Authentication Algorithm Research Articles

Multi-format speech BioHashing based on spectrogram

In order to solve the security problem of speech perception hash authentication, the application scope of speech authentication algorithm, and improve the robustness, discrimination and real-time authentication in the process of authentication, a multi-format speech BioHashing algorithm based on spectrogram is proposed. Firstly, the speech signal to be processed is converted into spectrogram and feature extraction is carried out by two-dimensional discrete cosine transform. Then, the dimensionality of the eigenvector is reduced by non-negative matrix factorization, and generation of BioHashing sequences by inner product of reduced dimension eigenvectors and orthogonal normalized random matrices. Finally, the BioHashing is encrypted by equal-length scrambling using Henon chaotic map. The algorithm also validates the unidirectionality of BioHashing with trapdoor by comparative difference method. The experimental results show that the proposed algorithm has the characteristics of good security, strong robustness, high real-time performance and wide application range.

Video tampering dataset development in temporal domain for video forgery authentication

Videos are tampered by the forgers to modify or remove their content for malicious purpose. Many video authentication algorithms are developed to detect this tampering. At present, very few standard and diversified tampered video dataset is publicly available for reliable verification and authentication of forensic algorithms. In this paper, we propose the development of total 210 videos for Temporal Domain Tampered Video Dataset (TDTVD) using Frame Deletion, Frame Duplication and Frame Insertion. Out of total 210 videos, 120 videos are developed based on Event/Object/Person (EOP) removal or modification and remaining 90 videos are created based on Smart Tampering (ST) or Multiple Tampering. 16 original videos from SULFA and 24 original videos from YouTube (VTD Dataset) are used to develop different tampered videos. EOP based videos include 40 videos for each tampering type of frame deletion, frame insertion and frame duplication. ST based tampered video contains multiple tampering in a single video. Multiple tampering is developed in three categories (1) 10-frames tampered (frame deletion, frame duplication or frame insertion) at 3-different locations (2) 20-frames tampered at 3- different locations and (3) 30-frames tampered at 3-different locations in the video. Proposed TDTVD dataset includes all temporal domain tampering and also includes multiple tampering videos. The resultant tampered videos have video length ranging from 6 s to 18 s with resolution 320X240 or 640X360 pixels. The database is comprised of static and dynamic videos with various activities, like traffic, sports, news, a ball rolling, airport, garden, highways, zoom in zoom out etc. This entire dataset is publicly accessible for researchers, and this will be especially valuable to test their algorithms on this vast dataset. The detailed ground truth information like tampering type, frames tampered, location of tampering is also given for each developed tampered video to support verifying tampering detection algorithms. The dataset is compared with state of the art and validated with two video tampering detection methods.

REPAIR: fragile watermarking for encrypted speech authentication with recovery ability

Confidentiality and integrity are fundamental requirements when transmitting and storing data. In order to guarantee the confidentiality and integrity of speech signal, we present a novel wateRmarking scheme for Encrypted sPeech AuthenticatIon with Recovery (REPAIR) scheme. In REPAIR, an encryption algorithm is first designed based on a hyper-chaotic method to improve the confidentiality of the original speech by encryption. Subsequently, a watermark generation and embedding algorithm is proposed to generate and embed the check bits and compression bits. Afterwards, a content authentication and tampering recovery algorithm is introduced to locate and recover the tampered speech frames. Meanwhile, a speech decryption algorithm is also presented to decrypt the encrypted speech. Analysis and experimental results demonstrate that REPAIR can detect and locate synchronization attacks and de-synchronization attacks without using the auxiliary synchronous code. Additionally, REPAIR can also recover the tampered content with high quality.

