed method is evaluated by using a virtual energy trade testbed and a private Ethereum blockchain platform.

We proposed a high-performance elliptic curve cryptography (ECC) processor over NIST prime fields. Instead of applying a full modular reduction to a $2{k}$ -bit product, the proposed partial modular reduction method iteratively performs reductions on partial products whose bit length is slightly greater than ${k}$ , where ${k}$ is the bit length of field elements. As a result, the computational complexity of modular multiplication (MM) was significantly reduced. Moreover, the amount of computation is configurable by parameterizing the size of the partial products. This is a very desirable characteristic of the proposed ECC processor, because the hardware complexity and processing time of the entire ECC processor can be adjusted according to the requirements of various Internet of Things environments. Including the proposed MM module, finite field operation modules are integrated into a single module to further reduce the required resources. The proposed ECC processor synthesized using 180-nm CMOS process technology can perform a 256-bit elliptic curve point multiplication in 0.20–0.74 ms with 144.8k–65.4k gate counts. These results and the experimental results in various FPGA devices show that the proposed ECC processor has significantly better throughput per area than the previously reported ones.

We present a new Personal Identification Number (PIN) entry method for smartphones that can be used in security-critical applications, such as smartphone banking. The proposed “Two-Thumbs-Up” (TTU) scheme is resilient against observation attacks such as shoulder-surfing and camera recording, and guides users to protect their PIN information from eavesdropping by shielding the challenge area on the touch screen. To demonstrate the feasibility of TTU, we conducted a user study for TTU, and compared it with existing authentication methods (Normal PIN, Black and White PIN, and ColorPIN) in terms of usability and security. The study results demonstrate that TTU is more secure than other PIN entry methods in the presence of an observer recording multiple authentication sessions.

Advanced smart grid technologies enable energy prosumers to trade surplus energy from their distributed renewable energy sources with other peer prosumers through peer-to-peer (P2P) energy trading. In many previous works, P2P energy trading was facilitated by blockchain technology through blockchain’s distributive nature and capacity to run smart contracts. However, the feature that all the data and transactions on a blockchain are visible to all blockchain nodes may significantly threaten the privacy of the parties participating in P2P energy trading. There are many previous works that have attempted to mitigate this problem. However, all these works focused on the anonymity of participants but did not protect the data and transactions. To address this issue, we propose a P2P energy trading system on a blockchain where all bids are encrypted and peer matching is performed on the encrypted bids by a functional encryption-based smart contract. The system guarantees that the information encoded in the encrypted bids is protected, but the peer matching transactions are performed by the nodes in a publicly verifiable manner through smart contracts. We verify the feasibility of the proposed system by implementing a prototype composed of smart meters, a distribution system operator (DSO) server, and private Ethereum blockchain.

The biggest cause of the epidemic is “unpredictable.” In Korea, the number of patients with hepatitis A has been increasing recently, and the government enacted a law in 1954 to effectively manage diseases such as hepatitis A. The purpose of this paper is to design a model for predicting trends in order to minimize the damage caused by the prevalence of infectious diseases. As a tool for it, various statistical techniques and Supervised Learning of Machine Learning and LSTM techniques were used. To this end, data were collected using Web Crawling and other data, correlation analysis using Regression analysis was conducted, and prediction models were designed using Machine Learning and LSTM.

The development of smart meters that can frequently measure and report power consumption has enabledelectricity providers to offer various time-varying rates, including time-of-use and real-time pricing plans. High-resolution power consumption data, however, raise serious privacy concerns because sensitive information regarding an individual’s lifestyle can be revealed by analyzing these data. Although extensive research has been conducted to address these privacy concerns, previous approaches have reduced the quality of measured data. In this paper, we propose a new privacy-preserving electricity billing method that does not sacrifice data quality for privacy. The proposed method is based on the novel use of functional encryption. Experimental results on a prototype system using a real-world smart meter device and data prove the feasibility of the proposed method.

