Signature Authentication Research Articles

An anonymous and privacy‐preserving scheme for efficient traffic movement analysis in intelligent transportation system

Intelligent transportation system (ITS) has gained popularity in recent times because it has the prospect to improve traffic efficiency, minimize traffic accident, provide convenience, and reduce air pollution. In this paper, we propose a secure, autonomous, anonymous, and privacy‐preserving traffic movement analysis scheme for ITS. In the proposed scheme, fine‐grained traffic information such as average speed can be obtained without compromising users' privacy. We employ modified Paillier cryptosystem and Chinese Remainder Theorem to aggregate data of heterogeneous roads for saving bandwidth and Boneh short signature for authentication. The proposed scheme is autonomous by allowing users to generate their private/public key pair on their own for communication. In addition, we show that the proposed scheme meets all the security and privacy requirements of ITS such as data confidentiality and integrity, anonymous authentication, conditional traceability, and attack resistance. The performance analysis shows that the proposed scheme is very efficient.

On the Use of Edge Features and Exponential Decaying Number of Nodes in the Hidden Layers for Handwritten Signature Recognition

Handwritten signatures are playing an important role in finance, banking and education and more because it is considered the “seal of approval” and remains the most preferred means of authentication. In this paper, an offline handwritten signature authentication algorithm is proposed using the edge features and deep feedforward neural network (DFNN). The number of hidden layers in DFNN is configured to be at least one layer and more. In this paper, an exponential decaying number of nodes in the hidden layers was proposed to achieve better recognition rate with reasonable training time. Of the six edge algorithms evaluated, Roberts operator and Canny edge detectors were found to produce better recognition rate. Results showed that the proposed exponential decaying number of nodes in the hidden layers outperform other structure. However, more training data was required so that the proposed DFNN structure could have more efficient learning.

The Opening Capability for Security against Privacy Infringements in the Smart Grid Environment

It is now known that more information can be leaked into the smart grid environment than into the existing environment. In particular, specific information such as energy consumption data can be exposed via smart devices. Such a phenomenon can incur considerable risks due to the fact that both the amount and the concreteness of information increase when more types of information are combined. As such, this study aimed to develop an anonymous signature technique along with a signature authentication technique to prevent infringements of privacy in the smart grid environment, and they were tested and verified at the testbed used in a previous study. To reinforce the security of the smart grid, a password and anonymous authentication algorithm which can be applied not only to extendable test sites but also to power plants, including nuclear power stations, was developed. The group signature scheme is an anonymous signature schemes where the authenticator verifies the group signature to determine whether the signer is a member of a certain group but he/she would not know which member actually signed in. However, in this scheme, the identity of the signer can be revealed through an “opener” in special circumstances involving accidents, incidents, or disputes. Since the opener can always identify the signer without his/her consent in such cases, the signer would be concerned about letting the opener find out his/her anonymous activities. Thus, an anonymous signature scheme where the signer issues a token when entering his/her signature to allow the opener to confirm his/her identity only from that token is proposed in this study.

Denoising of Ecg Signals Using Fir & Iir Filter: a Performance Analysis

Electrocardiogram (ECG) signal is the electrical recording of coronary heart activity. It is a common routine and vital cardiac diagnostic tool in which in electric signals are measured and recorded to recognize the practical status of heart, but ECG signal can be distorted with noise as, numerous artifacts corrupt the unique ECG signal and decreases it quality. Consequently, there may be a need to eliminate such artifacts from the authentic signal and enhance its quality for better interpretation. ECG signals are very low frequency signals of approximately 0.5Hz-100Hz and digital filters are used as efficient approach for noise removal of such low frequency signals. Noise may be any interference because of movement artifacts or due to power device that are present wherein ECG has been taken. Consequently, ECG signal processing has emerged as a common and effective tool for research and clinical practices. This paper gives the comparative evaluation of FIR and IIR filters and their performances from the ECG signal for proper understanding and display of the ECG signal.

