Yannis Xydas

(Thesis URL: http://users.teiath.gr/yxydas/Thesis_Yannis_Xydas.pdf). In this thesis we study the possibility of applying visualization and visual analytics in the context of data analysis for network security. In particular, we studied Internet web security and by using an “intelligent” visual representation of web attacks we extracted knowledge from a network operation graph. To achieve this goal we designed and developed an intelligent prototype system. This system is a surveillance aid for the security and web analyst, offering him/her a user friendly visual tool to detect anomalies in web requests by monitoring and exploring 3D graphs, to understand quickly the kind of undergoing attack by means of colours and the ability to navigate into the web request payload, of either normal or malicious traffic, for further analysis and appropriate response. The fundamental parts of such a system are Artificial Intelligence and Visualization. A hybrid expert system such as an Evolutionary ...

We present a numerical analysis of 50 Gbaud coherent detection enabled by injection locked lasers and line coding. The coherent receiver was tested with respect to an ideal receiver for two higher order modulation formats (16-QAM, QPSK) and under diverse operating regimes relating to the slave laser linewidth properties, the injection level and the frequency detuning between the incoming signal and the slave laser. The impact of the slave laser properties and line coding techniques on the receiver performance is highlighted showing that the technique could be used as a practical solution in order to enable low-cost and short reach n x 100 Gb/s Ethernet communication systems with the potential of flexible in terms of rate transmission.

Purpose The purpose of this paper is to introduce a novel framework for visual-aided ontology-based multidimensional ranking and to demonstrate a case study in the academic domain. Design/methodology/approach The paper presents a method for adapting semantic web technologies on multiple criteria decision-making algorithms to endow to them dynamic characteristics. It also showcases the enhancement of the decision-making process by visual analytics. Findings The semantic enhanced ranking method enables the reproducibility and transparency of ranking results, while the visual representation of this information further benefits decision makers into making well-informed and insightful deductions about the problem. Research limitations/implications This approach is suitable for application domains that are ranked on the basis of multiple criteria. Originality/value The discussed approach provides a dynamic ranking methodology, instead of focusing only on one application field, or one multiple criteria decision-making method. It proposes a framework that allows integration of multidimensional, domain-specific information and produces complex ranking results in both textual and visual form.

Purpose The purpose of this paper is to introduce a novel framework for visual-aided ontology-based multidimensional ranking and to demonstrate a case study in the academic domain. Design/methodology/approach The paper presents a method for adapting semantic web technologies on multiple criteria decision-making algorithms to endow to them dynamic characteristics. It also showcases the enhancement of the decision-making process by visual analytics. Findings The semantic enhanced ranking method enables the reproducibility and transparency of ranking results, while the visual representation of this information further benefits decision makers into making well-informed and insightful deductions about the problem. Research limitations/implications This approach is suitable for application domains that are ranked on the basis of multiple criteria. Originality/value The discussed approach provides a dynamic ranking methodology, instead of focusing only on one application field, or one multiple criteria decision-making method. It proposes a framework that allows integration of multidimensional, domain-specific information and produces complex ranking results in both textual and visual form.

Academia is a complex socio-technical system with multiple aspects and constituents that involve various stakeholders. In order to address stakeholders’ needs and to assist the institutional accountability, this complexity should be considered during the development of academic services. We have designed a dynamic multidimensional ranking approach, easily modifiable to address user requirements, so as to assess and compare the university performance with a clear view to the support of effective institutional strategic planning and policy making. Our approach comprises the following components: the AcademIS ontology to model the academic domain and its multiple dimensions, the AcademIS Information System to manage and display the academic information, published in Linked Open Data format and the visual-aided Multiple Criteria Decision Making component, to evaluate and rank the performance of the academic units. The data are aggregated from several sources, in different formats, LODif...

Intrusion Detection (ID) and Intrusion Prevention (IP) systems are an indispensable part of the information security infrastructure of every networking company or organization. Intrusion Detections Systems (IDS) have problems, such as false positives, operational issues in high-speed environments and the difficulty of detecting unknown threats. Intrusion Prevention Systems (IPS) are still in their infancy. There is a misconception in the market that intrusion detection and intrusion prevention are basically the same technology or that IDS systems are on the way out and IPS and firewalls are the wave of the future. In fact, IDS are far from becoming obsolete and both systems complement each other. Much of ID research has focused on improving the accuracy and operation of IDSs but surprisingly there has been very little research into supporting the security analysts’ intrusion detection tasks. In this paper we will describe an ongoing surveillance prototype system which offers a visua...

