Visible to the public International Conferences: CYBCONF 2015, Poland

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The 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) was held 24-26 June 2015 in Gdynia, Poland. The conference had several main tracks and special sessions, including Control Systems and Robotics, Artificial Intelligence, Knowledge-Based Systems, Machine Learning, Machine Vision, Computational Intelligence, Swarm Intelligence, Cognitive Systems, Neural Networks, Medical and Health Informatics, and Smart Applications.  

Sparrow, R.D.; Adekunle, A.A.; Berry, R.J.; Farnish, R.J., “Balancing Throughput and Latency for an Aerial Robot over a Wireless Secure Communication Link,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 184-189, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175929
Abstract: With the requirement for remote control of unmanned aerial vehicles (UAV) becoming more frequent in scenarios where the environment is inaccessible or hazardous to human beings (e.g. disaster recovery); remote functionality of a UAV is generally implemented over wireless networked control systems (WNCS). The nature of the wireless broadcast allows attackers to exploit security vulnerabilities through passive and active attacks; consequently, cryptography is often selected as a countermeasure to the aforementioned attacks. This paper analyses simulation undertaken and proposes a model to balance the relationship between throughput and latency for a secure multi-hop communication link. Results obtained indicate that throughput is more influential up to two hops from the initial transmitting device; conversely, latency is the determining factor after two hops.
Keywords: autonomous aerial vehicles; control engineering computing; cryptography; mobile communication; networked control systems; UAV; WNCS; active attacks; aerial robot; latency balancing; passive attacks; remote control; remote functionality; secure multihop communication link; security vulnerabilities; throughput balancing; unmanned aerial vehicles; wireless broadcast; wireless networked control systems; wireless secure communication link; Communication system security; Correlation; Mathematical model; Predictive models; Security; Throughput; Wireless communication; Latency; Security; Throughput; Unmanned Aerial Vehicles; Wireless (ID#: 15-6457)


Abraham, S.; Nair, S., “Exploitability Analysis Using Predictive Cybersecurity Framework,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 317-323, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175953
Abstract: Managing Security is a complex process and existing research in the field of cybersecurity metrics provide limited insight into understanding the impact attacks have on the overall security goals of an enterprise. We need a new generation of metrics that can enable enterprises to react even faster in order to properly protect mission-critical systems in the midst of both undiscovered and disclosed vulnerabilities. In this paper, we propose a practical and predictive security model for exploitability analysis in a networking environment using stochastic modeling. Our model is built upon the trusted CVSS Exploitability framework and we analyze how the atomic attributes namely Access Complexity, Access Vector and Authentication that make up the exploitability score evolve over a specific time period. We formally define a nonhomogeneous Markov model which incorporates time dependent covariates, namely the vulnerability age and the vulnerability discovery rate. The daily transition-probability matrices in our study are estimated using a combination of Frei's model & Alhazmi Malaiya's Logistic model. An exploitability analysis is conducted to show the feasibility and effectiveness of our proposed approach. Our approach enables enterprises to apply analytics using a predictive cyber security model to improve decision making and reduce risk.
Keywords: Markov processes; authorisation; decision making; risk management; access complexity; access vector; authentication; daily transition-probability matrices; decision making; exploitability analysis; nonhomogeneous Markov model; predictive cybersecurity framework; risk reduction; trusted CVSS exploitability framework; vulnerability age; vulnerability discovery rate; Analytical models; Computer security; Markov processes; Measurement; Predictive models; Attack Graph; CVSS; Markov Model; Security Metrics; Vulnerability Discovery Model; Vulnerability Lifecyle Model (ID#: 15-6458)