Definitely simultaneous determination of three lignans in rat using ultra-high performance liquid chromatography-tandem mass spectrometry

Herbal medicines (HMs) have been widely demonstrated to be extremely complicated chemical pools, notably the occurrences of isomers that usually possess similar chromatographic and spectrometric behaviors, and the complexity will be further boosted in HMs-treated biological samples. Hence, there is a technical barrier regarding identity confirmation towards the acquisition of reliable quantitative information for those compounds-of-interest in biological matrices, although tandem mass spectrometry (MS/MS) is a favored tool because of the advantages in terms of specificity and selectivity, in particular being hyphenated with ultra-high performance liquid chromatography (UHPLC). More structural information should be involved in addition to retention times and precursor-to-product ion transitions, to consolidate the identities of the captured signals. Attempts were made here to strengthen quantitation confidences via matching MS2 spectra and relative response-collision energy curves (RRCECs) between each pair of suspect peak and the authentic signal, and UHPLC coupled to hybrid triple quadrupole-linear ion trap mass spectrometry (Qtrap-MS) that enabled simultaneous acquisition of qualitative and quantitative information acted as the analytical tool. Definitely simultaneous determination of a pair of regio-isomers namely 6‑hydroxy‑4‑(4‑hydroxy‑3‑methoxyphenyl)‑3‑hydroxymethyl‑7‑methoxy‑3,4‑dihydro‑2‑naphthaldehyde (VB-1) and vitedoin A (VB-2), together with another analogue namely detetrahydroconidendrin (VB-3), in rat plasma as well as tissues was conducted following oral administration of the extract of fruits of Vitex negundo var. cannabifolia. Diverse method validation assays in regard of selectivity, linearity, intra- and inter-day variations, matrix effect, and recovery were employed to demonstrate the newly developed method being able to fulfill the demands of rational quantitation. Overall, the current study offers a promising approach to accomplish confidence-enhanced quantitation in biological matrices.

Genuine and Secure Identity-Based Public Audit for the Stored Data in Healthcare Cloud.

Cloud storage has attracted more and more concern since it permits cloud users to save and employ the corresponding outsourced files at arbitrary time, with arbitrary facility and from arbitrary place. To make sure data integrality, numerous public auditing constructions have been presented. However, existing constructions mainly have built on the PKI. In these constructions, to achieve data integrality, the auditor first must authenticate the legality of PKC, which leads to a great burden for the auditor. To eliminate the verification of time-consuming certificate, in this work, we present an efficient identity-based public auditing proposal. Our construction is an identity-based data auditing system in the true sense in that the algorithm to calculate authentication signature is an identity-based signature algorithm. By extensive security evaluation and experimental testing, the consequences demonstrate that our proposal is safe and effective; it can efficiently hold back forgery attack and replay attack. Finally, compared with the two identity-based public auditing proposals, our proposal outperforms the two proposals under the condition of overall considering computational cost, communication overhead, and security strength.

Review of Secure Communication Approaches for In-Vehicle Network

In the connected vehicles, connecting interfaces bring threats to the vehicles and they can be hacked to impact the vehicles and drivers. Compared with traditional vehicles, connected vehicles require more information transfer. Sensor signals and critical data must be protected to ensure the cyber security of connected vehicles. The communications among ECUs, sensors, and gateways are connected by in-vehicle networks. This paper discussed the state-of-art techniques about secure communication for in-vehicle networks. First, the related concepts in automotive secure communication have been provided. Then we have compared and contrasted existing approaches for secure communication. We have analyzed the advantages/disadvantages of MAC and digital signatures for message authentication and compared the performance and limitations of different cryptographic algorithms. Firewall and intrusion detection system are introduced to protect the networks. The constraints and features of different intrusion detection approaches are presented. After that, the technical requirements for cryptographic mechanism and intrusion detection policy are concluded. Based on the review of current researches, the future development directions of the automotive network security have been discussed. The purpose of this paper is to review current techniques on automotive secure communication and suggest suitable secure approaches to implement on the in-vehicle networks.

