Zeitschriften und Ausgaben

Volumen 22 (2022): Heft 3 (September 2022)

Volumen 22 (2022): Heft 2 (June 2022)

Volumen 22 (2022): Heft 1 (March 2022)

Volumen 21 (2021): Heft 4 (December 2021)

Volumen 21 (2021): Heft 3 (September 2021)

Volumen 21 (2021): Heft 2 (June 2021)

Volumen 21 (2021): Heft 1 (March 2021)

Volumen 20 (2020): Heft 6 (December 2020)
Special Heft on New Developments in Scalable Computing

Volumen 20 (2020): Heft 5 (December 2020)
Special issue on Innovations in Intelligent Systems and Applications

Volumen 20 (2020): Heft 4 (November 2020)

Volumen 20 (2020): Heft 3 (September 2020)

Volumen 20 (2020): Heft 2 (June 2020)

Volumen 20 (2020): Heft 1 (March 2020)

Volumen 19 (2019): Heft 4 (November 2019)

Volumen 19 (2019): Heft 3 (September 2019)

Volumen 19 (2019): Heft 2 (June 2019)

Volumen 19 (2019): Heft 1 (March 2019)

Volumen 18 (2018): Heft 5 (May 2018)
Special Thematic Heft on Optimal Codes and Related Topics

Volumen 18 (2018): Heft 4 (November 2018)

Volumen 18 (2018): Heft 3 (September 2018)

Volumen 18 (2018): Heft 2 (June 2018)

Volumen 18 (2018): Heft 1 (March 2018)

Volumen 17 (2017): Heft 5 (December 2017)
Special Heft With Selected Papers From The Workshop “Two Years Avitohol: Advanced High Performance Computing Applications 2017

Volumen 17 (2017): Heft 4 (November 2017)

Volumen 17 (2017): Heft 3 (September 2017)

Volumen 17 (2017): Heft 2 (June 2017)

Volumen 17 (2017): Heft 1 (March 2017)

Volumen 16 (2016): Heft 6 (December 2016)
Special issue with selection of extended papers from 6th International Conference on Logistic, Informatics and Service Science LISS’2016

Volumen 16 (2016): Heft 5 (October 2016)
Heft Title: Special Heft on Application of Advanced Computing and Simulation in Information Systems

Volumen 16 (2016): Heft 4 (December 2016)

Volumen 16 (2016): Heft 3 (September 2016)

Volumen 16 (2016): Heft 2 (June 2016)

Volumen 16 (2016): Heft 1 (March 2016)

Volumen 15 (2015): Heft 7 (December 2015)
Special Heft on Information Fusion

Volumen 15 (2015): Heft 6 (December 2015)
Special Heft on Logistics, Informatics and Service Science

Volumen 15 (2015): Heft 5 (April 2015)
Special Heft on Control in Transportation Systems

Volumen 15 (2015): Heft 4 (November 2015)

Volumen 15 (2015): Heft 3 (September 2015)

Volumen 15 (2015): Heft 2 (June 2015)

Volumen 15 (2015): Heft 1 (March 2015)

Volumen 14 (2014): Heft 5 (December 2014)
Special Heft

Volumen 14 (2014): Heft 4 (December 2014)

Volumen 14 (2014): Heft 3 (September 2014)

Volumen 14 (2014): Heft 2 (June 2014)

Volumen 14 (2014): Heft 1 (March 2014)

Volumen 13 (2013): Heft Special-Heft (December 2013)

Volumen 13 (2013): Heft 4 (December 2013)
The publishing of the present issue (Volumen 13, No 4, 2013) of the journal “Cybernetics and Information Technologies” is financially supported by FP7 project “Advanced Computing for Innovation” (ACOMIN), grant agreement 316087 of Call FP7 REGPOT-2012-2013-1.

