Volume 20 (2020): Issue 6 (December 2020) Special Issue on New Developments in Scalable Computing
Volume 20 (2020): Issue 5 (December 2020) Special issue on Innovations in Intelligent Systems and Applications
Volume 20 (2020): Issue 4 (November 2020)
Volume 20 (2020): Issue 3 (September 2020)
Volume 20 (2020): Issue 2 (June 2020)
Volume 20 (2020): Issue 1 (March 2020)
Volume 19 (2019): Issue 4 (November 2019)
Volume 19 (2019): Issue 3 (September 2019)
Volume 19 (2019): Issue 2 (June 2019)
Volume 19 (2019): Issue 1 (March 2019)
Volume 18 (2018): Issue 5 (May 2018) Special Thematic Issue on Optimal Codes and Related Topics
Volume 18 (2018): Issue 4 (November 2018)
Volume 18 (2018): Issue 3 (September 2018)
Volume 18 (2018): Issue 2 (June 2018)
Volume 18 (2018): Issue 1 (March 2018)
Volume 17 (2017): Issue 5 (December 2017) Special Issue With Selected Papers From The Workshop “Two Years Avitohol: Advanced High Performance Computing Applications 2017
Volume 17 (2017): Issue 4 (November 2017)
Volume 17 (2017): Issue 3 (September 2017)
Volume 17 (2017): Issue 2 (June 2017)
Volume 17 (2017): Issue 1 (March 2017)
Volume 16 (2016): Issue 6 (December 2016) Special issue with selection of extended papers from 6th International Conference on Logistic, Informatics and Service Science LISS’2016
Volume 16 (2016): Issue 5 (October 2016) Issue Title: Special Issue on Application of Advanced Computing and Simulation in Information Systems
Volume 16 (2016): Issue 4 (December 2016)
Volume 16 (2016): Issue 3 (September 2016)
Volume 16 (2016): Issue 2 (June 2016)
Volume 16 (2016): Issue 1 (March 2016)
Volume 15 (2015): Issue 7 (December 2015) Special Issue on Information Fusion
Volume 15 (2015): Issue 6 (December 2015) Special Issue on Logistics, Informatics and Service Science
Volume 15 (2015): Issue 5 (April 2015) Special Issue on Control in Transportation Systems
Volume 15 (2015): Issue 4 (November 2015)
Volume 15 (2015): Issue 3 (September 2015)
Volume 15 (2015): Issue 2 (June 2015)
Volume 15 (2015): Issue 1 (March 2015)
Volume 14 (2014): Issue 5 (December 2014) Special Issue
Volume 13 (2013): Issue 4 (December 2013) The publishing of the present issue (Volume 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.
The concept of virtualization has brought life to the new methods of software testing. With the help of cloud technology, testing has become much more popular because of the opportunities it provides. Cloud technologies provides everything as a service, hence the software testing is also provided as a service on cloud with the privileges of lower cost of testing, and relatively less effort. There are various cloud-based test tools focusing on different aspects of software testing such as load tests, regression tests, stress tests, performance tests, scalability tests, security tests, functional tests, browser performance tests, and latency tests. This paper investigates the cloud-based testing tools focusing on different aspects of software testing.
Feature selection technique has been a very active research topic that addresses the problem of reducing the dimensionality. Whereas, datasets are continuously growing over time both in samples and features number. As a result, handling both irrelevant and redundant features has become a real challenge. In this paper we propose a new straightforward framework which combines the horizontal and vertical distributed feature selection technique, called Horizo-Vertical Distributed Feature Selection approach (HVDFS), aimed at achieving good performances as well as reducing the number of features. The effectiveness of our approach is demonstrated on three well-known datasets compared to the centralized and the previous distributed approach, using four well-known classifiers.
In our work, we propose an ensemble of local and global filter-based feature selection method to reduce the high dimensionality of feature space and increase accuracy of spam review classification. These selected features are then used for training various classifiers for spam detection. Experimental results with four classifiers on two available datasets of hotel reviews show that the proposed feature selector improves the performance of spam classification in terms of well-known performance metrics such as AUC score.