Low‐complexity GNSS anti‐spoofing technique based on Doppler frequency difference monitoring

Single-antenna global navigation satellite system (GNSS) spoofing, where all spoofing signals are broadcast by the same antenna, is a great threat to mass market location-based services. This study proposes an anti-spoofing technique based on Doppler frequency difference (DFD) monitoring against single-antenna spoofing, which requires only a standalone receiver with a single antenna. When the receiver moves randomly, the DFD between two authentic satellite signals is non-linear in time domain, whereas between two single-antenna spoofing signals is linear. This study deduces the DFD model and converts the problem of spoofing detection into a sequence linearity detection problem. The hypothesis based on DFD is given, and the statistic is constructed by the method of sequence block processing. This technique has low complexity because it only requires the knowledge of the Doppler frequency without additional information. The detection performance is verified by simulations and real data experiments. The simulation results show that the detection probability can exceed 99.99% easily at 0.001% false alarm probability when the receiver's motion state changes sufficiently. The real data experiments show that the proposed technique can effectively detect GNSS spoofing and distinguish spoofing signals from authentic signals.

Development of E-Diploma System Model with Digital Signature Authentication

The purpose of developing an e-diploma system model is to provide an overview of digital files that can be used as documents that have the same validity as paper documents. The validity is obtained through digital signature authentication so that in the future the use of e-diploma can be synchronized with a paper-based diploma. The method used to develop the model is a descriptive qualitative. The result of the research is a model. A printed diploma has a vulnerability that must be considered. Basically, paper documents are easily lost and damaged. Digital signatures are the mechanisms used to guarantee the authenticity of digital documents in the form of digital certificates. Digital certificates issued by the state to maintain its authenticity and integrity. Digital signatures are attached to digital documents. An E-Diploma is given as a companion of the original diploma. The model is developed to show that an E-Diploma may be considered as a valid document in the future, as long as it is authenticated by digital signatures.

Hierarchical architecture and protocol for mobile object authentication in the context of IoT smart cities

The deployment of smart technologies such as smart meters, smart phones, and smart chips has facilitated the development of smart cities. Smart cities include different smart systems such as smart homes, smart grids, etc. These smart systems should be connected together along with huge number of smart objects in the world largest network known as the Internet of Things (IoT). Trusted communication between an IoT object, which could be any device, and smart systems is an essential objective for the security over the IoT. This can be supported by authentication enforcers which, with the large number of connected objects in the IoT, should impose efficient and scalable mobile object authentication solutions. In this paper, a four-layer architecture for mobile object authentication in the context of IoT smart cities is proposed. This architecture is designed to address different IoT challenges such as scalability, mobility, and heterogeneity. Moreover, the architecture is supported by the applicability of a proposed hierarchical elliptic curve identity based signature authentication protocol. The proposed architecture and the proposed authentication protocol have been compared with other related works proposed in the literature. Various design goals of IoT in smart cities have been considered in the comparison along with the computation cost on both the sender and the receiver entities. Results show that the proposed architecture supports more design goals of IoT in smart city than its rival architectures and the proposed authentication protocol has lower computation cost than the other related protocols.

Generation of a biometrically activated digital signature based on hybrid neural network algorithms

This paper suggests a model of a hybrid wide neural network based on perceptrons, quadratic form networks and multidimensional difference and hyperbolic Bayes functionals. It is experimentally proved that this model is highly efficient when used for biometric authentication and generation of a digital signature activated biometrically. The paper suggests methods of generating keys of a digital signature and personal authentication by handwritten patterns, a key stroke manner and facial parameters. Comparatively high rates of reliability for taken solutions were achieved that were estimated taking into account the variability of dynamic biometric patterns over time.

Moving variance-based signal quality monitoring method for spoofing detection

Signal quality monitoring (SQM) techniques, originally designed for multipath detection, were recently found to be useful to identify underway spoofing attacks. Conventional SQM-based methods directly employ the values of the SQM metrics to monitor spoofing attacks. They have good feasibility with simple structures but suffer from significant performance loss for frequency unlocked spoofing cases due to the drift of the relative carrier phase. We developed an enhanced SQM technique for detecting an onset of spoofing. It is known that the value of the SQM metric fluctuates significantly during the interaction stage between the counterfeit signal and authentic signal. As the variance of metric can better reflect this fluctuation, we choose the moving variance (MV) of the SQM metric as a new metric to detect the occurrence of spoofing. The basic principle of the proposed method is introduced. Its ability to detect spoofing has been validated using the Texas Spoofing Test Battery dataset and compared with the classic SQM methods and a moving average-based method. The results show that the proposed MV-based SQM method is advantageous in the detection of an onset of a frequency unlocked spoofing attack.