Volumen 13 (2013): Heft 3 (September 2013)

Volumen 13 (2013): Heft 2 (June 2013)

Volumen 13 (2013): Heft 1 (March 2013)

Volumen 12 (2012): Heft 4 (December 2012)

Volumen 12 (2012): Heft 3 (September 2012)

Volumen 12 (2012): Heft 2 (June 2012)

Volumen 12 (2012): Heft 1 (March 2012)

Zeitschriftendaten
Format
Zeitschrift
eISSN
1314-4081
Erstveröffentlichung
13 Mar 2012
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

Suche

Volumen 20 (2020): Heft 3 (September 2020)

Zeitschriftendaten
Format
Zeitschrift
eISSN
1314-4081
Erstveröffentlichung
13 Mar 2012
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

Suche

12 Artikel
Uneingeschränkter Zugang

CRUDyLeaf: A DSL for Generating Spring Boot REST APIs from Entity CRUD Operations

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 3 - 14

Zusammenfassung

Abstract

Domain-Specific Languages (DSLs) are programming languages designed specifically to express solutions to problems in a particular domain. It is said they foster productivity and quality. In this work we describe CRUDyLeaf, a DSL focused on the generation of Spring Boot REST APIs from entity CRUD operations. Spring Boot is an open source Java-based framework used to implement the REST architecture style. It has gained popularity among developers mainly because it allows to build stand-alone and production ready software applications (avoiding the use of an application server). Through seven proposed stages (domain immersion, golden application implementation, syntax definition, meta model generation, code generator implementation, deployment, and refinement) we describe the development of this DSL. We also exemplify and evaluate the proposed DSL. Our findings suggest a yield automation rate of 32.1 LOC (Lines Of Code) for each LOC written in this DSL, among other observed benefits.

Schlüsselwörter

  • CRUDyLeaf
  • DSL
  • Domain-Specific Language
  • Software Engineering
  • Spring Boot
Uneingeschränkter Zugang

Agile Elastic Desktop Corporate Architecture for Big Data

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 15 - 31

Zusammenfassung

Abstract

New challenges in the dynamically changing business environment require companies to experience digital transformation and more effective use of Big Data generated in their expanding online business activities. A possible solution for solving real business problems concerning Big Data resources is proposed in this paper. The defined Agile Elastic Desktop Corporate Architecture for Big Data is based on virtualizing the unused desktop resources and organizing them in order to serve the needs of Big Data processing, thus saving resources needed for additional infrastructure in an organization. The specific corporate business needs are analyzed within the developed R&D environment and, based on that, the unused desktop resources are customized and configured into required Big Data tools. The R&D environment of the proposed Agile Elastic Desktop Corporate Architecture for Big Data could be implemented on the available unused resources of hundreds desktops.

Schlüsselwörter

  • Agile Elastic Desktop Corporate Architecture
  • Desktop Virtualization
  • Big Data
  • Digital Transformation
Uneingeschränkter Zugang

Microservices Centric Architectural Model for Handling Data Stream Oriented Applications

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 32 - 44

Zusammenfassung

Abstract

The present-day software application systems are highly complex with many requirements and variations, which can only be handled by more than one architectural pattern. This paper focuses on a combinational architectural design, with the micro-services at the center and supported by the model view controller and the pipes and filter architectural patterns to realize any data stream-oriented application. The proposed model is very generic and for validation, a prototype GIS application has been considered. The application is designed to extract GIS data from internet sources and process the data using third party processing tools. The overall design follows the micro-services architecture and the processing segment is designed using pipes-and-filters architectural pattern. The user interaction is made possible with the use of the model view controller pattern. The versatility of the application is expressed in its ability to organize any number of given filters in a connected structure that agrees with inter-component dependencies. The model includes different services, which make the application more user-friendly and secure by prompting client for authentication and providing unique storage for every client. This approach is very much useful for building applications with a high degree of flexibility, maintainability and adaptability. A qualitative comparison is made using a set of criteria and their implementation using the different architectural styles.

Schlüsselwörter

  • Architectural Pattern
  • Microservices
  • Model View Controller
  • Pipes and Filters
  • Software Architecture
Uneingeschränkter Zugang

Cluster-Based Optimization of an Evacuation Process Using a Parallel Bi-Objective Real-Coded Genetic Algorithm

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 45 - 63

Zusammenfassung

Abstract

This work presents a novel approach to the design of a decision-making system for the cluster-based optimization of an evacuation process using a Parallel bi-objective Real-Coded Genetic Algorithm (P-RCGA). The algorithm is based on the dynamic interaction of distributed processes with individual characteristics that exchange the best potential decisions among themselves through a global population. Such an approach allows the HyperVolume performance metric (HV metric) as reflected in the quality of the subset of the Pareto optimal solutions to be improved. The results of P-RCGA were compared with other well-known multi-objective genetic algorithms (e.g., -MOEA, NSGA-II, SPEA2). Moreover, P-RCGA was aggregated with the developed simulation of the behavior of human agent-rescuers in emergency through the objective functions to optimize the main parameters of the evacuation process.