The Small Exponent Test (SET) for exponentiation is an essential batch-verification technique that is widely applied. In this paper, we propose a simplified SET that can securely batch-verify n instances with only n − 1 randomizing exponents. We show that the structure of the proposed batch test is compact in the sense that it works with a minimal number of randomizing exponents for the SET. Thus, our test offers various advantages. Overall, compared to the original SET, the proposed simplified SET is more efficient for any sized batch instance. In particular, unlike the SET, our proposal performs well even when the size of a batch instance is small, e.g., n = 1 , 2 , 3 , and 4. This feature can be also used to significantly reduce pairing computations in a signature scheme where several pairing equations are verified. In addition, our test can be combined easily and generically with existing batch techniques such as the use of sparse exponents, the bucket test for large batch sizes, or an automated tool to generate a batch algorithm. Finally, with our simplified test, an efficient identification algorithm can be constructed to discover incorrect instances in a batch.

User authentication is a process in which a user of a system proves his/her identity to acquire access permission. An effective user authentication method should be both secure and usable. In an attempt to achieve these two objectives, Bianchi et al. recently proposed novel unimodal PIN-entry methods that use either audio or vibration cues. This paper analyzes the security of their method, in particular, the vibration version of one of their proposals, Timelock. A probabilistic analysis and real attack experiment reveal that the security level guaranteed by Timelock is lower than that claimed in Bianchi et al.’s paper. As countermeasures to this problem, three PIN-entry methods are proposed and a usability study is performed. According to the result of this study, a simple modification may improve the security significantly while retaining the design philosophy of unimodal systems. In addition, the proposed methods address the PIN compatibility issue of Timelock and they can be used to enter a legacy numerical PIN without any change in the PIN.

We present an efficient hardware prime generator that generates a prime p by combining trial division and Fermat test in parallel. Since the execution time of this parallel combination is greatly influenced by the number k of the smallest odd primes used in the trial division, it is important to determine the optimal k to create the fastest parallel combination. We present probabilistic analysis to determine the optimal k and to estimate the expected running time for the parallel combination. Our analysis is conducted in two stages. First, we roughly narrow the range of optimal k by using the expected values for the random variables used in the analysis. Second, we precisely determine the optimal k by using the exact probability distribution of the random variables. Our experiments show that the optimal k and the expected running time determined by our analysis are precise and accurate. Furthermore, we generalize our analysis and propose a guideline for a designer of a hardware prime generator to determine the optimal k by simply calculating the ratio of M to D, where M and D are the measured running times of a modular multiplication and an integer division, respectively.

Fast growth of smartphone technology and advent of Fintech enabled smartphones to deal with more sensitive information. Although many devices applying biometric technology are released as a step for protecting sensitive information securely, there can be potential vulnerabilities if security is not considered at the design stage of a biometric system. By analyzing the potential vulnerabilities, we classify threats in biometric system design process on smartphones and we propose the design requirements for solving these problems. In addition, we propose a framework for secure biometric system design on smartphone by synthesizing the design requirements.Keywords:Biometrics, Smartphone Security, System Design Requirement, Framework 스마트폰 상의 안전한 바이오인식 시스템 설계를 위한 프레임워크 임 종 혁 † ⋅권 희 용 †† ⋅이 문 규 ††† 요 약 최근 스마트폰 기술의 빠른 발전과 핀테크의 등장으로 스마트폰은 더욱 많은 민감한 정보를 다루게 되었다. 이 같은 민감한 정보를 안전하게 보호하는 수단으로 바이오인식 기술이 적용된 다양한 기기들이 출시되고 있으나, 바이오인식 시스템 설계 시 보안을 고려하지 않을 경우 잠재적인 취약점이 존재할 수 있다. 이에 본 논문에서는 잠재적인 취약점의 분석을 통해 스마트폰 상의 바이오인식 시스템 설계 과정에서 주의할 점을 분류하고, 이를 해결하기 위한 설계 요구사항을 제시한다. 또한, 설계 요구사항을 종합하여 안전한 스마트폰 바이오인식 시스템 설계를 위한 프레임워크를 제시한다.키워드:바이오인식, 스마트폰 보안, 시스템 설계 요구사항, 프레임워크