Recent phishing campaigns are increasingly targeted to specific, small population of users and last for increasingly shorter life spans. There is thus an urgent need for developing defense mechanisms that do not rely on any forms of blacklisting or reputation: there is simply no time for detecting novel phishing campaigns and notify all interested organizations quickly enough. Such mechanisms should be close to browsers and based solely on the visual appearance of the rendered page. One of the major impediments to research in this area is the lack of systematic knowledge about how phishing pages actually look like. In this work we describe the technical challenges in collecting a large and diverse collection of screenshots of phishing pages and propose practical solutions. We also analyze systematically the visual similarity between phishing pages and pages of targeted organizations, from the point of view of a similarity metric that has been proposed as a foundation for visual phishing detection and from the point of view of a human operator.
Cryptographic protocols are the backbone of information security. Unfortunately the security of several important components of these protocols can be neglected. This causes violation of personal privacy and threats to democracy. Integration of biometrics with cryptography can overcome this problem. In this paper an enhanced session key agreement protocol which uses the data derived from iris signature is suggested to improve the security of biometric based applications like e-Passport, e-Driving license, etc. The authenticity and security properties of the proposed protocol are analyzed using ProVerif tool and demonstrate it satisfies the intended properties.
Address Resolution Protocol (ARP) cache poisoning results in numerous attacks. A novel mitigation system for ARP cache poisoning presented here avoids ARP cache poisoning attacks by introducing timestamps and counters in the ARP messages and ARP data tables. The system is evaluated based on criteria specified by the researchers and abnormal packets.
Published Online: 14 Dec 2018 Page range: 94 - 110
Abstract
Abstract
Modern web sites serve content that browsers fetch automatically from a number of different web servers that may be placed anywhere in the world. Such content is essential for defining the appearance and behavior of a web site and is thus a potential target for attacks. Many public administrations offer services on the web, thus we have entered a world in which web sites of public interest are continuously and systematically depending on web servers that may be located anywhere in the world and are potentially under control of other governments. In this work we focus on these issues by investigating the content included by almost 10000 web sites of the Italian Public Administration. We analyse the nature of such content, its quantity, its geographical location, the amount of dynamic variations over time. Our analyses demonstrate that the perimeter of trust of the Italian Public Administration collectively includes countries that are well beyond the control of the Italian government and provides several insights useful for implementing a centralized monitoring service aimed at detecting anomalies.
Published Online: 14 Dec 2018 Page range: 111 - 119
Abstract
Abstract
This research article discusses the problems having flexible demand, supply and cost in range referred as interval data based transportation problems and these cannot be solved directly using available methods. The uncertainty associated with these types of problems motivates authors to tackle it by converting interval to fuzzy numbers. This confront of conversion has been achieved by proposing a dichotomic fuzzification approach followed by a unique triangular incenter ranking approach to optimize interval data based transportation problems. A comparison with existing methods is made with the help of numerical illustrations. The algorithm proposed is found prompt in terms of the number of iteration involved and problem formation. This method is practical to handle the transportation problems not having a single valued data, but data in form of a range.
Published Online: 14 Dec 2018 Page range: 120 - 130
Abstract
Abstract
The residual vibrations in flexible structure system model can cause errors. In addition, the parameters in the system are also changed. For the problem of residual vibration, robust H∞ filter is designed for neutral systems with multi-delay. Based on Lyapunov stability theory, the sufficient condition for the existence of filter is given. For the permitted uncertainty and multi-delay, the designed filter can guarantee the robust asymptotically stability and satisfy H∞ performance index for the filtering error dynamic system. Finally, the designed filter is applied to the flexible system, and the result shows that the filter is effective.
The concept of virtualization has brought life to the new methods of software testing. With the help of cloud technology, testing has become much more popular because of the opportunities it provides. Cloud technologies provides everything as a service, hence the software testing is also provided as a service on cloud with the privileges of lower cost of testing, and relatively less effort. There are various cloud-based test tools focusing on different aspects of software testing such as load tests, regression tests, stress tests, performance tests, scalability tests, security tests, functional tests, browser performance tests, and latency tests. This paper investigates the cloud-based testing tools focusing on different aspects of software testing.