Szpyrka, M.; Szczur, A.; Bazan, J.G.; Dydo, L., “Extracting of Temporal Patterns from Data for Hierarchical Classifiers Construction," in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 330-335, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175955
Abstract: A method of automatic extracting of temporal patterns from learning data for constructing hierarchical behavioral patterns based classifiers is considered in the paper. The presented approach can be used to complete the knowledge provided by experts or to discover the knowledge automatically if no expert knowledge is accessible. Formal description of temporal patterns is provided and an algorithm for automatic patterns extraction and evaluation is described. A system for packet-based network traffic anomaly detection is used to illustrate the considered ideas.
Keywords: computer network security; data mining; learning (artificial intelligence); pattern classification; temporal logic; automatic pattern extraction; data temporal pattern extraction; hierarchical behavioral pattern; hierarchical classifier construction; knowledge discovery; learning data; packet-based network traffic anomaly detection; Clustering algorithms; Data mining; Decision trees; Entropy; Petri nets; Ports (Computers); Servers; LTL logic; feature extraction; hierarchical classifiers; network anomaly detection; temporal patterns (ID#: 15-6459)


Hermanowski, D., “Open Source Security Information Management System Supporting IT Security Audit,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 336-341, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175956
Abstract: Nowadays, assuring security of computer systems becomes difficult due to the rapid development of IT technologies, even in household appliances. This article shows exemplary model of the IT security monitoring and management system. Proposed solution is aimed to collect security events, analyse them, assess the risk they bring and inform the administrator about them in order to take appropriate decision to mitigate potential security incident. This system is based on open source code toolset. This toolset was studied, tested and examined in the context of the whole system. These tools were configured and an additional code was developed in order to achieve synergy effect from adopting various techniques aimed at network monitoring and system security.
Keywords: auditing; information management; public domain software; security of data; IT security audit; IT security management system; IT security monitoring; IT technologies; computer systems; household appliances; network monitoring; open source code toolset; open source security information management system; security events; security incident; synergy effect; system security; Correlation; Databases; Malware; Monitoring; Ports (Computers); Servers; IT audit; OSSIM; SIEM; computer security; monitoring; open source (ID#: 15-6460)


Goswami, S.; Chakrabarti, A.; Chakraborty, B., “Analysis of Correlation Structure of Data Set for Efficient Pattern Classification,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 24-29, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175901
Abstract: Pattern classification or clustering plays important role in a wide variety of applications in different areas like psychology and other social sciences, biology and medical sciences, pattern recognition and data mining. A lot of algorithms for supervised or unsupervised classification have been developed so far in order to achieve high classification accuracy with lower computational cost. However, some methods or algorithms work well for some of the data sets and perform poorly on others. For any particular data set, it is difficult to find out the most suitable algorithm without some random trial and error process. It seems that the characteristics of the data set might have some influence on the algorithm for classification. In this work, the data set characteristics is studied in terms of intra attribute relationship and a measure MVS (multivariate score) has been proposed to quantify and group different data sets on the basis of the correlation structure into strong independent, weak independent, weak correlated and strong correlated data set. The performance of different feature selection algorithms on different groups of data are studied by simulation experiments with 63 publicly available bench mark data sets. It has been verified that univariate methods lead to significant performance gain for strong independent data set compared to multivariate methods while multivariate methods have better performance for strong correlated data sets.
Keywords: data analysis; feature selection; pattern classification; pattern clustering; MVS; correlation structure analysis; data set characteristics; feature selection algorithms; intra attribute relationship; multivariate methods; multivariate score; pattern classification; pattern clustering; strong correlated data set; strong independent data set; univariate methods; weak correlated data set; weak independent data set; Accuracy; Classification algorithms; Clustering algorithms; Correlation; Data models; Histograms; Iris; Pattern classification algorithm; correlation structure. (ID#: 15-6461)