Security and Performance of Single Sign-on Based on One-Time Pad Algorithm

Single sign-on (SSO) techniques allow access control for multiple systems with a single login. The aim of our study is to construct an authentication algorithm that provides the authentication information of a user to a requester without requiring any specific token, thereby achieving domain-free access control. In this study, we propose an authentication algorithm for SSO based on a verifiable encryption (VE)-based authentication algorithm and implementation. VE is a kind of cryptosystem that allows calculation on cyphertexts, generating an encrypted result, which matches the distance between two plaintexts when decrypting. In our approach, we first construct the mathematical SSO algorithm based on the VE-based algorithm, and then implement the algorithm by applying the one-time pad to the algorithm and using sample data. We also consider robustness against theoretical attacks such as man-in-the-middle attack. In addition to that, our algorithm is robust against the well-known classical and theoretical attacks, the man-in-the-middle attack against the proposed algorithm is also impracticable. Furthermore, with security analysis using Proverif, the algorithm has been shown to be secure. The execution speed is less than 1 ms even with a text length of 8192 bits. Based on our results, it is evident that the computational burden of trusted third parties, such as a certificate authority, can be alleviated because the public key agreement is not required in our algorithm. Moreover, since only the authentication information is disclosed to the service provider, big tech such as GAFA cannot obtain personal information of the user without consent. As for the originality of our algorithm, any personal information, such as biometric information and non-contact magnetic IC cards in addition to the pair of ID and password, which is used for common SSO algorithms, is available.

Efficient and secure message authentication algorithm at the physical layer

Message authentication, which refers to source authentication and message integrity, is an essential security service, especially in emerging networks such as peer-to-peer, Device-to-Device, LPWAN (such as NB-IoT, LTE-M or SigFox) and vehicle to vehicle. Traditionally, message authentication schemes handled at upper layers of the protocol stack. Such schemes require multiple rounds and multiple operations per round, which results in a considerable overhead in terms of latency and required resources. Recently, many research works have shifted towards investigating the design of new security solutions at the physical layer (PLS). Although data confidentiality and device authentication schemes have been introduced at the physical layer, yet, no PLS message authentication scheme has been presented. In this paper, we propose a dynamic message authentication algorithm (keyed hash function) that makes use of a secret session key in addition to the random characteristics of the physical channel. Moreover, the cryptographic primitives are dynamic and get updated in a lightweight manner for every input frame symbol. Security and performance analysis were conducted to validate the efficiency and robustness of the proposed scheme. The results confirmed that the proposed authentication scheme exhibits a high level of security with minimum overhead in terms of delay.

An Improved Provable Secure Certificateless Aggregation Signature Scheme for Vehicular Ad Hoc NETworks

Vehicular Ad hoc NETworks (VANETs) which is an important part of smart cities are large networks that organize wireless communication and information exchange between vehicles and X (X: cars, roads, pedestrians, and the Internet). The security and efficiency of the message authentication algorithm are crucial to the VANETs. After analyzing the security shortage of Wang Daxing et al VANETs message authentication scheme, an improved provable secure certificateless aggregation signature scheme for VANETs is proposed. The scheme constructs a secure certificateless aggregation authentication scheme by using Elliptic Curve Cryptography (ECC) and reduces the complexity of the cryptographic operation process, while achieving user’s conditional privacy protection. Rigid security analysis proves that the scheme satisfies the security requirements of VANETs. The performance analysis shows the proposed scheme considerably reduces the computational cost of message signature, single verification and aggregation verification algorithm, and reduces the communication cost when compared with Wang schemes.

Efficient & secure image availability and content protection

Digital images are among the most communicated multimedia data types. Many of these images include private data that require a high level of security. The traditional image security schemes rely on cryptographic solutions to ensure the confidentiality or the authentication of image contents, and to ensure that the encryption key is not compromised. However, the continuous evolution of the attackers’ capabilities is making it harder than ever to achieve the goal of safeguarding the private data against breaches. Moreover, the centralization aspect of images’ storage makes them prone to availability attacks. In this paper, we propose a distributed and secure storage scheme for images, based on the Modified Information Dispersal Algorithm (MIDA), and taking into consideration the trade-off between the high security level and the associated computational overhead. The proposed solution applies block permutation on the image to ensure data confidentiality and then, divides it into k fragments that are encoded using the proposed parallel modified IDA. The output consists of n encoded fragments, instead of k, to ensure data availability. Next, each encoded fragment is authenticated using a lightweight Message Authentication Algorithm (MAA) to ensure data integrity with source authentication. Finally, the encoded fragments are distributed over n storage nodes (or multi-cloud providers). The resilience degree of such redundancy is (n − k), since only k fragments are required to reconstruct the original images. All the cryptographic steps such as permutation, IDA encoding and MAA consist of simple operations and they are based on a dynamic key. This ensures a high level of security since in each session, a new key is used to produce different cryptographic primitives as well as the update primitives, which are used to update the permutation and selection tables. The implementation results show that the proposed scheme meets the desired cryptographic properties to guard against different attacks. Finally, the performance tests show that the proposed scheme is lightweight with low overhead in terms of computations, communication and storage.