Existing graphical authentication methods take into account the fact that users are more capable of remembering pictures instead of text. Graphical authentication schemes are expected to be less vulnerable to specific hacker attack techniques that have greatly improved in recent years. The usability aspect of a graphical authentication product refers to the extent that a product can be used by users to achieve goals with effectiveness, efficiency and satisfaction in a specified context of use. This paper describes a prototype system providing graphical authentication of mobile devices over the Internet, covering both usability and security aspects. Color images are assigned to the mobile users and authentication is achieved by modifying the Red-Green-Blue (RGB) color intensity values of the assigned image.

Web sites are likely to be regularly scanned and attacked by both automated and manual means. Intrusion Detection Systems (IDS) assist security analysts by automatically identifying potential attacks from network activity and produce alerts describing the details of these intrusions. However, IDS have problems, such as false positives, operational issues in high-speed environments and the difficulty of detecting unknown threats. Much of ID research has focused on improving the accuracy and operation of IDSs but surprisingly there has been very little research into supporting the security analysts' intrusion detection tasks. Lately, security analysts face an increasing workload as their networks expand and attacks become more frequent. In this paper we describe an ongoing surveillance prototype system which offers a visual aid to the web and security analyst by monitoring and exploring 3D graphs. The system offers a visual surveillance of the network activity on a web server for ...

Due to the complicated nature of detecting actual intrusions, most current Network Intrusion Detection Systems (NIDS) place the burden of distinguishing an actual attack from a large set of false alarms on the security analyst, resulting in a significant cognitive load. Artificial Intelligence combined with Visualization will take advantage of human perceptual abilities and expertise to amplify cognition. In this paper we will describe an Evolutionary Artificial Neural Network (EANN) used as the knowledge base for the classification of web attacks in a prototype system. The aforementioned system is a surveillance aid for the security analyst, offering him a user friendly visual tool to detect anomalies in web requests by exploring 3D graphs, to understand quickly the kind of undergoing attack by means of colours and afford him the possibility to navigate into the payload of the web request for further analysis and adequate response. The EANN system is an improvement of our original ...

Academic units comprise multiple domains that influence their overall performance and synthesize their profile. In order to assist decision makers and examine the impact of the activities and the interactions of Higher Educational Institutions on the domains of which academia is consisted, multivariate rankings are utilized. Rankings can be used as a measure of the development of an academic unit in time and in relation to other academic units, as well as a guide for the strategic planning. Although, multifaceted information gives a clearer interpretation of the status of academic units and contributes to their development, it perplexes the decision making process by increasing its complexity. The paper describes a ranking methodology that considers the multidimensionality of academia, so as to offer a detailed comparison and assessment of educational institutions, but also alleviates the intricacy of multifaceted data by introducing semantic web technologies and visual analytics to...

Web sites are likely to be regularly scanned and attacked by both automated and manual means. Intrusion Detection Systems (IDS) assist security analysts by automatically identifying potential attacks from network activity and produce alerts describing the details of these intrusions. However, IDS have problems, such as false positives, operational issues in high-speed environments and the difficulty of detecting unknown threats. Much of ID research has focused on improving the accuracy and operation of IDSs but surprisingly there has been very little research into supporting the security analysts’ intrusion detection tasks. Lately, security analysts face an increasing workload as their networks expand and attacks become more frequent. In this paper we describe an ongoing surveillance prototype system which offers a visual aid to the web and security analyst by monitoring and exploring 3D graphs. The system offers a visual surveillance of the network activity on a web server for both normal and anomalous or malicious activity. Colours are used on the 3D graphics to indicate different categories of web attacks and the analyst has the ability to navigate into the web requests, of either normal or malicious traffic. Artificial Intelligence is combined with Visualization to detect and display unauthorized web traffic.

High Density WSN deployments applicable to large scale area extent is a venture of vital importance for a number of critical infrastructures. National borders monitoring, prediction and prevention of natural disasters and even crisis management issues comprise the wide application filed. Because of the critical role of the application and for expense reasons as well, the efficiency of the network should be assured. Emphasis has been given to connectivity and redundancy concerns, as they constitute the main contributory factor to a fully operational network. Therefore , topology, with respect to simulation issues, includes all the aforementioned terms. In this paper, we analyze the extended grid of cells topology with overlaps and its enhancement, with the aim to reduce cost and increase the response time of a monitoring network, which mainly acts as an early warning system. The proposed topology meets the specific problem requirements of large scale area coverage with high density sensor networks and provides a feasible and an efficient solution to it. This topology is applied in an expandable way, taking into consideration simulation results. The proposed network architecture combines the node signal attenuation with its localization for redundancy sake. The topology resembles the cellular phone network architecture, yet it is deployed according to WSN characteristics and limitations. It constitutes the fundamental theoretical topology approach upon which elevation and trees location will be taken into consideration in the forthcoming research. As a result, an appropriate WSN topology with increased efficiency and reduced cost per particular area is proposed. What is more, estimations and quantitative analysis regarding network devices and installation procedure are performed.

