Enhancing Intrusion Detection Systems with a Hybrid Deep Learning Model and Optimized Feature Composition

Systems for detecting intrusions (IDS) are essential for protecting network infrastructures from hostile activity. Advanced methods are required since traditional IDS techniques frequently fail to properly identify sophisticated and developing assaults. In this article, we suggest a novel method for improving IDS performance through the use of a hybrid deep learning model and feature composition optimization. RNN and CNN has strengths that the proposed hybrid deep learning model leverages to efficiently capture both spatial and temporal correlations in network traffic data. The model can extract useful features from unprocessed network packets using CNNs and RNNs, giving a thorough picture of network behaviour. To increase the IDS's ability to discriminate, we also offer feature optimization strategies. We uncover the most pertinent and instructive features that support precise intrusion detection through a methodical feature selection and engineering process. In order to reduce the computational load and improve the model's efficiency without compromising detection accuracy, we also use dimensionality reduction approaches. We carried out extensive experiments using a benchmark dataset that is frequently utilized in intrusion detection research to assess the suggested approach. The outcomes show that the hybrid deep learning model performs better than conventional IDS methods, obtaining noticeably greater detection rates and lower false positive rates. The performance of model is further improved by the optimized feature composition, which offers a more accurate depiction of network traffic patterns

Algorithms for Image Analysis in Traffic Surveillance Systems

Import 23/07/2015The presence of various surveillance systems in many areas of the modern society is indisputable and the most perceptible are the video surveillance systems. This thesis mainly describes novel algorithm for vision-based estimation of the parking lot occupancy and the closely related topics of pre-processing of images captured under harsh conditions. The developed algorithms have their practical application in the parking guidance systems which are still more popular. One part of this work also tries to contribute to the specific area of computer graphics denoted as direct volume rendering (DVR).Přítomnost nejrůznějších dohledových systémů v mnoha oblastech soudobé společnosti je nesporná a systémy pro monitorování dopravy jsou těmi nejviditelnějšími. Hlavní část této práce se věnuje popisu nového algoritmu pro detekci obsazenosti parkovacích míst pomocí analýzy obrazu získaného z kamerového systému. Práce se také zabývá tématy úzce souvisejícími s předzpracováním obrazu získaného za ztížených podmínek. Vyvinuté algoritmy mají své praktické uplatnění zejména v oblasti pomocných parkovacích systémů, které se stávají čím dál tím více populárními. Jedna část této práce se snaží přispět do oblasti počítačové grafiky označované jako přímá vizualizace objemových dat.Prezenční460 - Katedra informatikyvyhově

Contributions of online social networks for e-learning

The emergence of Web 2.0 offers users the opportunity to not only see but also introduce new content and interact with the authors of original content and other users. The structure of the Web 2.0 offers an online space for groups of people with common interests to share experiences and information. Today, websites such as online social networks are extremely well known worldwide, with more users each day. The concept of Web 2.0 is based on these sites, encouraging the creation of collaborative environments of sharing among its users. Such concepts are extremely interesting when applied in an academic environment. The use of e-learning platforms have become widespread, however, such systems tend to be mostly mere repositories of content and are not stimulant systems for students. Concepts such as community, relationship and sharing, present in online social networks will be important in shaping the learning process of the student, making him an active element in this process by encouraging his critical spirit and his ability to solve problems

