Pub Date : 2011-11-10DOI: 10.1109/IDAACS.2011.6072705
Vaclav Haasz
The aging VXI and physical limitations of PXI create a need for new bus standard for the highest performance test applications. AXIe, based on AdvancedTCA with extensions for instrumentation and test, leverage existing standards from PXI, LXI and IVI and provide more than enough power and space to accommodate the most demanding test instruments. AXIe promises high scalability and performance that will address a range of platforms including bench top measurements, modular systems and automated test equipment.
{"title":"AXIe — New standard for the highest performance test and measurement applications","authors":"Vaclav Haasz","doi":"10.1109/IDAACS.2011.6072705","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072705","url":null,"abstract":"The aging VXI and physical limitations of PXI create a need for new bus standard for the highest performance test applications. AXIe, based on AdvancedTCA with extensions for instrumentation and test, leverage existing standards from PXI, LXI and IVI and provide more than enough power and space to accommodate the most demanding test instruments. AXIe promises high scalability and performance that will address a range of platforms including bench top measurements, modular systems and automated test equipment.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134085800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-10DOI: 10.1109/IDAACS.2011.6072781
Pavel Kachurka, V. Golovko
Modern intrusion detection systems process large amounts of data. Most systems use signature- and rule-based approaches to find attack traces. The main disadvantage of such technologies is the need of continuous updating of signature database to let the system detect newest attacks. We present recirculation neural network based approach which lets to detect previously unseen attack types in real-time mode and to further correct recognition of this types. The experiments held on both KDD data and real network traffic data prove that this approach can be used in host-based anomaly and misuse detectors.
{"title":"Neural network approach to real-time network intrusion detection and recognition","authors":"Pavel Kachurka, V. Golovko","doi":"10.1109/IDAACS.2011.6072781","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072781","url":null,"abstract":"Modern intrusion detection systems process large amounts of data. Most systems use signature- and rule-based approaches to find attack traces. The main disadvantage of such technologies is the need of continuous updating of signature database to let the system detect newest attacks. We present recirculation neural network based approach which lets to detect previously unseen attack types in real-time mode and to further correct recognition of this types. The experiments held on both KDD data and real network traffic data prove that this approach can be used in host-based anomaly and misuse detectors.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116920495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-10DOI: 10.1109/IDAACS.2011.6072875
M. Drozd, M. Barabas, M. Grégr, P. Chmelar
In this abstract, we investigate the network traffic that may cause the unauthorized control of a computer in the campus network using buffer overflow attacks, the objective of which is to gain the control of privileged programs and computers. We provide statistics of the network traffic in a campus and an eterprise network together with probabilities of a buffer overflow attack to provide attakers the most vulnerable services using low interaction honeypot HoneyD together with a highly interactive shadow honeypot Argos that were used to detect attacks and describe their detection profiles. In this manner, we can collect data to be used for training classifiers to predict and detect even zero day vulnerabilities and malware. Our intension is to acquaint dataset that can identify serious security threats in much higher details, compared to 1999 KDD Cup dataset.
{"title":"Buffer overflow attacks data acquisition","authors":"M. Drozd, M. Barabas, M. Grégr, P. Chmelar","doi":"10.1109/IDAACS.2011.6072875","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072875","url":null,"abstract":"In this abstract, we investigate the network traffic that may cause the unauthorized control of a computer in the campus network using buffer overflow attacks, the objective of which is to gain the control of privileged programs and computers. We provide statistics of the network traffic in a campus and an eterprise network together with probabilities of a buffer overflow attack to provide attakers the most vulnerable services using low interaction honeypot HoneyD together with a highly interactive shadow honeypot Argos that were used to detect attacks and describe their detection profiles. In this manner, we can collect data to be used for training classifiers to predict and detect even zero day vulnerabilities and malware. Our intension is to acquaint dataset that can identify serious security threats in much higher details, compared to 1999 KDD Cup dataset.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116896729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-10DOI: 10.1109/IDAACS.2011.6072865
V. Golovko, Sergei V. Bezobrazov, Vasilii Melianchuk, M. Komar
In this paper we present the basic principles of the evolution of detectors in intelligent malware detection system. This system based on integration of both AI methods: artificial neural networks and artificial immune systems. The goal of the evolution is adaptation of detectors to new, unknown malicious code for increasing of quality of detection.
