Michalis Stefanidakis

Data integration in biological research: an overview

Data sharing, integration and annotation are essential to ensure the reproducibility of the analysis and interpretation of the experimental findings. Often these activities are perceived as a role that bioinformaticians and computer scientists have to take with no or little input from the experimental biologist. On the contrary, biological researchers, being the producers and often the end users of such data, have a big role in enabling biological data integration. The quality and usefulness of data integration depend on the existence and adoption of standards, shared formats, and mechanisms that are suitable for biological researchers to submit and annotate the data, so it can be easily searchable, conveniently linked and consequently used for further biological analysis and discovery. Here, we provide background on what is data integration from a computational science point of view, how it has been applied to biological research, which key aspects contributed to its success and future directions.

Secure and practical key establishment for distributed sensor networks

Key establishment in sensor networks is a challenging task, due to the physical constraints of sensor devices and their exposure to several threats. Existing protocols based on symmetric cryptography are very efficient but they are weak against several node impersonation and insider attacks. On the other hand, asymmetric protocols are resilient to such attacks but unfortunately, they are not feasible for sensor networks, even in their most efficient versions (e.g. the elliptic curve (EC) Diffie-Hellman family of key agreement protocols). In this paper, we present two pairwise key establishment protocols for sensor nodes in unattended distributed sensor networks (DSNs). The first protocol is hybrid and it combines asymmetric (elliptic curve (EC)) cryptography with symmetric key techniques. The second protocol is fully asymmetric. Furthermore, through simulations, we measure the efficiency of the proposed protocols in comparison with existing hybrid protocols. Our results show that under conditions, it is feasible for highly sensitive applications of static sensor networks to employ partial or fully asymmetric key establishment techniques and thus extend their security properties. Copyright

A spatial stochastic model for worm propagation: scale effects

Realistic models for worm propagation in the Internet have become one of the major topics in the academic literature concerning network security. In this paper, we propose an evolution equation for worm propagation in a very small number of Internet hosts, hereinafter called a subnet and introduce a generalization of the classical epidemic model by including a second order spatial term which models subnet interactions. The corresponding gradient coefficient is a measure of the characteristic scale of interactions and as a result a novel scale approach for understanding the evolution of worm population in different scales, is considered. Results concerning random scan strategies and local preference scan worms are presented. A comparison of the proposed model with simulation results is also presented. Based on our model, more efficient monitoring strategies could be deployed.

Adding Temporal Dimension to Ontologies via OWL Reification

It has been pointed out recently by many researchers that it is difficult for languages such as OWL to incorporate time in their relations. As a result it is difficult to reason about the temporal ordering of events or about the temporal properties of relations that vary as a function of time. There are a number of methods that have been proposed in order to circumvent this difficulty. One technique that can be used for this purpose is reification. The advantage of this approach is that it does not require the introduction of additional constructs to the OWL language. In this work we investigate the types of queries that are possible with this mechanism and we conclude that is in fact possible to express many interesting and useful queries. Moreover, due to the use of standard OWL, existing reasoning tools are capable of handling these queries.

Visualizing OPAC subject headings

Purpose – This paper aims at providing a robust, user‐friendly and efficient navigation procedure in an online library catalog that is based on semantic information encapsulated within subject headings.Design/methodology/approach – The paper describes an interactive navigation procedure inside an online library catalog based on semantic information. The proposed approach is presented through a web‐based, prototype application following the most recent trends of the semantic web such as AJAX technology and the web ontology language – OWL for encoding semantics.Findings – According to the proposed method, a GUI interface exposes the hierarchy of the subject headings employed within an OPAC, as well as all stated relations between such headings, as links that the user can follow, effectively traversing the ontology and formulating at the same time the actual query to the underlying OPAC. This act of interactive navigation through the librarys assets aids searchers in accurately formulating their queries, by...