Schlüsselwörter

  • Cluster-based multi-objective optimization
  • human crowd behavior
  • real-coded genetic algorithms
  • multi-agent systems
  • fuzzy clustering
Uneingeschränkter Zugang

Activity Recognition on Subject Independent Using Machine Learning

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 64 - 74

Zusammenfassung

Abstract

Recent Activity Daily Living (ADL) not only tackles simple activities, but also caters to a wide range of complex activities. Although the same activity has been carried out under the same environmental conditions, the acceleration signal obtained from each subject considerably differs. This happens due to the pattern of action generated for each subject is diverse based on several aspects such as subject age, gender, emotion and personality. This project therefore compares the accuracy of various machine learning models for ADL classification. On top of that, this research work also scrutinizes the effectiveness of various feature selection methods to identify the most relevant attribute for ADL classification. As a result, Random Forest was able to achieve the highest accuracy of 83.3% on subject independent matter in ADL classification. Meanwhile, CFS Subset Evaluator is considered to be a good feature selector as it successfully selected the 8 most relevant features compared with Correlation and Information Gain Evaluator.

Schlüsselwörter

  • Activity Daily Living (ADL)
  • accelerometer
  • wearable sensor
  • machine learning
Uneingeschränkter Zugang

Employing Divergent Machine Learning Classifiers to Upgrade the Preciseness of Image Retrieval Systems

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 75 - 85

Zusammenfassung

Abstract

Content Based Image Retrieval (CBIR) system is an efficient search engine which has the potentiality of retrieving the images from huge repositories by extracting the visual features. It includes color, texture and shape. Texture is the most eminent feature among all. This investigation focuses upon the classification complications that crop up in case of big datasets. In this, texture techniques are explored with machine learning algorithms in order to increase the retrieval efficiency. We have tested our system on three texture techniques using various classifiers which are Support vector machine, K-Nearest Neighbor (KNN), Naïve Bayes and Decision Tree (DT). Variant evaluation metrics precision, recall, false alarm rate, accuracy etc. are figured out to measure the competence of the designed CBIR system on two benchmark datasets, i.e. Wang and Brodatz. Result shows that with both these datasets the KNN and DT classifier hand over superior results as compared to others.

Schlüsselwörter

  • Support vector machines
  • K-Nearest Neighbour (KNN)
  • Decision tree
  • Naïve bayes
  • False alarm rate
Uneingeschränkter Zugang

Key Generation Using Generalized Pell’s Equation in Public Key Cryptography Based on the Prime Fake Modulus Principle to Image Encryption and Its Security Analysis

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 86 - 101

Zusammenfassung

Abstract

RSA is one among the most popular public key cryptographic algorithm for security systems. It is explored in the results that RSA is prone to factorization problem, since it is sharing common modulus and public key exponent. In this paper the concept of fake modulus and generalized Pell’s equation is used for enhancing the security of RSA. Using generalized Pell’s equation it is explored that public key exponent depends on several parameters, hence obtaining private key parameter itself is a big challenge. Fake modulus concept eliminates the distribution of common modulus, by replacing it with a prime integer, which will reduce the problem of factorization. It also emphasizes the algebraic cryptanalysis methods by exploring Fermat’s factorization, Wiener’s attack, and Trial and division attacks.

Schlüsselwörter

  • Public Key Cryptography
  • Fermat’s Factorization
  • Standard Deviation
  • Pell’s Equation
  • Wiener’s Attack
  • Trial and Division
Uneingeschränkter Zugang

Coverless VoIP Steganography Using Hash and Hash

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 102 - 115

Zusammenfassung

Abstract

Performing secure and robust embedding and extracting in real time voice streams without deteriorating the voice quality is a great challenge. This paper aims on hiding the secret data bits in the voice packets without modifying any data in the cover thereby improving the embedding transparency and becomes robust against the steganalysis attacks using coverless approach. Initially a hash array is built with the frame size. The cover bit position is identified from the hashing function. The hash array is marked with a flag value to indicate that the particular sample consist of the secret message bit. The hash array is attached with the VoIP samples, at the receiver side the hash table is separated, and the secret bits are extracted based on the hash array. The experimental results conducted on a VoIP prototype proved to be simpler and effective in terms of the computational complexity, undetectability and voice quality at both sender and receiver end.