{"title":"Evolution of immune detectors in intelligent security system for malware detection","authors":"V. Golovko, Sergei V. Bezobrazov, Vasilii Melianchuk, M. Komar","doi":"10.1109/IDAACS.2011.6072865","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072865","url":null,"abstract":"In this paper we present the basic principles of the evolution of detectors in intelligent malware detection system. This system based on integration of both AI methods: artificial neural networks and artificial immune systems. The goal of the evolution is adaptation of detectors to new, unknown malicious code for increasing of quality of detection.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124663754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-10DOI: 10.1109/IDAACS.2011.6072874
Sergiy Lysenko, O. Savenko
New technique for computer system Trojan diagnosis in monitor mode which uses fuzzy logic and allows improving reliability and efficiency is developed.
提出了一种基于模糊逻辑的监控模式下计算机系统木马诊断新技术，提高了系统的可靠性和效率。
{"title":"The technique for computer systems Trojan diagnosis in the monitor mode","authors":"Sergiy Lysenko, O. Savenko","doi":"10.1109/IDAACS.2011.6072874","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072874","url":null,"abstract":"New technique for computer system Trojan diagnosis in monitor mode which uses fuzzy logic and allows improving reliability and efficiency is developed.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124945493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-10DOI: 10.1109/IDAACS.2011.6072717
M. Budnyk, Volodymyr Sosnytskyi, I. Voitovych, V. Maiko, Y. Minov, P. Sutkovyi, Oleksandr Zakorchenyi, T. Ryzhenko, V. Budnyk
Detail description of hardware and software of novel Ukrainian generation of magnetocardiographic apparatus — cardiomagnetic scanner CARDIOMAGSCAN have been presented. This cheaper supersensitive device includes 4 signal SQUID-channels, electrocardiograph, and automatic electromechanical system for patient scanning. Scanner is enabled to perform observation of the human heart during 15 minutes at unshielded environment. Device is intended to non-invasive medical diagnostics of cardiology diseases with help of advanced software including early stages, difficult-to-diagnose cases, and asymptomatic forms.
{"title":"Development of 4-channel cardiomagnetic scaner and technical requirements for 9-channel scaner to diagnose the heart abnormalities","authors":"M. Budnyk, Volodymyr Sosnytskyi, I. Voitovych, V. Maiko, Y. Minov, P. Sutkovyi, Oleksandr Zakorchenyi, T. Ryzhenko, V. Budnyk","doi":"10.1109/IDAACS.2011.6072717","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072717","url":null,"abstract":"Detail description of hardware and software of novel Ukrainian generation of magnetocardiographic apparatus — cardiomagnetic scanner CARDIOMAGSCAN have been presented. This cheaper supersensitive device includes 4 signal SQUID-channels, electrocardiograph, and automatic electromechanical system for patient scanning. Scanner is enabled to perform observation of the human heart during 15 minutes at unshielded environment. Device is intended to non-invasive medical diagnostics of cardiology diseases with help of advanced software including early stages, difficult-to-diagnose cases, and asymptomatic forms.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125178661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-10DOI: 10.1109/IDAACS.2011.6072883
Eileen Kuehn, J. Reinhardt, Stephan Bergemann, J. Sieck
This paper presents two different approaches to visualise information from culture and creative industries by using RFID based tracking and identification as well as Wi-Fi for the communication between the different components. Besides the required RFID backend, the paper also introduces a multi media information system built on top of the backend. The first approach is based on passive RFID whereas the second uses active RFID. In particular, the differences in the processing of system events, delivery of needed information and the implemented infrastructure will be discussed and evaluated.