Qiangfu Zhao, “Aware System, Aware Unit and Aware Logic,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 42-47, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175904
Abstract: In recent years, various aware systems have been developed in the context of ubiquitous computing to improve the quality of services (QoS). The ultimate goal of awareness computing (AC) is to establish a win-win relation between producers and consumers. On the other hand, the main purpose of computational awareness (CA) is to understand the mechanism of awareness in human or animal brains, so that awareness, consciousness, and even intelligence can be realized step-by-step in computing machines. In this paper, we first provide a formal definition of aware systems, and then consider a way to build interpretable aware systems based on 3-valued logic. Some primary experiments show that it is possible to realize interpretable aware systems via discretizing multilayer feedforward neural network.
Keywords: formal logic; multilayer perceptrons; quality of service; ubiquitous computing; 3-valued logic; QoS; animal brain; aware logic; aware unit; awareness computing; computational awareness; computing machine; formal definition; human brain; interpretable aware system; multilayer feedforward neural network; quality of services; ubiquitous computing; win-win relation; Context; Context modeling; Gold; Inductors; Neurons; Sensors; Training; Computational awareness; aware logic; aware system; (ID#: 15-6462)


Tzung-Pei Hong; Ling-I Huang; Wen-Yang Lin; Yu-Yang Liu; Chakraborty, G., “Dynamic Migration in Multiple Ant Colonies,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, pp. 146-150, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175922
Abstract: Multi-population-based bio-inspired computation may use migration among groups to increase the search diversity. Through good solutions exchanged among sub-populations, better solutions may be found with a high probability. In this paper, we propose two algorithms to dynamically adjust the two primary parameters, migration interval and migration rate, for flexibly reflect solution situation for effective migration. The first algorithm only dynamically changes the migration interval, and the second considers both interval and rate. We will examine how the dynamic migration strategies affect the quality of solutions in the experiments.
Keywords: ant colony optimisation; search problems; dynamic migration strategies; migration interval; migration rate; multiple ant colonies; multipopulation-based bioinspired computation; search diversity; solution situation; Ant colony optimization; Computer science; Genetic algorithms; Heuristic algorithms; Particle swarm optimization; Sociology; Statistics; Ant Colony System; Bio-Inspired Computation; Dynamic Migration; Multiple Population (ID#: 15-6463)


Anh Duc Dang; Horn, J., “Formation Control of Autonomous Robots Following Desired Formation During Tracking a Moving Target,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 160-165, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175925
Abstract: In this paper, we propose a novel method for control the formation of the autonomous robots following to the desired formations during tracking a moving target under the influence of the dynamic environment. The V-shape formation is used to track a moving target when the distance from this formation to the target is longer than the target approaching radius. Furthermore, when the leader moves in the target approaching range, the circling shape formation is used to encircle the target. The motion of the robots to the optimal positions in the desired formations are controlled by the artificial force fields, which consist of local and global potential fields around the virtual nodes in the desired formations. Using the global attractive force field around the target, the formation of robots is always driven towards the target position. Moreover, using the repulsive/rotational vector fields in the obstacle avoiding controller, robots can easily escape the obstacle without collisions. The success of the proposed method is verified in simulations.
Keywords: collision avoidance; mobile robots; motion control; multi-robot systems; optimal control; target tracking; V-shape formation; artificial force fields; autonomous robots; circling shape formation; dynamic environment; formation control; global attractive force field; global potential fields; local potential fields;moving target tracking; obstacle avoiding controller; optimal positions; repulsive vector fields; robots motion; rotational vector fields; swarm intelligence; virtual nodes; Collision avoidance; Dynamics; Force; Robot kinematics; Target tracking; Formation control; artificial vector fields; collision avoidance; swarm intelligence (ID#: 15-6464)


Kempa, W.M., “Study on Time-Dependent Departure Process in a Finite-Buffer Queueing Model with BMAP-Type Input Stream,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 245-250, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175940
Abstract: Transient departure process of outgoing packets in a finite-buffer queueing model with the BMAP-type input stream and generally distributed processing times is investigated. Applying the paradigm of embedded Markov chain and the total probability law, a system of integral equations for the distribution function of the number of packets successfully processed up to fixed time t; conditioned by the initial level of buffer saturation and the state of the underlying Markov chain, is obtained. The solution of the corresponding system written for the mixed double transforms is found in a compact form by utilizing the approach based on linear and matrix algebra. Remarks on numerical treatment of analytical results and computational example are attached as well.
Keywords: Markov processes; matrix algebra; probability; queueing theory; BMAP-type input stream; buffer saturation; distributed processing times; distribution function; embedded Markov chain; finite-buffer queueing model; linear algebra; matrix algebra; time-dependent departure process; total probability law; Integral equations; Markov processes; Mathematical model; Matrices; Probability distribution; Transforms; Transient analysis; BMAP-type arrival stream; departure process; finite buffer; queueing system; transient analysis (ID#: 15-6465)