Existing graphical authentication methods take into account the fact that users are more capable of remembering pictures instead of text. Graphical authentication schemes are expected to be less vulnerable to specific hacker attack techniques that have greatly improved in recent years. The usability aspect of a graphical authentication product refers to the extent that a product can be used by users to achieve goals with effectiveness, efficiency and satisfaction in a specified context of use. This paper describes a prototype system providing graphical authentication of mobile devices over the Internet, covering both usability and security aspects. Color images are assigned to the mobile users and authentication is achieved by modifying the Red-Green-Blue (RGB) color intensity values of the assigned image.

Internet-based social networks are facilities (typically web sites) where people can form online communities, connect to each other and share information. This paper explores the area of applying visual analytics to represent data and underlying relationships in social networks-more specifically, on the Twitter micro-blogging service. Networks of this kind can be treated as graphs, where each node corresponds to a user or a specific piece of information and edges connect such nodes representing relationships. Visualizing graphs is a vast research area in its own right, with numerous applications in science and engineering. In this assignment we are using readily-available software to visualize parts of the network, via filtering or other operations, in order to be able to draw conclusions. Social networks are an excellent candidate to apply visual analytics to, due to their exponential growth when new users join.

Due to the complicated nature of detecting actual intrusions, most current Network Intrusion Detection Systems (NIDS) place the burden of distinguishing an actual attack from a large set of false alarms on the security analyst, resulting in a significant cognitive load. Artificial Intelligence combined with Visualization will take advantage of human perceptual abilities and expertise to amplify cognition. In this paper we will describe an Evolutionary Artificial Neural Network (EANN) used as the knowledge base for the classification of web attacks in a prototype system. The aforementioned system is a surveillance aid for the security analyst, offering him a user friendly visual tool to detect anomalies in web requests by exploring 3D graphs, to understand quickly the kind of undergoing attack by means of colours and afford him the possibility to navigate into the payload of the web request for further analysis and adequate response. The EANN system is an improvement of our original work that used a supervised multilayer Artificial Neural Network (ANN) as the web attacks classifier.

Once a web site has been made operational by a company, organisation or individual there is a wish to know the details regarding the connections to the site. In addition, there is a great interest to monitor the activity profile of the web site in terms of how many hits are received, where they come from, the relationship between this activity and increased revenues of the business and so on. Due to the complexity and volume of data involved in these tasks the only way to manage all of the information is to present it using a visual paradigm. Furthermore, web sites are likely to be regularly scanned and attacked by both automated and manual means. Companies, organisations and individuals are making every effort to build and maintain secure web sites. In this paper we will present an ongoing surveillance prototype system which offers a visual aid to the web analyst by monitoring and exploring 3D graphs. The system offers a visual surveillance of the web traffic for both normal and malicious activity. Web requests are presented as 3D directed graphs. Colours are used on the 3D graphics to indicate malicious attempts or anomalous traffic and the analyst has the ability to perform visual data analysis by navigating online into the web request payload, of either normal or malicious traffic.

In this thesis we study the possibility of applying visualization and visual analytics in the context of data analysis for network security. In particular, we studied Internet web security and by using an “intelligent” visual representation of web attacks we extracted knowledge from a network operation graph.
To achieve this goal we designed and developed an intelligent prototype system. This system is a surveillance aid for the security and web analyst, offering him/her a user friendly visual tool to detect anomalies in web requests by monitoring and exploring 3D graphs, to understand quickly the kind of undergoing attack by means of colours and the ability to navigate into the web request payload, of either normal or malicious traffic, for further analysis and appropriate response.
The fundamental parts of such a system are Artificial Intelligence and Visualization. A hybrid expert system such as an Evolutionary Artificial Neural Network proved to be ideal for the classification of the web attacks.

Keywords: Visualization, visual analytics, intelligent visualization, information security, surveillance aid, intrusion detection, web attacks, network security, web visualization, evolutionary neural networks, expert systems.