A two‐level authentication scheme for clone node detection in smart cities using Internet of things

AbstractClone node attack in IoT sensor devices remains a grave security concern as it paves the way for sinkhole, wormhole, and selective forwarding attacks. In this paper, a two‐level authentication scheme named Fingerprint‐based Zero‐Knowledge Authentication (FZKA) algorithm is proposed to improve the detection rate of clone node among the sensor devices. In the fingerprint generation phase, the base station calculates a distinct fingerprint value for each and every node in the network by gathering neighborhood information, represented in the form of superimposed s‐disjunct code matrix. The calculated fingerprint is considered as a secret value and distributed to each cluster nodes for the process of authentication. The FZKA algorithm improves the cloned node detection accuracy with minimal detection time. The simulation results highlight the cloned node detection rate of the proposed scheme by a margin of 92.5% against the existing Exponential Smoothing Algorithm (ETS), Position Verification Method, and Message Verification and Passing algorithms.

Palm Vein based Authentication

The palm vein authentication technology offers a high level of accuracy. Palm vein authentication uses the vascular patterns of an individual’s palm as personal identification data. If we compare with a finger or the back of a hand, a palm has a broader and more complicated vascular pattern and thus contains a wealth of differentiating features for personal identification. The importance of biometrics in the current field of Security has been depicted in this work. We have processed the raw image from the dataset before implementing authentication algorithm. After getting the suitable image after pre- processing, we have used local binary pattern (LBP) for feature extraction purpose & then using a machine learning algorithm, with support vector machine (SVM), we tried to match the vascular vein pattern for authentication. Result of the matching algorithm is not only optimized as per the proposed approach but also quite efficient.

Comparative study of support vector machines and random forests machine learning algorithms on credit operation

SummaryCorporate insolvency has significant adverse effects on an economy. With the number of multinationals increasing rapidly, corporate bankruptcy can severely disrupt the global financial environment. However, multinationals do not fail instantaneously; objective strategies combined with a rigorous analysis of both qualitative and quantifiable data can go a long way in identifying an organization's financial risks. Recent advancements in information and communication technologies have made data collection and storage an easy task. The challenge becomes mining the appropriate data about a company's financial risks and implementing it in forecasting a company's insolvency probabilities. In recent years, machine learning has been incorporated into big data analytics owing to its massive success in learning complex models. Machine learning algorithms such as Support Vector Machines (SVM), Random Forests (RF), Artificial Neural Networks, Gaussian Processes, and Adaptive Learning have been used in the analysis of Big Data to predict the financial risks of companies. In this paper, credit scoring is explored with regards to data processed using the collateral as an independent variable. The obtained results indicate that RF algorithm is promising for use in credit risk management. This research shows the advantages of the RF approach over the SVM algorithm are its speed and operational simplicity, and SVM has the benefit of higher classification accuracy than RF. The paper compares the SVM and RF algorithms to forecast the recovered value in a credit task. The execution of the projected intelligent systems uses tests and algorithms for authentication of the projected model.

Fast and Accurate Algorithm for ECG Authentication Using Residual Depthwise Separable Convolutional Neural Networks

The electrocardiogram (ECG) is relatively easy to acquire and has been used for reliable biometric authentication. Despite growing interest in ECG authentication, there are still two main problems that need to be tackled, i.e., the accuracy and processing speed. Therefore, this paper proposed a fast and accurate ECG authentication utilizing only two stages, i.e., ECG beat detection and classification. By minimizing time-consuming ECG signal pre-processing and feature extraction, our proposed two-stage algorithm can authenticate the ECG signal around 660 μs. Hamilton’s method was used for ECG beat detection, while the Residual Depthwise Separable Convolutional Neural Network (RDSCNN) algorithm was used for classification. It was found that between six and eight ECG beats were required for authentication of different databases. Results showed that our proposed algorithm achieved 100% accuracy when evaluated with 48 patients in the MIT-BIH database and 90 people in the ECG ID database. These results showed that our proposed algorithm outperformed other state-of-the-art methods.

Specifying a Cryptographical Protocol in Lustre and SCADE

We present SCADE and Lustre models of the Message Authenticator Algorithm (MAA), which is one of the first cryptographic functions for computing a message authentication code. The MAA was adopted between 1987 and 2001, in international standards (ISO 8730 and ISO 8731-2), to ensure the authenticity and integrity of banking transactions. This paper discusses the choices and the challenges of our MAA implementations. Our SCADE and Lustre models validate 201 official test vectors for the MAA.

