This study presents a secret key sharing protocol that establishes cryptographically secured communication between two entities. A new symmetric key exchange scenario for smart city applications is ...presented in this research. The protocol is based on the specific properties of the Fuss-Catalan numbers and the Lattice Path combinatorics. The proposed scenario consists of three phases: generating a Fuss-Catalan object based on the grid dimension, defining the movement in the Lattice Path Grid and defining the key equalisation rules. In the experimental part, the authors present the security analysis of the protocol as well as its test. Also, they examine the equivalence of the proposed with Maurer's satellite scenario and suggest a new scenario that implements an information-theoretical protocol for the public key distribution. Additionally, a comparison with related studies and methods is provided, as well as a comparison with satellite scenario, which proves the advantages of solution presented by the authors. Finally, they propose further research directions regarding key management in smart city applications.
This paper presents a novel iris recognition system based on machine learning methods. The motivation behind this research resides in the interrelatedness of biometric systems and stylometry, as ...shown in our previous research. The main goal of the proposed model is to reach virtually perfect classification accuracy, eliminate false acceptance rates, and cancel the possibility of recreating an iris image from a generated template. To achieve this, we omit Gabor wavelets and other filter banks typically employed in iris recognition systems based on the pioneering work of John Daugman. Instead, we employ machine learning methods that classify biometric templates as numeric features. The biometric templates are generated by converting a normalized iris image into a one-dimensional set of fixed-length codes, which then undergoes stylometric feature extraction. The extracted features are further used for classification. A new recognition method is developed using the CASIA iris database, and its generalizability is demonstrated on the MMU and IITD iris databases separately, and also on their unification with the CASIA database, by applying oversampling before and during the cross-validation procedure. The experimental evaluation shows that the system performs as intended. In addition, the computational costs are significantly decreased with respect to traditional systems, which in turn reduces the overall complexity of the recognition system, making it suitable for use in practical applications.
•Virtually perfect classification with zero false acceptance rates.•Extremely low false rejection rates originating from noise.•Reduced biometric template size to 128 and 256 bits.•Inability to recreate original iris image from template.•Reduced computational costs.
This paper presents a new method of data hiding using Catalan numbers and Dyck words. The proposed steganographic solution belongs to the category of techniques based on the key generating process, ...rather than steganographic techniques such as injecting or substituting bits. The complex stego key consists of three sets of values that provide the technique of a hidden message generation completely. Hidden message is generated based on the data carrier and an adequate complex stego key. An important characteristic of the proposed method is that the data carrier retains its original shape, without supplements or modifications. Proposed method is explained in detail through the general scenario and through concrete examples. State of the art steganographic analysis of the proposed solution is presented in this paper, as well as possible suggestions for application in business information systems, authentication and distribution of secret cryptographic keys.
•Novel data hiding method using Catalan numbers and Dyck words.•Data carrier retains its’ original shape.•Implementation in Java proofs the work.•State of art machine learning analysis proofs the security of the system.
Internet of Things and Blockchain are considered two major technologies. Lower latency and a higher linked system number provide greater flexibility for remote execution of Internet of Things (IoT) ...applications. It is no secret that IoT devices often have insufficient computing capacity (both in terms of processing power and storage requirements) to support robust protection and encryption algorithms. The Internet of Things is facing many challenges such as poor interoperability, security vulnerabilities, privacy, and lack of industry standards. Cyber-attacks on IoT devices can have an impact on energy trading privacy and security. This paper suggests a method for introducing a basic interface to an IoT device’s security gateway architecture along with Blockchain to provide decentralization and authentication. It adds much-needed anonymity and versatility to IoT infrastructure, which is currently lacking. The solution enhances the reliability of data sent to remote services by applying compatible cryptographic algorithms to it before sending it. The solution’s benefits include compatibility with all IoT products and the ability to run any cryptographic algorithm on data that can be used for microgrid trading and can be initialized and securely transported over 5G or 6G network infrastructures. As a part of this work, a security procedure has been created that supports every cryptographic algorithm for all IoT devices in the network. In addition, the interface is guarded by the Blockchain technology which eliminates single control authority, records historical transactions performed by the IoT devices and provides a trust between devices.
