High-level Authentication Research Articles

Cross-layer Authentication Mechanism Model Combined with 5G Converged Channel Fingerprint

In the actual communication environment, once the attacker successfully steals the legitimate channel information, the key information can be cracked according to the authentication response, so there is a security risk of key leakage. This paper combines the physical layer channel characteristics with the shared key, and combines it into a joint key to design a challenge-response physical layer authentication mechanism based on interpolation polynomial. Then, this method is applied to the EAP-AKA’ authentication protocol of 5G network, and a cross-layer authentication mechanism for 5G converged channel fingerprint is proposed. Finally, using the captured high-level authentication challenge response data, a simulation environment is built in MATLAB and the feasibility and security of the scheme are verified. The experimental results show that the authentication mechanism has better authentication performance and security performance. Compared with the traditional high-level authentication mechanism, it has certain advantages in computing overhead and can meet the 5G application scenarios of large-scale IoT terminals. Moreover, it combines physical layer authentication with high-level authentication, realizes mutual complementarity and mutual enhancement, and enhances the security performance of authentication.

Enhancing medical image security through machine learning and dual watermarking-based technique

ABSTRACT As the world becomes increasingly digital, healthcare is no exception. With the ease of sharing e-healthcare records over open networks, smart healthcare systems have become a popular way to manage patient information. But as the popularity of these systems has grown, so has the concern for their security. That's where image security techniques come in. In this paper we have developed a new approach to secure e-patient records like DICOM images. By combining the redundant discrete wavelets transform (RDWT), Hessenberg Decomposition (HD), and randomized singular value decomposition (RSVD). We developed a robust and dual watermarking scheme. This scheme uses multiple watermarks, including Electronic Patient Record (EPR) as text and images, to ensure high-level authentication. In order to attain a balance between imperceptibility and robustness, a PSO-based optimization of scale factor is employed and Turbo code is utilized to encode the EPR and minimize channel noise. Additionally, the marked image undergoes encryption using a 3D chaotic-based encryption technique, and the extracted watermark is denoised through a deep neural network. The result shows that the proposed scheme is both secure and reliable. With this dual watermarking scheme, we have made great strides in securing e-patient records.

BLOCK CHAIN-BASED BIOMETRIC AUTHENTICATION SCHEME

Data security is one aspect of the digital era, and it is recommended that biometrics and block chain be used together as an original and reliable method of protecting sensitive data. As high-level authentication methods, biometric technologies are often utilized in the modern world in place of passwords because they are more difficult for hackers to crack. At this point, the block chain can actually serve as a rapid access method while providing high degrees of security. Any authentication process generates digital signatures using a common hashing method. This paper describes the hashing method's use in the block chain system to process identical digital signatures.

Optical multilevel authentication based on singular value decomposition ghost imaging and secret sharing cryptography

An optical multilevel authentication method is proposed that is based on the singular value decomposition ghost imaging (SVDGI) and (t, n) threshold secret sharing scheme. SVDGI provides an efficient reconstruction method in ghost imaging (GI) by modifying the measurement matrix with the help of singular value decomposition, which enables the reconstruction of an N-pixel image utilizing much less than N measurements with less time and a higher quality. On the other hand, the (t, n) threshold secret sharing algorithm guarantees the multilevel authentication system, in which, the modified measurement matrix is grouped into n parts as n keys and distributed to n different participants, any t (t ≤ n) or more of authorized participants with their correct keys can be collected to restore the original meaningful certification image, which is so called the high-level authentication; While in the case of low-level authentication, any t - 1 or fewer will gain no exact information of the certification image, but a remarkable peak output can be acquired in the 3D distribution of the nonlinear correlation coefficient of the standard certification image and the recovered image. So that the method successfully provides a multilevel authentication. Both numerical simulations and optical experiments validate the feasibility of the proposed method.