A LIGHTWEIGHT AUTHENTICATION TECHNIQUE FOR SECURE COMMUNICATION OF EDGE/FOG DATA-CENTERS

Edge computing has significantly enhanced the capabilities of cloud computing. Edge data-centres are used for storing data of the end-user devices. Secure communication between the legitimate edge data-centres during the load balancing process has attracted industrial and academic researchers. Recently, Puthal et al. have proposed a technique for authenticating edge datacenters to enable secure load balancing. However, the resource-constraint nature of the edge data-centres is ignored. The scheme is characterized by complex computation and memory intensive cryptographic protocol. It is also vulnerable to key escrow attack because the secret key used for encrypting and decrypting of the communicated messages is been created by the trusted cloud datacenter. Additionally, the key sharing phase of their algorithm is complex. Therefore, to address the highlighted challenges, this paper proposed a lightweight key escrow-less authentication algorithm that will ensure secure communication of resource-constrained edge data-centres during the load balancing process. The security capability of the proposed scheme has been formally evaluated using the automatic cryptographic analytical tool ProVerif. The relatively low computation and communication costs of the proposed scheme compared to the benchmark schemes proved that it is lightweight, thus suitable for resource-constrained edge datacenters.

High-Resolution Remote Sensing Image Integrity Authentication Method Considering Both Global and Local Features

Content integrity of high-resolution remote sensing (HRRS) images is the premise of its usability. Existing HRRS image integrity authentication methods are mostly binary decision-making processes, which cannot provide a further interpretable information (e.g., tamper localization, tamper type determination). Due to this reason, a robust HRRS images integrity authentication algorithm using perceptual hashing technology considering both global and local features is proposed in this paper. It extracts global features by the efficient recognition ability of Zernike moments to texture information. Meanwhile, Features from Accelerated Segment Test (FAST) key points are applied to local features construction and tamper localization. By applying the concept of multi-feature combination to the integrity authentication of HRRS images, the authentication process is more convincing in comparison to existing algorithms. Furthermore, an interpretable authentication result can be given. The experimental results show that the algorithm proposed in this paper is highly robust to the content retention operation, has a strong sensitivity to the content changing operations, and the result of tampering localization is more precise comparing with existing algorithms.

IRBA: An Identity-Based Cross-Domain Authentication Scheme for the Internet of Things

The incredible development of Internet of things technology promotes the integration of application systems, which enable people to enjoy the convenience of multiple application services through a single intelligent device or terminal. In order to implement value exchange and information sharing between different applications, cross-domain access is inevitable. In order to prevent illegal access, identity authentication is necessary before the terminal accesses the service. Because of the need to introduce a trusted third party, the traditional centralized authentication model not only destroys the autonomy and flexibility of the application system, but also causes issues such as single point of failure and hidden dangers of unilateral control. This paper proposes an identity-based cross-domain authentication scheme for the Internet of Things. This scheme uses the Blockchain as a decentralized trust anchor instead of the traditional certificate of authority, and uses the identity-based self-authentication algorithm to replace the traditional PKI authentication algorithm. The scheme proposed in this paper implements a decentralized authentication model, which can guarantee the autonomy and initiative of the security domain.

Integration of Proposed Authentication Algorithm for End User Data Navigation in Data Warehouse

Data Warehouse epitomizes an assortment of databases that originate from diverse foundations. They are cohesive within the organization and are employed for incapacitating glitches and furnishing with apposite pronouncements. Data Warehouse encompasses diversity of information which proffers a comprehensible image of the concern’s fiscal circumstances at any specific instant. Data Warehouse safekeeping is an imperious functionality that entails upkeep and attention of exertions, since the information is stowed in a solitary setting. Data Mart is an unpretentious form of Data Warehouse, which is engrossed on a solitary theme (Purposeful zone). Data Marts are habitually constructed and controlled by a solitary division within an organization. The proposed work induces attention towards Data Mart safekeeping as well as safeguarding Data Warehouse. Integration of proposed Authentication Algorithm for end user data navigation in Data Warehouse has been comprehensively ensured through the projected work as well. It not only safeguards solitary Data Mart but additional autonomous Data Marts also, operating in parallel with other reliant Data Marts dwelling in the Data Warehouse. Correlated utilization of the projected work is in a miscellany of organizations, where accretion of credible record is of utmost implication. The assortment of organization grips an incorporation of pedagogic establishments, commercial groups, curative remedial initiatives, safekeeping bureaus with subtle facts, categorized initiatives and onward.