Schlüsselwörter

  • Hash
  • VoIP
Uneingeschränkter Zugang

Towards a Multistep Method for Assessment in e-Learning of Emerging Technologies

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 116 - 129

Zusammenfassung

Abstract

In the Fourth Industrial Revolution some important leading technologies are identified as emerging technologies with unknown in advance potential risks. Emphasized is the need for new approaches and solutions for forming of increased information awareness, knowledge and competencies in the present and future generations to use the possibilities of Industry 4.0 for technological breakthroughs. A method for evaluation and prognosis of the knowledge, skills and competencies of the students in the virtual education space is proposed in the form of a five-step process. The method can be adapted to new technologies and applications. Research and analysis of the method are carried out in the academic course ‘Artificial Intelligence’ at the Burgas Free University with the application of the instruments of the Orange system for experimentation and inference.

Schlüsselwörter

  • Industry 4.0
  • Еmerging тechnologies
  • virtual education space
  • e-Learning
  • risks
  • artificial intelligence
  • machine learning
  • Orange system
Uneingeschränkter Zugang

Multiscale Transform and Shrinkage Thresholding Techniques for Medical Image Denoising – Performance Evaluation

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 130 - 146

Zusammenfassung

Abstract

Due to sparsity and multiresolution properties, Mutiscale transforms are gaining popularity in the field of medical image denoising. This paper empirically evaluates different Mutiscale transform approaches such as Wavelet, Bandelet, Ridgelet, Contourlet, and Curvelet for image denoising. The image to be denoised first undergoes decomposition and then the thresholding is applied to its coefficients. This paper also deals with basic shrinkage thresholding techniques such Visushrink, Sureshrink, Neighshrink, Bayeshrink, Normalshrink and Neighsureshrink to determine the best one for image denoising. Experimental results on several test images were taken on Magnetic Resonance Imaging (MRI), X-RAY and Computed Tomography (CT). Qualitative performance metrics like Peak Signal to Noise Ratio (PSNR), Weighted Signal to Noise Ratio (WSNR), Structural Similarity Index (SSIM), and Correlation Coefficient (CC) were computed. The results shows that Contourlet based Medical image denoising methods are achieving significant improvement in association with Neighsureshrink thresholding technique.

Schlüsselwörter

  • Medical Image Denoising
  • Multiscale Transforms
  • Shrinkage Thresholding
Uneingeschränkter Zugang

PS-PC: An Effective Method to Improve VoIP Technology Bandwidth Utilization over ITTP Protocol

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 147 - 158

Zusammenfassung

Abstract

Voice over IP (VoIP) wastes a valuable amount of bandwidth because of its large packet header size compared to its small packet payload. The main objective of this paper is to reduce the amount of this wasted bandwidth, by proposing a new packets coalescence method, called Payload Shrinking and Packets Coalesce (PS-PC). The proposed PS-PC method reduces the amount of the wasted bandwidth by i) coalesces a group of VoIP packets in one header instead of a separate header to each packet and ii) shrinks the VoIP packet payload to a smaller one based on a certain algorithm. The proposed PS-PC method is deployed at the sender side VoIP gateway that represents an exit point to a myriad number of simultaneous VoIP calls. The performance evaluation showed better bandwidth usage when deploying the proposed PS-PC method with ITTP protocol in comparison to the traditional ITTP protocol without the PS-PC method.

Schlüsselwörter

  • ITTP
  • VoIP Protocols
  • Packet Coalesce
  • Header Overhead
  • Bandwidth Utilization
Uneingeschränkter Zugang

A Novel Feature Descriptor for Face Anti-Spoofing Using Texture Based Method

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 159 - 176

Zusammenfassung

Abstract

In this paper we propose a novel approach for face anti-spoofing called Extended Division Directional Ternary Co-relation Pattern (EDDTCP). The EDDTCP encodes co-relation of ternary edges based on the centre pixel gray values with its immediate directional neighbour and its next immediate average directional neighbour, which is calculated by using the average of cornered neighbours with directional neighbours. The proposed method is robust against presentation attacks by extracting the spatial information in all directions. Three Experiments were performed by using all the four texture descriptors (LBP, LTP, LGS and EDDTCP) and the results are compared. The proposed face anti-spoofing method performs better than LBP, LTP and LGS.