Conspicuous Consumption on the Long Tail: How Can Luxury Brands Benefit from Counterfeits?

We study how luxury brands can use product line expansion as a strategy when facing a threat from the counterfeit market. Consumers who are status-conscious consider the bene fits and costs of buying luxury items in order to strengthen the beliefs of others about their status. Our findings suggest that product line expansion strategy serves these high-end consumers and their motives to strengthen their status image. In a market with counterfeiters, consumers have an incentive to buy additional products in order to reduce the uncertainty of their status signals. Increasing consumption makes it harder for others to imitate status when authentic brands signal quality and status with higher precision compared to counterfeits. Since each luxury item purchased contributes to one's status in a marginally declining fashion, it is rational for a luxury brand to expand its product line such that it maintains its core product and introduces peripheral products with lower status signalling benefi ts and prices. We further show that an increasing counterfeit market share can increase status-conscious consumers' willingness to pay for luxury goods. As a result, presence of counterfeiters can increase the pro t of a luxury brand.

Secure authentication framework for cloud-based toll payment message dissemination over ubiquitous VANETs

The privacy and security issues of information message dissemination have been well researched in typical VANETs. However, cloud computing paradigm is merely utilized for secure information message dissemination over VANETs. In this paper, we propose a secure authentication framework for cloud-based toll payment message dissemination over ubiquitous VANETs, which primarily deal with two types of information messages that is general purpose and special purpose information messages. General purpose information messages include infotainment, traffic congestion, location-based services and emergency services. While the special purpose information messages include toll tax and revenue collection services. Moreover, our secure authentication framework (CCES-PKC) integrates the novel cloud-based pairing-free certificate-less encryption, secure authentication control, signature-based information encryption, decryption through cloud verification and signature authentication along with batch auditing. The certificate overhead management is passed over to the cloud infrastructure for fine-grained information message dissemination by enabling verification, integrity and confidentiality. Performance assessments including efficiency, security and experimental analysis emphasize that the proposed scheme is remarkably appropriate for secure toll payment information message dissemination.

From BoVW to VLAD with KAZE features: Offline signature verification considering cognitive processes of forensic experts

The widespread use of handwritten signatures for identity authentication has resulted in a need for automated verification systems. However, there is room for improvement in the performance of automated systems compared to human analysis, particularly that of forensic document examiners (FDEs), under a wide range of conditions. As any inaccuracy in analysis can cause serious problems, further research is required to improve performance. In this study, to improve the performance of offline signature verification under various writing conditions, new approaches using feature encoding methods of a bag-of-visual words (BoVW) and a vector of locally aggregated descriptors (VLAD) are adopted. The proposed method considers current knowledge about the cognitive processes used by FDEs to improve performance. The proposed method incorporates an approach based on BoVW and VLAD with local features to mimic the cognitive processes of FDEs for feature extraction. In addition, KAZE features detected in strokes and background space are employed as local features to enhance discriminative power. The performance of the proposed approach is demonstrated using the publicly-available CEDAR and MCYT-75 signature datasets.

BSeIn: A blockchain-based secure mutual authentication with fine-grained access control system for industry 4.0

To be prepared for the ‘Industry 4.0’-era, we propose a hierarchical framework comprising four tangible layers, which is designed to vertically integrate inter-organizational value networks, engineering value chain, manufacturing factories, etc. The conceptual framework allows us to efficiently implement a flexible and reconfigurable smart factory. However, we need to consider security inherent in existing (stand-alone) devices and networks as well as those that may arise in such integrations. Especially the existing solutions are insufficient to address these fundamental security concerns. Thus, we present a blockchain-based system for secure mutual authentication, BSeIn, to enforce fine-grained access control polices. The proposed system (with integrated attribute signature, multi-receivers encryption and message authentication code) is designed to provide privacy and security guarantees such as anonymous authentication, auditability, and confidentiality. BSeIn also scales well due to the utilization of smart contract. We then evaluate the security and performance of BSeIn. For example, findings from the performance evaluation demonstrate that Initialization/Request Issuance/Chain Transaction/State Delivery/Permission Update phase only cost 12.123/4.810/6.978/0.013/2.559s, respectively.