A Multi-User, Single-Authentication Protocol for Smart Grid Architectures.

In a smart grid system, the utility server collects data from various smart grid devices. These data play an important role in the energy distribution and balancing between the energy providers and energy consumers. However, these data are prone to tampering attacks by an attacker, while traversing from the smart grid devices to the utility servers, which may result in energy disruption or imbalance. Thus, an authentication is mandatory to efficiently authenticate the devices and the utility servers and avoid tampering attacks. To this end, a group authentication algorithm is proposed for preserving demand–response security in a smart grid. The proposed mechanism also provides a fine-grained access control feature where the utility server can only access a limited number of smart grid devices. The initial authentication between the utility server and smart grid device in a group involves a single public key operation, while the subsequent authentications with the same device or other devices in the same group do not need a public key operation. This reduces the overall computation and communication overheads and takes less time to successfully establish a secret session key, which is used to exchange sensitive information over an unsecured wireless channel. The resilience of the proposed algorithm is tested against various attacks using formal and informal security analysis.

Research and implementation of information security for intelligent distribution network

The intelligent distribution network is an important hub for connecting power generation and users, and the security of its information is closely related to the stable operation of the power grid. In order to solve the contradiction between the security and real-time of information in intelligent distribution network according to Supplementary Provisions for Safety Protection of Medium and Low Voltage Distribution Network Automation System, an information security model of intelligent distribution network is proposed, after deeply studying AES encryption algorithm and SHA-256 authentication algorithm, using OPNET as simulation software for smart distribution network information to carryout transmission delay curve. FPGA is used as information security processing platform. We obtain the total delay, analyze the integrity and availability. The experiment proves that the intelligent distribution network information security processing solution satisfies the three elements of CIA information security, and has good confidentiality, integrity and availability.

DNA Computing Based Encryption Algorithm for Wireless Multimedia Communication System

Transmission of digital images for wireless multimedia communication system requires reliable security in storage which is a challenging task. So many works are carried out to develop and implement the cryptographic techniques for a wireless multimedia communication system. A traditional symmetric key cryptographic algorithm such as Light weight Data Encryption Standard cipher, Advanced Encryption Standard cipher, Triple-DES, Twofish, Blowfish, RC5 etc played a major role to transmit and receive the multimedia (text, image and video) data. Proposed DNA computing based authentication algorithm provides secure transmission of multimedia data by using symmetric key cryptography techniques. DNA computing techniques provides a higher level of security and enables the user to store a large amount of data. Finally, it shows the implemented result analysis the performance of different symmetric key cryptographic techniques using the simulation parameters such as power consumption, key size, processing time, memory space, speed and latency. It also improves the security level by incorporating the advantage of DNA cryptography to achieve a high level of security against various attacks.

DHCPv6Auth: a mechanism to improve DHCPv6 authentication and privacy

Internet Protocol version 6 (IPv6) deployment continues to gain ground due to the increasing demand for IP addresses generated by the number of Internet facing devices, and it is compounded by the exhaustion of allocatable IPv4 addresses. Dynamic Host Configuration Protocol version 6 (DHCPv6) is used to allocate IPv6 addresses and distribute network configuration information to IPv6 hosts in a link-local network. However, DHCPv6 messages in transit expose identifiable information of the DHCPv6 client that could be used by malicious users to track their victims. Additionally, the lack of an authentication mechanism leaves IPv6 hosts vulnerable to rogue DHCPv6 server attacks. This paper introduces DHCPv6 Authentication (DHCPv6Auth) mechanism to prevent rogue DHCPv6 server attacks and protect the privacy of IPv6 hosts. DHCPv6Auth uses the Ed25519 digital signature algorithm for authentication and could be used in conjunction with Anonymity Profile mechanisms for privacy protection. The DHCPv6Auth mechanism was compared with other mechanisms in terms of processing time, prevention of rogue DHCPv6 server attack, and protection of users’ privacy. The results show that it requires less processing time and traffic overhead than other authentication mechanisms; is able to prevent rogue DHCPv6 server attacks; and provides better privacy protection for the IPv6 host than other authentication mechanisms to which it was compared.