{"title":"Multimedia and wireless communication in culture and creative industries","authors":"Eileen Kuehn, J. Reinhardt, Stephan Bergemann, J. Sieck","doi":"10.1109/IDAACS.2011.6072883","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072883","url":null,"abstract":"This paper presents two different approaches to visualise information from culture and creative industries by using RFID based tracking and identification as well as Wi-Fi for the communication between the different components. Besides the required RFID backend, the paper also introduces a multi media information system built on top of the backend. The first approach is based on passive RFID whereas the second uses active RFID. In particular, the differences in the processing of system events, delivery of needed information and the implemented infrastructure will be discussed and evaluated.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129373026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-10DOI: 10.1109/IDAACS.2011.6072916
O. Pomorova, T. Hovorushchenko
This paper represents the artificial neural network's method of design results evaluation and software quality characteristics prediction (NMEP) and the analysis of results of realized artificial neural network (ANN) training and functioning.
{"title":"Research of artificial neural network's component of software quality evaluation and prediction method","authors":"O. Pomorova, T. Hovorushchenko","doi":"10.1109/IDAACS.2011.6072916","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072916","url":null,"abstract":"This paper represents the artificial neural network's method of design results evaluation and software quality characteristics prediction (NMEP) and the analysis of results of realized artificial neural network (ANN) training and functioning.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129348025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-10DOI: 10.1109/IDAACS.2011.6072870
G. Markowsky
At the 2009 IEEE International Conference on Technologies for Homeland Security the author presented a paper entitled “Comparing Apples to Oranges” which showed the fundamental problem of ranking assets on multiple-factors. In particular, the talk showed that programs like Carver2 cannot consistently order targets. In particular, the author contends that using a spreadsheet such as Excel™ permits users to do as good a job of assessing targets as more dedicated systems. To improve the usefulness of Excel™ for target selection, the author has written a module that permits the spreadsheet to identify Condorcet cycles so that users will get a more realistic understanding of the vulnerability of their various assets. This paper describes the theoretical basis for this module and illustrates its operation. This module is available from the author.
{"title":"Universal asset assessment system based on excel™","authors":"G. Markowsky","doi":"10.1109/IDAACS.2011.6072870","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072870","url":null,"abstract":"At the 2009 IEEE International Conference on Technologies for Homeland Security the author presented a paper entitled “Comparing Apples to Oranges” which showed the fundamental problem of ranking assets on multiple-factors. In particular, the talk showed that programs like Carver2 cannot consistently order targets. In particular, the author contends that using a spreadsheet such as Excel™ permits users to do as good a job of assessing targets as more dedicated systems. To improve the usefulness of Excel™ for target selection, the author has written a module that permits the spreadsheet to identify Condorcet cycles so that users will get a more realistic understanding of the vulnerability of their various assets. This paper describes the theoretical basis for this module and illustrates its operation. This module is available from the author.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130699741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-10DOI: 10.1109/IDAACS.2011.6072780
I. Turchenko, V. Kochan
A method of individual conversion characteristic identification of multisensor using reduced number of its calibration/testing results is described in this paper. The proposed method is based on the neural-based reconstruction (approximation or prediction) of surface points of multisensor conversion characteristic. Each neural network module reconstructs separate point of the surface. Our results show that the use of a Support Vector Machine (SVM) model allows improving the reconstruction accuracy of multisensor conversion characteristic. The reconstruction results obtained by SVM are compared with the results obtained by a multi-layer perceptron (MLP).
{"title":"Improvement of identification accuracy of multisensor conversion characteristic using SVM","authors":"I. Turchenko, V. Kochan","doi":"10.1109/IDAACS.2011.6072780","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072780","url":null,"abstract":"A method of individual conversion characteristic identification of multisensor using reduced number of its calibration/testing results is described in this paper. The proposed method is based on the neural-based reconstruction (approximation or prediction) of surface points of multisensor conversion characteristic. Each neural network module reconstructs separate point of the surface. Our results show that the use of a Support Vector Machine (SVM) model allows improving the reconstruction accuracy of multisensor conversion characteristic. The reconstruction results obtained by SVM are compared with the results obtained by a multi-layer perceptron (MLP).","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127974803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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