Feature selection technique has been a very active research topic that addresses the problem of reducing the dimensionality. Whereas, datasets are continuously growing over time both in samples and features number. As a result, handling both irrelevant and redundant features has become a real challenge. In this paper we propose a new straightforward framework which combines the horizontal and vertical distributed feature selection technique, called Horizo-Vertical Distributed Feature Selection approach (HVDFS), aimed at achieving good performances as well as reducing the number of features. The effectiveness of our approach is demonstrated on three well-known datasets compared to the centralized and the previous distributed approach, using four well-known classifiers.
In our work, we propose an ensemble of local and global filter-based feature selection method to reduce the high dimensionality of feature space and increase accuracy of spam review classification. These selected features are then used for training various classifiers for spam detection. Experimental results with four classifiers on two available datasets of hotel reviews show that the proposed feature selector improves the performance of spam classification in terms of well-known performance metrics such as AUC score.
Recent phishing campaigns are increasingly targeted to specific, small population of users and last for increasingly shorter life spans. There is thus an urgent need for developing defense mechanisms that do not rely on any forms of blacklisting or reputation: there is simply no time for detecting novel phishing campaigns and notify all interested organizations quickly enough. Such mechanisms should be close to browsers and based solely on the visual appearance of the rendered page. One of the major impediments to research in this area is the lack of systematic knowledge about how phishing pages actually look like. In this work we describe the technical challenges in collecting a large and diverse collection of screenshots of phishing pages and propose practical solutions. We also analyze systematically the visual similarity between phishing pages and pages of targeted organizations, from the point of view of a similarity metric that has been proposed as a foundation for visual phishing detection and from the point of view of a human operator.
Cryptographic protocols are the backbone of information security. Unfortunately the security of several important components of these protocols can be neglected. This causes violation of personal privacy and threats to democracy. Integration of biometrics with cryptography can overcome this problem. In this paper an enhanced session key agreement protocol which uses the data derived from iris signature is suggested to improve the security of biometric based applications like e-Passport, e-Driving license, etc. The authenticity and security properties of the proposed protocol are analyzed using ProVerif tool and demonstrate it satisfies the intended properties.
Address Resolution Protocol (ARP) cache poisoning results in numerous attacks. A novel mitigation system for ARP cache poisoning presented here avoids ARP cache poisoning attacks by introducing timestamps and counters in the ARP messages and ARP data tables. The system is evaluated based on criteria specified by the researchers and abnormal packets.
Modern web sites serve content that browsers fetch automatically from a number of different web servers that may be placed anywhere in the world. Such content is essential for defining the appearance and behavior of a web site and is thus a potential target for attacks. Many public administrations offer services on the web, thus we have entered a world in which web sites of public interest are continuously and systematically depending on web servers that may be located anywhere in the world and are potentially under control of other governments. In this work we focus on these issues by investigating the content included by almost 10000 web sites of the Italian Public Administration. We analyse the nature of such content, its quantity, its geographical location, the amount of dynamic variations over time. Our analyses demonstrate that the perimeter of trust of the Italian Public Administration collectively includes countries that are well beyond the control of the Italian government and provides several insights useful for implementing a centralized monitoring service aimed at detecting anomalies.
This research article discusses the problems having flexible demand, supply and cost in range referred as interval data based transportation problems and these cannot be solved directly using available methods. The uncertainty associated with these types of problems motivates authors to tackle it by converting interval to fuzzy numbers. This confront of conversion has been achieved by proposing a dichotomic fuzzification approach followed by a unique triangular incenter ranking approach to optimize interval data based transportation problems. A comparison with existing methods is made with the help of numerical illustrations. The algorithm proposed is found prompt in terms of the number of iteration involved and problem formation. This method is practical to handle the transportation problems not having a single valued data, but data in form of a range.
The residual vibrations in flexible structure system model can cause errors. In addition, the parameters in the system are also changed. For the problem of residual vibration, robust H∞ filter is designed for neutral systems with multi-delay. Based on Lyapunov stability theory, the sufficient condition for the existence of filter is given. For the permitted uncertainty and multi-delay, the designed filter can guarantee the robust asymptotically stability and satisfy H∞ performance index for the filtering error dynamic system. Finally, the designed filter is applied to the flexible system, and the result shows that the filter is effective.