Schlüsselwörter

  • Face Anti-spoofing
  • Extended Division Directional Ternary Co-relation Pattern (EDDCP)
  • Texture analysis
  • Replay-Attack
12 Artikel
Uneingeschränkter Zugang

CRUDyLeaf: A DSL for Generating Spring Boot REST APIs from Entity CRUD Operations

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 3 - 14

Zusammenfassung

Abstract

Domain-Specific Languages (DSLs) are programming languages designed specifically to express solutions to problems in a particular domain. It is said they foster productivity and quality. In this work we describe CRUDyLeaf, a DSL focused on the generation of Spring Boot REST APIs from entity CRUD operations. Spring Boot is an open source Java-based framework used to implement the REST architecture style. It has gained popularity among developers mainly because it allows to build stand-alone and production ready software applications (avoiding the use of an application server). Through seven proposed stages (domain immersion, golden application implementation, syntax definition, meta model generation, code generator implementation, deployment, and refinement) we describe the development of this DSL. We also exemplify and evaluate the proposed DSL. Our findings suggest a yield automation rate of 32.1 LOC (Lines Of Code) for each LOC written in this DSL, among other observed benefits.

Schlüsselwörter

  • CRUDyLeaf
  • DSL
  • Domain-Specific Language
  • Software Engineering
  • Spring Boot
Uneingeschränkter Zugang

Agile Elastic Desktop Corporate Architecture for Big Data

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 15 - 31

Zusammenfassung

Abstract

New challenges in the dynamically changing business environment require companies to experience digital transformation and more effective use of Big Data generated in their expanding online business activities. A possible solution for solving real business problems concerning Big Data resources is proposed in this paper. The defined Agile Elastic Desktop Corporate Architecture for Big Data is based on virtualizing the unused desktop resources and organizing them in order to serve the needs of Big Data processing, thus saving resources needed for additional infrastructure in an organization. The specific corporate business needs are analyzed within the developed R&D environment and, based on that, the unused desktop resources are customized and configured into required Big Data tools. The R&D environment of the proposed Agile Elastic Desktop Corporate Architecture for Big Data could be implemented on the available unused resources of hundreds desktops.

Schlüsselwörter

  • Agile Elastic Desktop Corporate Architecture
  • Desktop Virtualization
  • Big Data
  • Digital Transformation
Uneingeschränkter Zugang

Microservices Centric Architectural Model for Handling Data Stream Oriented Applications

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 32 - 44

Zusammenfassung

Abstract

The present-day software application systems are highly complex with many requirements and variations, which can only be handled by more than one architectural pattern. This paper focuses on a combinational architectural design, with the micro-services at the center and supported by the model view controller and the pipes and filter architectural patterns to realize any data stream-oriented application. The proposed model is very generic and for validation, a prototype GIS application has been considered. The application is designed to extract GIS data from internet sources and process the data using third party processing tools. The overall design follows the micro-services architecture and the processing segment is designed using pipes-and-filters architectural pattern. The user interaction is made possible with the use of the model view controller pattern. The versatility of the application is expressed in its ability to organize any number of given filters in a connected structure that agrees with inter-component dependencies. The model includes different services, which make the application more user-friendly and secure by prompting client for authentication and providing unique storage for every client. This approach is very much useful for building applications with a high degree of flexibility, maintainability and adaptability. A qualitative comparison is made using a set of criteria and their implementation using the different architectural styles.

Schlüsselwörter

  • Architectural Pattern
  • Microservices
  • Model View Controller
  • Pipes and Filters
  • Software Architecture
Uneingeschränkter Zugang

Cluster-Based Optimization of an Evacuation Process Using a Parallel Bi-Objective Real-Coded Genetic Algorithm

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 45 - 63

Zusammenfassung

Abstract

This work presents a novel approach to the design of a decision-making system for the cluster-based optimization of an evacuation process using a Parallel bi-objective Real-Coded Genetic Algorithm (P-RCGA). The algorithm is based on the dynamic interaction of distributed processes with individual characteristics that exchange the best potential decisions among themselves through a global population. Such an approach allows the HyperVolume performance metric (HV metric) as reflected in the quality of the subset of the Pareto optimal solutions to be improved. The results of P-RCGA were compared with other well-known multi-objective genetic algorithms (e.g., -MOEA, NSGA-II, SPEA2). Moreover, P-RCGA was aggregated with the developed simulation of the behavior of human agent-rescuers in emergency through the objective functions to optimize the main parameters of the evacuation process.