24th International Conference on Information Modelling and Knowledge Bases

In the last three decades information modelling and knowledge bases have become essentially important subjects not only in academic communities related to information systems and computer science but also in the business area where information technology is applied. The series of European – Japanese Conference on Information Modelling and Knowledge Bases (EJC) originally started as a co-operation initiative between Japan and Finland in 1982. The practical operations were then organised by professor Ohsuga in Japan and professors Hannu Kangassalo and Hannu Jaakkola in Finland (Nordic countries). Geographical scope has expanded to cover Europe and also other countries. Workshop characteristic - discussion, enough time for presentations and limited number of participants (50) / papers (30) - is typical for the conference. Suggested topics include, but are not limited to: 1. Conceptual modelling: Modelling and specification languages; Domain-specific conceptual modelling; Concepts, concept theories and ontologies; Conceptual modelling of large and heterogeneous systems; Conceptual modelling of spatial, temporal and biological data; Methods for developing, validating and communicating conceptual models. 2. Knowledge and information modelling and discovery: Knowledge discovery, knowledge representation and knowledge management; Advanced data mining and analysis methods; Conceptions of knowledge and information; Modelling information requirements; Intelligent information systems; Information recognition and information modelling. 3. Linguistic modelling: Models of HCI; Information delivery to users; Intelligent informal querying; Linguistic foundation of information and knowledge; Fuzzy linguistic models; Philosophical and linguistic foundations of conceptual models. 4. Cross-cultural communication and social computing: Cross-cultural support systems; Integration, evolution and migration of systems; Collaborative societies; Multicultural web-based software systems; Intercultural collaboration and support systems; Social computing, behavioral modeling and prediction. 5. Environmental modelling and engineering: Environmental information systems (architecture); Spatial, temporal and observational information systems; Large-scale environmental systems; Collaborative knowledge base systems; Agent concepts and conceptualisation; Hazard prediction, prevention and steering systems. 6. Multimedia data modelling and systems: Modelling multimedia information and knowledge; Contentbased multimedia data management; Content-based multimedia retrieval; Privacy and context enhancing technologies; Semantics and pragmatics of multimedia data; Metadata for multimedia information systems. Overall we received 56 submissions. After careful evaluation, 16 papers have been selected as long paper, 17 papers as short papers, 5 papers as position papers, and 3 papers for presentation of perspective challenges. We thank all colleagues for their support of this issue of the EJC conference, especially the program committee, the organising committee, and the programme coordination team. The long and the short papers presented in the conference are revised after the conference and published in the Series of “Frontiers in Artificial Intelligence” by IOS Press (Amsterdam). The books “Information Modelling and Knowledge Bases” are edited by the Editing Committee of the conference. We believe that the conference will be productive and fruitful in the advance of research and application of information modelling and knowledge bases. Bernhard Thalheim Hannu Jaakkola Yasushi Kiyok

Upowszechnianie wyników badań naukowych w międzynarodowych bazach danych : analiza biometryczna na przykładzie nauk technicznych, ze szczególnym uwzględnieniem elektrotechniki

The issues of bibliometrics, scientometrics, informetrics and webometrics have an important place among research subject undertaken by Polish and foreign scholars. Initially, these notions were used only by researchers in the fields of library science, scientometrics and information science. However, at the turn of the 20th and 21st centuries, quantitative methods became a fundamental tool for evaluation of, among others, sources of academic communication, academic research, research and academic centers. One of the elements of the evaluation is a quantitative analysis of academic publications in databases with international access. It is of particular importance in the case of technical sciences. This work is an attempt at a quantitative analysis of publications by Polish authors (affiliated to Polish technical universities) and Polish journals on electrotechnics in international databases. The contents are organized into four chapters with an introduction, conclusions, bibliography, name index and a list of figures and illustrations. Chapters one and two are devoted to theoretical issues, whereas chapters three and four – to practical issues. In the first chapter, selected issues concerning quantitative methods were presented, including an analysis of literature and a discussion over terminology carried out in book publications and journals. Moreover, selected examples of research conducted with the use of quantitative methods (including rankings and scientific reports) were discussed in this chapter). In chapter two, sources of information on academic publications, their origins and development (from bibliographic bases to citation indexes) were presented. A separate subchapter was devoted to databases of academic publications created by libraries of technical universities, and to indicators in the assessment of academic publications. Chapter three deals with electrotechnics as a field of science. An analysis was conducted with regard to the place of electrotechnics in science classifications based on selected examples, and the development of the teaching of electrotechnics at university level was shown. In this chapter, early and contemporary Polish journals on electrotechnics were presented, including journals published by technical universities themselves. Chapter four contains the results of an analysis of international databases (Scopus, WoS, CC), focusing on the representation of Polish journals, including their citations, and publications of authors with affiliation to Polish technical universities. Final conclusions of research and analyses have brought an answer to questions raised with regard to the assessment of representation in international databases of publications by Polish authors affiliated to Polish technical universities (in its various aspects, e.g., a publication type, language of publication, publication dynamics taking into account years of publications, cooperation with representatives of other European and non-European countries), and of Polish journals

The design and performance evaluation of a proactive multipath routing protocol for mobile ad hoc networks

Due to unpredictable network topology changes, routing in Mobile Ad Hoc Networks (MANET) is an important and challenging research area. The routing protocol should detect and maintain a good route(s) between source and destination nodes in these dynamic networks. Many routing protocols have been proposed for mobile ad hoc networks, and none can be considered as the best under all conditions. This thesis presents the design and implementation of a new proactive multipath MANET routing protocol. The protocol, named Multipath Destination Sequenced Distance Vector (MDSDV), is based on the well known single path Destination Sequenced Distance Vector (DSDV). We show that the protocol finds node-disjoint paths, i.e., paths which do not have any nodes in common, except for the source and the destination. The thesis presents a systematic evaluation of MDSDV in comparison with three well known protocols: one proactive (DSDV), and two reactive (AODV) and (DSR). MDSDV behaves very well in terms of its packet delivery fraction and data dropped in both static and dynamic networks. It delivers nearly 100% of data in dense networks (networks with more than 20 nodes). The speed of the nodes and the number of sources have a low impact on its performance