Authentication Using Metallic Inkjet-Printed Chipless RFID Tags

A high-level (i.e., in terms of security) authentication method is proposed in this communication, where the chipless RFID is extended to the chipless authentication. The proposed method is based on low-cost inkjet-printed square-check-patterned chipless tags, whose design is explicitly optimized keeping the randomness inherent to the inkjet-printing process in view. These optimized chipless tags are very difficult to duplicate, as their unique backscattered EM responses depend on proximate coupling among the possible separated squares that happened naturally due to the randomness of inkjet printing. The performance of the proposed method is analyzed by a low-cost impulse radio (IR) UWB chipless RFID reader as well as by the highly accurate VNA-based chipless RFID reader. The achieved probability of error is comparable to the various fingerprint evaluation campaigns found in the literature.

Securing Communication in IoT Ecosystem Using Cryptographic Algorithms

Internet of Things (IoTs) is defined as an ever-growing network, which comprises of numerous physical objects with a specific IP address along with wireless internet communication, which enables the process of information sharing between two objects. Due to the frequent transfer and exchange of high confidential data between two devices through internet, there arise some susceptible attacks in IoT such as denial of service, eavesdropping attack and so on. A high-level authentication protocol and cryptographic techniques are required to resolve the issue of vulnerable attack and data loss. The current study presents a review of various IoT models and applications. Furthermore, the concerns related to security with respect to data sharing and numerous attacks have been featured in this paper. In order to avoid and minimize these attacks, numerous security measures and cryptographic algorithms have been developed by different authors. The study on several existing protocols has been carried out in this research along with the study on authentication algorithm developed by the authors. The result section contrasts a brief idea about the key requirements for the data security and authentication for the future aspects along with necessity of memory and power utilization. Additionally, some examination has been carried out briefing the future directions in which additionally work would be possible on the development of lightweight cryptography protocols.

A Systematic Review for Enabling of Develop a Blockchain Technology in Healthcare Application: Taxonomy, Substantially Analysis, Motivations, Challenges, Recommendations and Future Direction.

Blockchain in healthcare applications requires robust security and privacy mechanism for high-level authentication, interoperability and medical records sharing to comply with the strict legal requirements of the Health Insurance Portability and Accountability Act of 1996. Blockchain technology in the healthcare industry has received considerable research attention in recent years. This study conducts a review to substantially analyse and map the research landscape of current technologies, mainly the use of blockchain in healthcare applications, into a coherent taxonomy. The present study systematically searches all relevant research articles on blockchain in healthcare applications in three accessible databases, namely, ScienceDirect, IEEE and Web of Science, by using the defined keywords 'blockchain', 'healthcare' and 'electronic health records' and their variations. The final set of collected articles related to the use of blockchain in healthcare application is divided into three categories. The first category includes articles (i.e. 43/58 scientific articles) that attempted to develop and design healthcare applications integrating blockchain, particularly those on new architecture, system designs, framework, scheme, model, platform, approach, protocol and algorithm. The second category includes studies (i.e., 6/58 scientific articles) that attempted to evaluate and analyse the adoption of blockchain in the healthcare system. Finally, the third category comprises review and survey articles (i.e., 6/58 scientific articles) related to the integration of blockchain into healthcare applications. The final articles for review are discussed on the basis of five aspects: (1) year of publication, (2) nationality of authors, (3) publishing house or journal, (4) purpose of using blockchain in health applications and the corresponding contributions and (5) problem types and proposed solutions. Additionally, this study provides identified motivations, open challenges and recommendations on the use of blockchain in healthcare applications. The current research contributes to the literature by providing a detailed review of feasible alternatives and identifying the research gaps. Accordingly, researchers and developers are provided with appealing opportunities to further develop decentralised healthcare applications through a comprehensive discussion of about the importance of blockchain and its integration into various healthcare applications.