A Personal Identification Number (PIN) is a multiple-digit sequence widely used for user authentication. It is desirable for a PIN-entry method to be secure against two main security threats, random guessing attacks and recording attacks. Although there have been many proposals for challenge-response-based PIN-entry methods, it is well known that the only way to prevent both attacks is to physically prevent attackers from observing the challenge-response pairs, which motivates the development of PIN-entry methods that use secure secondary channels such as audio signals. To provide a guideline for designing an audio-based PIN-entry method, we propose a simple framework to transform a non-audio-based method into an audio-based one. We also present a new PIN-entry method that improves the performance of this simple transformation. Most audio-based methods in the literature are unimodal methods, that is, they transmit almost all required information through an audio channel because it was believed that this approach maximized the user's performance. In this paper, however, we show that a carefully designed bimodal system may be more usable than a unimodal one. We present a new PIN-entry method whose audio channel only transmits the minimal required data while most of the challenge information is transmitted through the efficient visual channel. Our user study shows that the PIN-entry time of the proposed method is shorter than those of the previous audio-based methods, while its error rate is kept as low as that of the previous methods.

Currently, an increasing number of smartphones are adopting fingerprint verification as a method to authenticate their users. Fingerprint verification is not only used to unlock these smartphones, but also used in financial applications such as online payment. Therefore, it is very crucial to secure the fingerprint verification mechanism for reliable services. In this paper, however, we identify a few vulnerabilities in one of the currently deployed smartphones equipped with fingerprint verification service by analyzing the service application. We demonstrate actual attacks via two proof-of-concept codes that exploit these vulnerabilities. By the first attack, a malicious application can obtain the fingerprint image of the owner of the victimized smartphone through message-based interprocess communication with the service application. In the second attack, an attacker can extract fingerprint features by decoding a file containing them in encrypted form. We also suggest a few possible countermeasures to prevent these attacks.

We propose an efficient method for batch verification of exponentiation using width-w Non-Adjacent Forms (w-NAFs), which can be applied to modified DSA and ECDSA signatures. We further generalize this method to use tau-adic w-NAF scalars on elliptic curves with complex multiplication such as Koblitz curves. The theoretical analyses and experimental results show that our method accelerates the individual verification by a factor of up to 7.49 in the single-signer case and by up to 1.47 in the multiple-signer case for 1000 instances over a Koblitz curve K233. Our method can also be exploited to accelerate batch verification of pairing-based signatures.

In this paper, we introduce a transaction authentication solution that provides compatibility with any banking transactions. Our solution is based on a novel visual cryptographic scheme that supports multiple uses of a single static share, unlike existing techniques in the literature of visual cryptography. To support multiple uses, we utilize complementary colors in the subtractive color mixing model. In our solution, a user is asked to overlap an issued visual cryptography card on an encrypted image that is rendered on a screen to check transaction information and transaction authentication number. We analyze the security of our scheme against various attacks and show its effectiveness using a usability study.

The personal identification number (PIN) is a well-known authentication method used in various devices, such as ATMs, mobile devices, and electronic door locks. Unfortunately, the conventional PIN-entry method is vulnerable to shoulder-surfing attacks. Consequently, various shoulder-surfing resistant methods have been proposed. However, the security analyses used to justify these proposed methods are not based on rigorous quantitative analysis, but instead on the results of experiments involving a limited number of human attackers. In this paper, we propose new theoretical and experimental techniques for quantitative security analysis of PIN-entry methods. We first present new security notions and guidelines for secure PIN-entry methods by analyzing the existing methods under the new framework. On the basis of these guidelines, we develop a new PIN-entry method that effectively obviates human shoulder-surfing attacks by significantly increasing the amount of short-term memory required in an attack.