Schlüsselwörter

  • Cluster-based multi-objective optimization
  • human crowd behavior
  • real-coded genetic algorithms
  • multi-agent systems
  • fuzzy clustering
Uneingeschränkter Zugang

Activity Recognition on Subject Independent Using Machine Learning

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 64 - 74

Zusammenfassung

Abstract

Recent Activity Daily Living (ADL) not only tackles simple activities, but also caters to a wide range of complex activities. Although the same activity has been carried out under the same environmental conditions, the acceleration signal obtained from each subject considerably differs. This happens due to the pattern of action generated for each subject is diverse based on several aspects such as subject age, gender, emotion and personality. This project therefore compares the accuracy of various machine learning models for ADL classification. On top of that, this research work also scrutinizes the effectiveness of various feature selection methods to identify the most relevant attribute for ADL classification. As a result, Random Forest was able to achieve the highest accuracy of 83.3% on subject independent matter in ADL classification. Meanwhile, CFS Subset Evaluator is considered to be a good feature selector as it successfully selected the 8 most relevant features compared with Correlation and Information Gain Evaluator.

Schlüsselwörter

  • Activity Daily Living (ADL)
  • accelerometer
  • wearable sensor
  • machine learning
Uneingeschränkter Zugang

Employing Divergent Machine Learning Classifiers to Upgrade the Preciseness of Image Retrieval Systems

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 75 - 85

Zusammenfassung

Abstract

Content Based Image Retrieval (CBIR) system is an efficient search engine which has the potentiality of retrieving the images from huge repositories by extracting the visual features. It includes color, texture and shape. Texture is the most eminent feature among all. This investigation focuses upon the classification complications that crop up in case of big datasets. In this, texture techniques are explored with machine learning algorithms in order to increase the retrieval efficiency. We have tested our system on three texture techniques using various classifiers which are Support vector machine, K-Nearest Neighbor (KNN), Naïve Bayes and Decision Tree (DT). Variant evaluation metrics precision, recall, false alarm rate, accuracy etc. are figured out to measure the competence of the designed CBIR system on two benchmark datasets, i.e. Wang and Brodatz. Result shows that with both these datasets the KNN and DT classifier hand over superior results as compared to others.

Schlüsselwörter

  • Support vector machines
  • K-Nearest Neighbour (KNN)
  • Decision tree
  • Naïve bayes
  • False alarm rate
Uneingeschränkter Zugang

Key Generation Using Generalized Pell’s Equation in Public Key Cryptography Based on the Prime Fake Modulus Principle to Image Encryption and Its Security Analysis

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 86 - 101

Zusammenfassung

Abstract

RSA is one among the most popular public key cryptographic algorithm for security systems. It is explored in the results that RSA is prone to factorization problem, since it is sharing common modulus and public key exponent. In this paper the concept of fake modulus and generalized Pell’s equation is used for enhancing the security of RSA. Using generalized Pell’s equation it is explored that public key exponent depends on several parameters, hence obtaining private key parameter itself is a big challenge. Fake modulus concept eliminates the distribution of common modulus, by replacing it with a prime integer, which will reduce the problem of factorization. It also emphasizes the algebraic cryptanalysis methods by exploring Fermat’s factorization, Wiener’s attack, and Trial and division attacks.

Schlüsselwörter

  • Public Key Cryptography
  • Fermat’s Factorization
  • Standard Deviation
  • Pell’s Equation
  • Wiener’s Attack
  • Trial and Division
Uneingeschränkter Zugang

Coverless VoIP Steganography Using Hash and Hash

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 102 - 115

Zusammenfassung

Abstract

Performing secure and robust embedding and extracting in real time voice streams without deteriorating the voice quality is a great challenge. This paper aims on hiding the secret data bits in the voice packets without modifying any data in the cover thereby improving the embedding transparency and becomes robust against the steganalysis attacks using coverless approach. Initially a hash array is built with the frame size. The cover bit position is identified from the hashing function. The hash array is marked with a flag value to indicate that the particular sample consist of the secret message bit. The hash array is attached with the VoIP samples, at the receiver side the hash table is separated, and the secret bits are extracted based on the hash array. The experimental results conducted on a VoIP prototype proved to be simpler and effective in terms of the computational complexity, undetectability and voice quality at both sender and receiver end.