Treating scalability and modelling human countermeasures against local preference worms via gradient models

A network worm is a specific type of malicious software that self propagates by exploiting application vulnerabilities in network-connected systems. Worm propagation models are mathematical models that attempt to capture the propagation dynamics of scanning worms as a means to understand their behaviour. It turns out that the emerged scalability in worm propagation plays an important role in order to describe the propagation in a realistic way. On the other hand human-based countermeasures also drastically affect the propagation in time and space. This work elaborates on a recent propagation model (Avlonitis et al. in J Comput Virol 3, 87–92, 2007) that makes use of Partial Differential Equations in order to treat correctly scalability and non-uniform behaviour (e.g., local preference worms). The aforementioned gradient model is extended in order to take into account human-based countermeasures that influence the propagation of local-preference worms in the Internet. Certain aspects of scalability emerged in random and local preference strategies are also discussed by means of random field considerations. As a result the size of a critical network that needs to be studied in order to describe the global propagation of a scanning worm is estimated. Finally, we present simulation results that validate the proposed analytical results and demonstrate the higher propagation rate of local preference worms compared with random scanning worms.

Visualizing Ontologies on the Web

The proposed paper introduces an ontology visualization model suitable for average web users. It is capable of retaining ontology expressiveness while at the same time hiding the formal terminology that is usually employed in the context of ontology development. According to the proposed ontology visualization model, classes are represented as boxes and their corresponding properties are represented as labeled lines connecting such boxes. By hoping from one box to another, users are able to interactively explore the underlying ontology. Such interaction is facilitated through an intuitive, web-based GUI implemented in Javascript, which communicates with the underlying ontology through a middleware component implemented in Python.

Top-K Shortest Paths in Large Typed RDF Datasets Challenge

Perhaps the most widely appreciated linked data principle instructs linked data providers to provide useful information using the standards (i.e., RDF and SPARQL). Such information corresponds to patterns expressed as SPARQL queries that are matched against the RDF graph. Until recently, patterns had to specify the exact path that would match against the underlying graph. The advent of the SPARQL 1.1 Recommendation introduced property paths as a new graph matching paradigm that allows the employment of Kleene star * (and its variant Kleene plus +) unary operators to build SPARQL queries that are agnostic of the underlying RDF graph structure. In this paper, we present the Top-k Shortest Paths in large typed RDF Datasets Challenge. It highlights the key aspects of property path queries that employ the Kleene star operator, presenting three widely different approaches.

Toward early warning against Internet worms based on critical-sized networks

In this paper, we build on a recent worm propagation stochastic model, in which random effects during worm spreading were modeled by means of a stochastic differential equation. On the basis of this model, we introduce the notion of the critical size of a network, which is the least size of a network that needs to be monitored, in order to correctly project the behavior of a worm in substantially larger networks. We provide a method for the theoretical estimation of the critical size of a network in respect to a worm with specific characteristics. Our motivation is the requirement in real systems to balance the needs for accuracy (i.e., monitoring a network of a sufficient size in order to reduce false alarms) and performance (i.e., monitoring a small-scale network to reduce complexity). In addition, we run simulation experiments in order to experimentally validate our arguments. Finally, based on notion of critical-sized networks, we propose a logical framework for a distributed early warning system against unknown and fast-spreading worms. In the proposed framework, propagation parameters of an early detected worm are estimated in real time by studying a critical-sized network. In this way, security is enhanced as estimations generated by a critical-sized network may help large-scale networks to respond faster to new worm threats. Copyright

Semantifying queries over large-scale Web search engines

In many situations, searching the web is synonymous to information seeking. Currently, web search engines are the most popular vehicle via which people get access to the web. Their popularity is partially due to the intrinsic way that people interact with them, i.e., by typing some keywords to the corresponding input box. Despite their popularity, search engines often fail to satisfy certain information needs, especially when the latter are haze and poorly articulated. In this paper, we focus on the occasions when large-scale web search engines find it difficult to cope with specific information-seeking behaviors and we accordingly introduce a query construction service that is targeted towards the solution of this problem. The proposed service leverages information coming from various DBpedia datasets and provides an intuitive GUI via which searchers determine the semantic orientation of their queries before these are addressed to the underlying search engine. The evaluation of the query construction service justifies the motive of this paper and indicates that it can considerably improve the searchers’ querying ability when search engines fail to provide adequate help.