Applying machine learning techniques and methods in biometric recognition has gained significant attention in recent years as it can provide a better performance, high accuracy, and cancellable ...biometrics data. This paper proposes a new approach for fingerprint recognition based on machine learning methods and stylometric features. The proposed solution deals with fingerprint recognition, cancellability, stylometry, blockchain and machine learning. This research uses machine learning methods that classify fingerprint templates as a numeric feature instead of using Gabor wavelets and filters. The proposed method gives very high accuracy for biometric fingerprint templates. For these reasons, we additionally consider the use of an internal blockchain in the form of a distributed database that implements all security services, including privacy protection. Because the recognition method is based on machine learning, the generated templates are a numerical data type and take up minimal memory size, which further favors the application of a blockchain and enables implementation even in IoT devices. We generate the fingerprint biometric template by converting an enhanced fingerprint image into a 1-D set of fixed length codes. After that, we extract stylometric features that will be used for classification. The experiment is conducted on the CASIA-FingerprintV5 and achieved excellent results where the CatBoost method with over-sampling (SMOTE) achieved the best results for All_features(42) and GRRF(10) sets with 99.95% accuracy and 99.98%, respectively, and FAR 0.0007 and 0.0003, respectively. In addition, the proposed system significantly decreased the computational costs which makes it suitable for other applications.
It is not a secret that Internet of Things (IoT) devices often come with not so realistic processing power (i.e. processing power and storage requirements) that would provide a basis for strong ...security and encryption algorithms. This work proposes an approach to adding a simple interface as a security gateway architecture for IoT devices. The security interface provides mapping for the IoT device remote services as long as support for stronger cryptographic algorithms. The solution improves the security of the data that IoT devices send to remote services by performing compatible cryptographic algorithms on the data before it sends to remote services. The result of this work is the development of a security interface that provides support for any cryptographic algorithm, uses Internet Protocol (IP) mapping to prevent access to the devices behind the interface from non-authorized IP addresses. As such it provides robust protection against attacks and data manipulation. The work is tested for memory usage and the strength of the security it provides.
Modern access controls employ biometrics as a means of authentication to a great extent. For example, biometrics is used as an authentication mechanism implemented on commercial devices such as ...smartphones and laptops. This paper presents a fingerprint biometric cryptosystem based on the fuzzy commitment scheme and convolutional neural networks. One of its main contributions is a novel approach to automatic discretization of fingerprint texture descriptors, entirely based on a convolutional neural network, and designed to generate fixed-length templates. By converting templates into the binary domain, we developed the biometric cryptosystem that can be used in key-release systems or as a template protection mechanism in fingerprint matching biometric systems. The problem of biometric data variability is marginalized by applying the secure block-level Bose–Chaudhuri–Hocquenghem error correction codes, resistant to statistical-based attacks. The evaluation shows significant performance gains when compared to other texture-based fingerprint matching and biometric cryptosystems.
This paper introduces a heuristic for multiple sequence alignment aimed at improving real-time object recognition in short video streams with uncertainties. It builds upon the idea of the progressive ...alignment but is cognitively economical to the extent that the underlying edit distance approach is adapted to account for human working memory limitations. Thus, the proposed heuristic procedure has a reduced computational complexity compared to optimal multiple sequence alignment. On the other hand, its relevance was experimentally confirmed. An extrinsic evaluation conducted in real-life settings demonstrated a significant improvement in number recognition accuracy in short video streams under uncertainties caused by noise and incompleteness. The second line of evaluation demonstrated that the proposed heuristic outperforms humans in the post-processing of recognition hypotheses. This indicates that it may be combined with state-of-the-art machine learning approaches, which are typically not tailored to the task of object sequence recognition from a limited number of frames of incomplete data recorded in a dynamic scene situation.
This paper will show one of many possible hardware implementations of random
sequence generators and give a short survey on existing work related to
techniques used for producing true random bits. By ...using cheap electronic
components found in every specialized store such as 8-bit RISC
microcontroler, double analogue comparator chip and USB to RS232 interface
integrated circuit, we were able to produce a low cost, higly portable device
that outputs random sequences with excellent statistical characteristics and
high entropy. The source of randomness is a mix of techniques such as
electronic noise, phase noise and oscillator jitter. The device in question
has a built-in debiasing algorithm similar to 1 and a security mechanism
that protects the end user by constantly monitoring the quality of digitized
noise signal. Finaly, we will show the results of comparative analysis of
data acquired from our device and ?random.org? online service.
nema
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