Schlüsselwörter

  • Hash
  • VoIP
Uneingeschränkter Zugang

Towards a Multistep Method for Assessment in e-Learning of Emerging Technologies

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 116 - 129

Zusammenfassung

Abstract

In the Fourth Industrial Revolution some important leading technologies are identified as emerging technologies with unknown in advance potential risks. Emphasized is the need for new approaches and solutions for forming of increased information awareness, knowledge and competencies in the present and future generations to use the possibilities of Industry 4.0 for technological breakthroughs. A method for evaluation and prognosis of the knowledge, skills and competencies of the students in the virtual education space is proposed in the form of a five-step process. The method can be adapted to new technologies and applications. Research and analysis of the method are carried out in the academic course ‘Artificial Intelligence’ at the Burgas Free University with the application of the instruments of the Orange system for experimentation and inference.

Schlüsselwörter

  • Industry 4.0
  • Еmerging тechnologies
  • virtual education space
  • e-Learning
  • risks
  • artificial intelligence
  • machine learning
  • Orange system
Uneingeschränkter Zugang

Multiscale Transform and Shrinkage Thresholding Techniques for Medical Image Denoising – Performance Evaluation

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 130 - 146

Zusammenfassung

Abstract

Due to sparsity and multiresolution properties, Mutiscale transforms are gaining popularity in the field of medical image denoising. This paper empirically evaluates different Mutiscale transform approaches such as Wavelet, Bandelet, Ridgelet, Contourlet, and Curvelet for image denoising. The image to be denoised first undergoes decomposition and then the thresholding is applied to its coefficients. This paper also deals with basic shrinkage thresholding techniques such Visushrink, Sureshrink, Neighshrink, Bayeshrink, Normalshrink and Neighsureshrink to determine the best one for image denoising. Experimental results on several test images were taken on Magnetic Resonance Imaging (MRI), X-RAY and Computed Tomography (CT). Qualitative performance metrics like Peak Signal to Noise Ratio (PSNR), Weighted Signal to Noise Ratio (WSNR), Structural Similarity Index (SSIM), and Correlation Coefficient (CC) were computed. The results shows that Contourlet based Medical image denoising methods are achieving significant improvement in association with Neighsureshrink thresholding technique.

Schlüsselwörter

  • Medical Image Denoising
  • Multiscale Transforms
  • Shrinkage Thresholding
Uneingeschränkter Zugang

PS-PC: An Effective Method to Improve VoIP Technology Bandwidth Utilization over ITTP Protocol

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 147 - 158

Zusammenfassung

Abstract

Voice over IP (VoIP) wastes a valuable amount of bandwidth because of its large packet header size compared to its small packet payload. The main objective of this paper is to reduce the amount of this wasted bandwidth, by proposing a new packets coalescence method, called Payload Shrinking and Packets Coalesce (PS-PC). The proposed PS-PC method reduces the amount of the wasted bandwidth by i) coalesces a group of VoIP packets in one header instead of a separate header to each packet and ii) shrinks the VoIP packet payload to a smaller one based on a certain algorithm. The proposed PS-PC method is deployed at the sender side VoIP gateway that represents an exit point to a myriad number of simultaneous VoIP calls. The performance evaluation showed better bandwidth usage when deploying the proposed PS-PC method with ITTP protocol in comparison to the traditional ITTP protocol without the PS-PC method.

Schlüsselwörter

  • ITTP
  • VoIP Protocols
  • Packet Coalesce
  • Header Overhead
  • Bandwidth Utilization
Uneingeschränkter Zugang

A Novel Feature Descriptor for Face Anti-Spoofing Using Texture Based Method

Online veröffentlicht: 13 Sep 2020
Seitenbereich: 159 - 176

Zusammenfassung

Abstract

In this paper we propose a novel approach for face anti-spoofing called Extended Division Directional Ternary Co-relation Pattern (EDDTCP). The EDDTCP encodes co-relation of ternary edges based on the centre pixel gray values with its immediate directional neighbour and its next immediate average directional neighbour, which is calculated by using the average of cornered neighbours with directional neighbours. The proposed method is robust against presentation attacks by extracting the spatial information in all directions. Three Experiments were performed by using all the four texture descriptors (LBP, LTP, LGS and EDDTCP) and the results are compared. The proposed face anti-spoofing method performs better than LBP, LTP and LGS.

Schlüsselwörter

  • Face Anti-spoofing
  • Extended Division Directional Ternary Co-relation Pattern (EDDCP)
  • Texture analysis
  • Replay-Attack

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