Research on Signature Verification Method Based on Discrete Fréchet Distance

This paper proposes a multi-feature signature template based on discrete Fréchet distance, which breaks through the limitation of traditional signature authentication using a single signature feature. It solves the online handwritten signature authentication signature global feature template extraction calculation workload, signature feature selection unreasonable problem. In this experiment, the false recognition rate (FAR) and false rejection rate (FRR) of the statistical signature are calculated and the average equal error rate (AEER) is calculated. The feasibility of the combined template scheme is verified by comparing the average equal error rate of the combination template and the original template.

Implementation of 4-way Superscalar Hash MIPS Processor Using FPGA

Due to the quick advancements in the personal communications systems and wireless communications, giving data security has turned into a more essential subject. This security idea turns into a more confounded subject when next-generation system requirements and constant calculation speed are considered in real-time. Hash functions are among the most essential cryptographic primitives and utilized as a part of the many fields of signature authentication and communication integrity. These functions are utilized to acquire a settled size unique fingerprint or hash value of an arbitrary length of message. In this paper, Secure Hash Algorithms (SHA) of types SHA-1, SHA-2 (SHA-224, SHA-256) and SHA-3 (BLAKE) are implemented on Field-Programmable Gate Array (FPGA) in a processor structure. The design is described and implemented using a hardware description language, namely VHSIC “Very High Speed Integrated Circuit” Hardware Description Language (VHDL). Since the logical operation of the hash types of (SHA-1, SHA-224, SHA-256 and SHA-3) are 32-bits, so a Superscalar Hash Microprocessor without Interlocked Pipelines (MIPS) processor are designed with only few instructions that were required in invoking the desired Hash algorithms, when the four types of hash algorithms executed sequentially using the designed processor, the total time required equal to approximately 342 us, with a throughput of 4.8 Mbps while the required to execute the same four hash algorithms using the designed four-way superscalar is reduced to 237 us with improved the throughput to 5.1 Mbps.

Adaptive complex‐EKF‐based DOA estimation for GPS spoofing detection

In this study, a simple but effective spoofing detection method using a global positioning system (GPS) directional antenna is proposed which exploits the difference between the estimated direction-of-arrival (DOA) and the measured DOA from a GPS almanac and ephemeris data. The receiving signal's DOA is estimated by using a single antenna power measurement-based complex extended Kalman filter (EKF) which is a complex valued state space based estimation technique. Furthermore, an adaptive logic is applied to the complex EKF to reduce the effect of the measurement disturbance. To maintain the validity of the proposed algorithm, it is assumed that the spoofer is aware of the target's location, but that its DOA is not perfectly the same as that of the authentic GPS signal. In addition, the orientation of the directional antenna is known by using an attitude and heading reference system that is attached to the antenna, and its antenna radiation pattern is also known. The proposed detection method is evaluated using a theoretical analysis and simulations. It is finally confirmed that the proposed algorithm can detect a spoofing signal according to the different direction angles of the spoofing signal, and especially those with low DOAs.

GNSS Signal Authentication Via Power and Distortion Monitoring

We propose a simple low-cost technique that enables civil Global Positioning System (GPS) receivers and other civil global navigation satellite system (GNSS) receivers to reliably detect carry-off spoofing and jamming. The technique, which we call the Power-Distortion detector, classifies received signals as interference-free, multipath-afflicted, spoofed, or jammed according to observations of received power and correlation function distortion. It does not depend on external hardware or a network connection and can be readily implemented on many receivers via a firmware update. Crucially, the detector can with high probability distinguish low-power spoofing from ordinary multipath. In testing against over 25 high-quality empirical data sets yielding over 900,000 separate detection tests, the detector correctly alarms on all malicious spoofing or jamming attacks while maintaining a <0.6% single-channel false alarm rate.