Search

The paper presents a botnet detection approach for the distributed systems. It is based on the developed three level model, which includes botnet’s components: command and control center, control centers, basic elements of the botnet (bots). The novel framework provides the ability to detect known and unknown botnets, and consists of the host and the network levels. At the host level, the detection procedure is based on the implementation of the Bayes classification. The network level extends the results obtained at the host level to the rest of the local area network. Proposed approach provides the exchange of the results obtained by the Bayes classification for further use by other program units of the distributed system. The results of the developed classifier show that representation of the botnets’ samples for different classes and subclasses is sufficient for efficient botnet detection. Proposed technique demonstrates promising results concerning botnet detection in the distributed systems.

This article presents the technique for botnet detection using the distributed systems in the local area network. Distributed system contains host and network levels. At the host level, the botnets detection is based on Bayes classification. In order to perform the classification, the classes and subclasses were constructed on the basis of botnets patterns. An algorithm for classifier training was developed. The network level provides the exchange of the classification results for the knowledge transfer to the rest of the antivirus program units of the distributed system.

The paper proposes the architecture of a distributed malware detection system based on decentralized architecture in local area computer networks. Its feature is the synthesis of its requirements of distribution, decentralization, multilevel. This allows you to use it autonomously. In addition, the feature of the components of the system is the same organization, which allows the exchange of knowledge in the middle of the system, which, unlike the known systems, allows you to use the knowledge gained by separate parts of the system in other parts. The developed system allows to fill it with subsystems of detection of various types of malicious software in local area networks. The paper presents the results of experiments on the use of the developed system for the detection of metamorphic viruses.

The paper proposes the architecture of distributed multilevel detection system of malicious software in local area networks. Its feature is the synthesis of its requirements of distribution, decentralization, multilevel. This allows you to use it autonomously. In addition, the feature of autonomous program modules of the system is the same organization, which allows the exchange of knowledge in the middle of the system, which, unlike the known systems, allows you to use the knowledge gained by separate parts of the system in other parts. The developed system allows to fill it with subsystems of detection of various types of malicious software in local area networks.

The Ternopil Educational Communication Center was developed with NATO funding to improve computing for the universities of Ternopil, Ukraine. It provides high speed access for all of Ternopil’s universities to the Internet and the World Wide Web. It enables high speed communication within Ternopil, and between institutions in Ternopil using the UarNet and URAN networks. It provides an integration of on-line library services, and it supports such activities as video conferencing, distance education, and class to class participation. The universities of Ternopil and the University of Maine are developing programs and projects to involve students and faculty both in Ukraine and the US.

This paper describes the Smart Vehicle Screening System, which can be installed into a tollbooth for automated recognition of vehicle license plate information using a photograph of a vehicle. An automated system could then be implemented to control the payment of fees, parking areas, highways, bridges or tunnels, etc. There are considered an approach to identify vehicle through recognizing of it license plate using image fusion, neural networks and threshold techniques as well as some experimental results to recognize the license plate successfully.

This article gives some background information on the authors’ forthcoming book, The State of Learning. There are many challenges facing educators who want to bring education into the 21st century. At the same time, the explosion of technology has the potential to make education more available and influential than ever before. Education is taking place on a large stage and is not just confined to schools. We must rethink the foundations of education so it can truly benefit from new technology.

Authors suggested the development of a specialized network interface for network of detectors that are part of alarm system. Providing a high level of network security against intruder is achieved using a large number of security elements and their dynamic change in on-line mode network operation. The proposed system uses traditional detectors; each is connected to the network through node based on a microcontroller. This allows connection of traditional detectors into two-wired network with common bus type and to reduce the number of wired lines without loss of system informative channels. An additional advantage is in powering sensors by a server via informational network channel.

We describe the recent developments of an open-source project called RATCHET that can be used by groups of users to collectively construct attack trees. We present the RATCHET framework as well as a model for testing and evaluation of the produced attack trees. RATCHET has been tested in classroom settings with positive results and this paper presents the plans for expanding its outreach to the community at large and building attack trees through crowdsourcing. This paper gives an overview of RATCHET and an introduction to its use.