Since Ratha et al. introduced the functional transform for cancelable fingerprint templates, a few simulation attacks to this method have been proposed. The attacks are based on the fact that the transform depends only on the predefined parameters. That is, the attacker may fully simulate the transform and partially invert it if the parameters are available. Although an original template is transformed using different parameters for different systems, even the compromise of only one of these systems may reveal the original template, which may be a serious potential threat from a practical viewpoint. In this paper, we propose an improved functional transform, whose parameters are decided by the original template, as well as predefined user-specific keys. Because the information on the original template will not be available to the attacker even when a system is compromised, the proposed method significantly improves the security of the original template by preventing the attacker from reconstructing the transform. Copyright © 2013 John Wiley & Sons, Ltd.

Finite field multiplication is a crucial building block for cryptography, especially the elliptic curve public key cryptosystem. Recently, various algorithms for efficient finite field multiplication over devices whose resources are extremely constrained have been proposed. However, most of these proposals only take speed optimization into account, but they do not pay much attention to optimization of memory usage. In this paper, we propose a multiplication algorithm on $F_{2^{m}}$ , which minimizes the RAM requirement by rescheduling operation sequences. According to our experimental results on the ATmega128L microprocessor, the proposed algorithm reduces the amount of required RAM by up to 50 % while maintaining the speed at the same level. We also verify the feasibility of our algorithm by applying it to the elliptic curve cryptosystem.

AIMS The study investigated the clinical equivalence in reducing haemoglobin A1c (A1C) between glimepiride/metformin sustained release (GM-SR) 2/500 mg, a fixed-dose combination, once daily and glimepiride/metformin (GM) 1/250 mg, a fixed-dose combination, twice daily in patients with type 2 diabetes (T2D). METHODS A multicentre, randomised, double-blind, double-dummy study was conducted in 14 hospitals in Korea. Inclusion criteria were age 30-75 years, T2D diagnosis no longer than 10 years previously, A1C between 7% and 10%, and body mass index

User authentication is a process for a system to verify the identity of a claimed user and to give access permission. Although there are many other authentication methods such as biometrics and physical tokens, passwords are still being used in many applications due to easy deployment. To enhance the security against possible attacks such as an off-line dictionary attack, passwords are usually stored in a hashed form using a random nonce called a salt. However, this does not completely solve the security issue. In this paper, we propose a new password-based authentication method using homomorphic encryption where a password is stored in a remote server in an encrypted form and an input password is compared with the stored one on the encrypted domain. For this purpose, we also propose a new cryptographic primitive called one-time private key-based digital signature.

Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications are considered as building blocks in many promising applications related to traffic safety and management. However, network security issues related to V2V and V2I communications should be considered together for more robust service. For example, message recipients (vehicles or road side units) should be able to verify the origin and integrity of a message by verifying the signature corresponding to the message. Because in some cases a recipient has to verify a large number of signatures in a short time period, faster signature verification is required. In this paper, we show that the signature verification process can be accelerated by sharing public key extraction processes between messages and we propose an efficient algorithm for fast signature verification. Our proposal can be applied to both separate verification and batch verification scenarios.

Biometric verification systems have security issues regarding the storage of biometric data in that a user's biometric features cannot be changed into other ones even when a system is compromised. To address this issue, it may be safe to store the biometrics data on a reliable remote server instead of storing them in a local device. However, this approach may raise a privacy issue. In this paper, we propose a biometric verification system where the biometric data are stored in a remote server in an encrypted form and the similarity of the user input to the registered biometric data is computed in an encrypted domain using a homomorphic encryption. We evaluated the performance of the proposed system through an implementation on an Android-based smartphone and an i7-based server.

Since card-type one-time password (OTP) generators became available, power and area consumption has been one of the main issues of hardware OTPs. Because relatively smaller batteries and smaller chip areas are available for this type of OTP compared to existing tokentype OTPs, it is necessary to implement power-efficient and compact dedicated OTP hardware modules. In this paper, we design and implement a low-power small-area hardware OTP generator based on the Advanced Encryption Standard (AES). First, we implement a prototype AES hardware module using a 350 nm process to verify the effectiveness of our optimization techniques for the SubBytes transform and data storage. Next, we apply the optimized AES to a real-world OTP hardware module which is implemented using a 180 nm process. Our experimental results show the power consumption of our OTP module using the new AES implementation is only 49.4% and 15.0% of those of an HOTP and softwarebased OTP, respectively.