Vein Enhancement Using a Dark Diffusion Prior

Vein recognition is emerging as a good alternative to the high-level biometric authentication due to its robustness against forgery. However, the poor quality of the vein image still poses a great difficulty to the extension of its usability. In this letter, we propose a novel method for vein enhancement based on a dark diffusion prior. The key idea of the proposed method is to reveal the characteristics of veins, which absorbs the near infrared well compared to background, by exploring multiple diffusion spaces. In contrast to previous approaches, the proposed method does not yield the blurring effect while efficiently suppressing unwanted noise. Experimental results on the benchmark database show that the proposed method is effective for vein recognition compared to other enhancement schemes introduced in the literature.

Received Signal Strength Based Gait Authentication

Expansion of wireless body area networks applications, such as health-care, m-banking, and others has lead to vulnerability of privacy and personal data. An effective and unobtrusive natural method of authentication is therefore a necessity in such applications. Accelerometer-based gait recognition has become an attractive solution, however, continuous sampling of accelerometer data reduces the battery life of wearables. This paper investigates the usage of received signal strength indicator (RSSI) as a source of gait recognition. Unlike the accelerometer-based method, the RSSI approach does not require additional sensors (hardware) or sampling of them, but uses the RSSI values already available in all radio devices. Three radio channel features namely, the time series, auto-correlation function, and level crossing rate were extracted from unique signature of the RSSI in relation to the corresponding subject. The extracted features were then used together with four different classification learners, namely decision tree, support vector machine, $k$ -nearest neighbors, and artificial neural network, to evaluate the method. The best performance was achieved utilizing artificial neural network with 95% accuracy when the features were extracted from one on-body radio channel (right wrist to waist), and 98% when the features were extracted from two on-body radio channels (right wrist to waist, and left wrist to waist). The developed RSSI-based gait authentication approach can complement high-level authentication methods for increased privacy and security, without additional hardware, or high energy consumption existing in accelerometer-based solutions.

Multilevel image authentication using row scanning compressive ghost imaging and hyperplane secret sharing algorithm

A multilevel image authentication method is proposed which is based on row scanning compressive ghost imaging and a hyperplane secret sharing algorithm. In the image encoding process, after the wavelet transform and Arnold transform for the certification image, through row scanning compressive ghost imaging, the ciphertext matrix can be first detected by a bucket detector (BD). Based on a hyperplane secret sharing algorithm, the measurement key using in the row scanning compressive ghost imaging, can be decomposed and shared into n subkeys, which are then distributed to n different participants. In the high-level authentication process, based on a hyperplane secret sharing algorithm and a compressive reconstruction algorithm, any t or more participants with the corresponding correct subkeys can be gathered to reconstruct the original meaningful certification image with high correlation coefficient (CC); While in the case of low-level authentication process, only one authenticator who possesses a correct subkey will gain no significant information of certification image, however, it can result in a remarkable peak output in the nonlinear correlation coefficient distribution. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.

Formula omitted]: Capacity-aware security access authentication in federated-IoT-enabled V2G networks

Vehicle-to-Grid (V2G) systems promoted by the federated Internet of Things (IoT) technology will be ubiquitous in the future; therefore, it is crucial to provide trusted, flexible and efficient operations for V2G services using high-quality measures for security and privacy. These can be achieved by access and authority authentication. This paper presents a lightweight protocol for capacity-based security access authentication named AccessAuth. Considering the overload probability and system capacity constraints of the V2G network domain, as well as the mobility of electric vehicles, the ideal number of admissible access requests is first calculated adaptively for each V2G network domain to actively achieve capacity-based access admission control. Subsequently, to provide mutual authentication and maintain the data privacy of admitted sessions, by considering whether there is prior knowledge of the trust relationship between the relevant V2G network domains, a high-level authentication model with specific authentication procedures is presented to enforce strict access authentication such that the sessions are conducted only by authorized requesters. Additionally, efficient session revocation with forward security and session recovery with no extra authentication delay are also discussed. Finally, analytical and evaluation results are presented to demonstrate the performance of AccessAuth.

Two-level image authentication by two-step phase-shifting interferometry and compressive sensing

A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.