We propose a new method to speed up discrete logarithm (DL)-based cryptosystems by considering a new variant of the DL problem, where the exponents are formed as e1 + e2 for some fixed a and two integers e1, ae2 with a low weight representation. We call this class of exponents split exponents, and we show that with certain choice of parameters the DL problem on split exponents is essentially as secure as the standard DL problem, while the exponentiation operation using exponents of this class is significantly faster than best exponentiation algorithms given for standard exponents. For example, the speed of scalar multiplication on the standard Koblitz curve K163 is estimated to be accelerated by up to 51.5 % and 23.5 % at the cost of memory for one precomputed point, compared to the TNAF and window TNAF methods, respectively. As for security, we show that the provable security of the DL problem using split exponents is only by a small constant, e.g., 1/4, worse than the security of the standard DL problem. Split exponents can be adopted to speed up various DL-based cryptosystems. We exemplify this on the recent CCA-secure public key encryption of Bellare, Kohno, and Shoup.

A physical unclonable function (PUF) based on process variations on silicon wafers is a very promising technology which finds various applications in identification and authentication, but only a few integrated circuits have been reported so far. As those circuits are vulnerable to power supply noises, switching noises and environmental variations, they lead to a reliability issue such as time-varying or metastable responses. To resolve this issue, this letter proposes a new integrated circuit design for PUFs using differential amplifiers. The feasibility of the proposed circuit has been theoretically analyzed and validated through HSPICE simulations for the previous and proposed circuits.

The NTRU cryptosystem is a public key system based on lattice problems. While its theoretical security has been well studied, little effort has been made to analyze its security against implementation attacks including power analysis attacks. In this paper, we show that a typical software implementation of NTRU is vulnerable to the simple power analysis and the correlation power analysis including a second-order power attack. We also present novel countermeasures to prevent these attacks, and perform experiments to estimate the performance overheads of our countermeasures. According to our experimental results, the overheads in required memory and execution time are only 8.17% and 9.56%, respectively, over a Tmote Sky equipped with an MSP430 processor.

In an RFID search protocol, a reader uses designated query to determine whether a specific tag is in the vicinity of the reader. This fundamental difference makes search protocol more vulnerable to replay attacks than authentication protocols. Due to this, techniques used in existing RFID authentication protocols may not be suitable for RFID search protocols. In this paper, we propose two RFID search protocols, one based on static ID and the other based on dynamic ID, which use counter to prevent replay attacks. Moreover, we propose a security model for RFID search protocols that includes forward/backward traceability, de-synchronization and forgery attack. Based on this model, we analyze security of our protocols and related works.

This paper presents the design and implementation of a hyperelliptic curve cryptography (HECC) coprocessor over affine and projective coordinates, along with measurements of its performance, hardware complexity, and power consumption. We applied several design techniques, including parallelism, pipelining, and loop unrolling, in designing field arithmetic units, group operation units, and scalar multiplication units to improve the performance and power consumption. Our affine and projective coordinate-based HECC processors execute in 0.436 ms and 0.531 ms, respectively, based on the underlying field GF(2 89 ). These results are about five times faster than those for previous hardware implementations and at least 13 times better in terms of area-time products. Further results suggest that neither case is superior to the other when considering the hardware complexity and performance. The characteristics of our proposed HECC coprocessor show that it is applicable to high-speed network applications as well as resource-constrained environments, such as PDAs, smart cards, and so on.