Hierarchical multilevel authentication system for multiple-image based on phase retrieval and basic vector operations

A hierarchical multilevel authentication system for multiple-image based on phase retrieval and basic vector operations in the Fresnel domain is proposed, by which more certification images are iteratively encoded into multiple cascaded phase masks according to different hierarchical levels. Based on the secret sharing algorithm by basic vector decomposition and composition operations, the iterated phase distributions are split into n pairs of shadow images keys (SIKs), and then distributed to n different participants (the authenticators). During each level in the high authentication process, any 2 or more participants can be gathered to reconstruct the original meaningful certification images. While in the case of each level in the low authentication process, only one authenticator who possesses a correct pair of SIKs, will gain no significant information of certification image; however, it can result in a remarkable peak output in the nonlinear correlation coefficient of the recovered image and the standard certification image, which can successfully provide an additional authentication layer for the high-level authentication. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.

A kind of multilevel authentication system for multiple-image by modulated real part synthesis and iterative phase multiplexing

A kind of multilevel authentication system for multiple-image based on modulated real part synthesis and iterative phase multiplexing in the Fresnel domain is proposed. In the design process of the low-level authentication system, a series of normalized real part information are iteratively generated by phase retrieval algorithm in the Fresnel domain, and the final private keys for different individual low-level certification images can be fabricated by binary amplitude modulation, superposition, synthesis, and sampling; while in the design process of the high-level authentication system, the final private keys for different individual high-level certification images can be generated by iterative phase information encoding and multiplexing. During the high-level authentication, the meaningful certification image can be reconstructed by the inverse Fresnel transform with the corresponding correct private keys, meanwhile, the correlation coefficient is utilized as judgment criterion; while in the low-level authentication, with the help of correct keys, the noise-like image with meaningless information can be recovered, but a remarkable peak output in the nonlinear correlation coefficient can be generated, which is adopted as the criterion to judge whether the low-level authentication is successful or not. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.

Multiple-image authentication with a cascaded multilevel architecture based on amplitude field random sampling and phase information multiplexing.

A multiple-image authentication method with a cascaded multilevel architecture in the Fresnel domain is proposed, in which a synthetic encoded complex amplitude is first fabricated, and its real amplitude component is generated by iterative amplitude encoding, random sampling, and space multiplexing for the low-level certification images, while the phase component of the synthetic encoded complex amplitude is constructed by iterative phase information encoding and multiplexing for the high-level certification images. Then the synthetic encoded complex amplitude is iteratively encoded into two phase-type ciphertexts located in two different transform planes. During high-level authentication, when the two phase-type ciphertexts and the high-level decryption key are presented to the system and then the Fresnel transform is carried out, a meaningful image with good quality and a high correlation coefficient with the original certification image can be recovered in the output plane. Similar to the procedure of high-level authentication, in the case of low-level authentication with the aid of a low-level decryption key, no significant or meaningful information is retrieved, but it can result in a remarkable peak output in the nonlinear correlation coefficient of the output image and the corresponding original certification image. Therefore, the method realizes different levels of accessibility to the original certification image for different authority levels with the same cascaded multilevel architecture.

Watermarking approach to embedded signature-based authentication by channel statistics

Embedded signature-based authentication is a highly promis- ing watermarking method for solving high-level authentication problems. This work proposes such a watermarking approach using channel sta- tistics evaluated from a reference watermark. The basic concept is to consider the problem to be an example of communications with side information, which is the reference watermark embedded in the host with the signature at the sender site. At the receiver site, the reference wa- termark is first extracted to determine channel statistics, which are used to generate information about signature reliability. Three kinds of infor- mation are derived, including a reliability measure, an entropy measure, and an authenticated signature. Experimental results establish that the measures of reliability and uncertainty are meaningful, and that the em- bedded signature can survive high-quality JPEG compression and ma- nipulations such as negation, cropping, replacement, and modification. © 2003 Society of Photo-Optical Instrumentation Engineers.