Passwords and personal identification numbers (PINs) are convenient and ubiquitous, but they are quite vulnerable to attackers who stand near the user (“shoulder-surfers”). This problem may be partially resolved by changing the user interface, but previous solutions of this kind still give shoulder-surfing attackers a significant advantage over brute force search. This paper provides a novel solution based on three dimensions, particularly suitable for glasses-free three-dimensional (3D) displays found in many smartphones and handheld game consoles. A user at the “3D spot” may log in easily, while nearby shoulder-surfers gain no advantage. A detailed experimental usability analysis is performed to demonstrate the effectiveness of the proposed scheme in comparison to the existing methods.

A very promising application of active RFID systems is the electronic seal, an electronic device to guarantee the authenticity and integrity of freight containers. To provide freight containers with a high level of tamper resistance, the security of electronic seals must be ensured. In this paper, we present the design and implementation of an electronic seal protection system. First, we propose the eSeal Protection Protocol (ePP). Next, we implement and evaluate various cryptographic primitives as building blocks for our protocol. Our experimental results show that AES-CBC-MAC achieves the best performance among various schemes for message authentication and session key derivation. Finally, we implement a new electronic seal system equipped with ePP, and evaluate its performance using a real-world platform. Our evaluation shows that ePP guarantees a sufficient performance over an ARM9based interrogator.

The MIN cache replacement algorithm is an optimal off-line policy to decide which item to evict when a new item should be fetched into a cache. Recently, two short proofs were given by van Roy (2007) 3 and Vogler (2008) 4. We provide a simpler proof based on a novel invariant condition maintained through an incremental procedure. We provide an intuitive proof of optimality for the MIN cache replacement policy.Our proof uses an incremental procedure.Our proof is based on a novel invariant condition.

Currently, many smartphones are adopting fingerprint verification as a method to authenticate their users. Because fingerprint verification is not only used to unlock these smartphones but also used in financial applications such as online payment, it is crucial to secure the fingerprint verification mechanism for reliable services. In this paper, we identify a few vulnerabilities in one of the currently deployed smartphones equipped with fingerprint verification service by analyzing the service application. We demonstrate actual attacks via a proof-of-concept code that exploits these vulnerabilities. By these attacks, an attacker can extract fingerprint features by decoding a file containing them in encrypted form. We also suggest a few possible countermeasures against these attacks.

This paper proposes an efficient scalar multiplication algorithm for hyperelliptic curves, which is based on the idea that efficient endomorphisms can be used to speed up scalar multiplication. We first present a new Frobenius expansion method for special hyperelliptic curves that have Gallant-Lambert-Vanstone (GLV) endomorphisms. To compute kD for an integer k and a divisor D, we expand the integer k by the Frobenius endomorphism and the GLV endomorphism. We also present improved scalar multiplication algorithms that use the new expansion method. By our new expansion method, the number of divisor doublings in a scalar multiplication is reduced to a quarter, while the number of divisor additions is almost the same. Our experiments show that the overall throughputs of scalar multiplications are increased by 15.6 to 28.3 % over the previous algorithms when the algorithms are implemented over finite fields of odd characteristics.

Von zur Gathen proposed an efficient parallel exponentiation algorithm in finite fields using normal basis representations. In this paper we present a processor-efficient parallel exponentiation algorithm in GF(qn) which improves upon von zur Gathen's algorithm. We also show that exponentiation in GF(qn) can be done in O((log2 n)2 / logq n) time using n / (log2 n)2 processors. Hence we get a processor-time bound of O(n / logq n), which matches the best known sequential algorithm. Finally, we present an efficient on-line processor assignment scheme which was missing in von zur Gathen's algorithm.

Passwords and PINs are convenient and ubiquitous, yet they are quite vulnerable to attackers who stand near the user. This problem may be partially resolved by changing the user interface, but previous solutions of this kind still give shoulder-surfing attackers a significant advantage over brute-force search. We propose a novel solution based on 3D, especially suitable for glasses-free 3D displays found in many smartphones and handheld game consoles. A user at the “3D spot” may log in easily, while nearby shoulder-surfers gain no advantage. We perform a detailed experimental analysis of the usability of our scheme.