Hadorn, B.; Courant, M.; Hirsbrunner, B., “Holistic Integration of Enactive Entities into Cyber Physical Systems,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 281-286, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175947
Abstract: Cyber physical systems (CPSs) are built of physical components that are integrated into the cyber (virtual) world of computing. Whereas there are many open questions and challenges, such as time modeling, interaction between cyber and physical components, our research focuses on how humans can be holistically integrated. Our vision is to link human intelligence with CPS in order to get a smart partner for daily human activities. This will bring new system characteristics enabling to cope with self-awareness, cognition and creativity as well as the co-evolution of human-machine-symbiosis. In this sense, we state that drawing borders between virtual and physical or between users and technical artifacts is misleading. In contrast to that, we aim to treat the system as a whole. To achieve this, the paper presents a generic coordination model based on third-order cybernetics. In particular, the holistic integration of humans and other living systems into CPSs is presented, which leads toward human-centered CPSs.
Keywords: human computer interaction; cyber physical systems; enactive entities; generic coordination model; holistic integration; human-centered CPS; living systems; third-order cybernetics; Collaboration; Complexity theory; Cybernetics; Electronic mail; Informatics; Joining processes; Organizations; Coordination model; cybernetics; enactive entities; holistic integration; human-centered cyber physical system (ID#: 15-6466)


Suchacka, G.; Sobkow, M., “Detection of Internet Robots Using a Bayesian Approach,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp.365-370, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175961
Abstract: A large part of Web traffic on e-commerce sites is generated not by human users but by Internet robots: search engine crawlers, shopping bots, hacking bots, etc. In practice, not all robots, especially the malicious ones, disclose their identities to a Web server and thus there is a need to develop methods for their detection and identification. This paper proposes the application of a Bayesian approach to robot detection based on characteristics of user sessions. The method is applied to the Web traffic from a real e-commerce site. Results show that the classification model based on the cluster analysis with the Ward's method and the weighted Euclidean metric is very effective in robot detection, even obtaining accuracy of above 90%.
Keywords: Bayes methods; Internet; Web sites; electronic commerce; invasive software; pattern classification; pattern clustering; telecommunication traffic; Bayesian approach; Internet robots detection; Internet robots identification; Ward method; Web server; Web traffic; classification model; cluster analysis; e-commerce sites; hacking bots; malicious robots; search engine crawlers; shopping bots; user sessions characteristics; weighted Euclidean metric; Bayes methods; Correlation; Euclidean distance; Internet; Robots; Testing; Bayesian approach; Bayesian statistics; Internet robot; Matlab; Web bot; Web mining; Web robot detection; Web server; Web traffic; cluster analysis; correlation analysis; data mining; e-commerce; log file analysis (ID#: 15-6467)


Jianjia Pan; Xianwei Zheng; Lina Yang; Yulong Wang; Haoliang Yuan; Yuan Yan Tang, “A Forecasting Method Based on Extrema Mean Empirical Mode Decomposition and Wavelet Neural Network,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 377-381, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175963
Abstract: Time series forecasting is a widely and important research area in signal processing and machine learning. With the development of the artificial intelligence (AI), more and more AI technologies are used in time series forecasting. Multi-layer network structure has been widely used for forecasting problems. In this paper, based on a data-driven and adaptive method, extrema mean empirical mode decomposition, we proposed a decomposition-forecasting-ensemble approach to time series forecasting. Experimental result shows the prediction result by proposed models are better than original signal and EMD based models.
Keywords: forecasting theory; learning (artificial intelligence); signal processing; time series; wavelet neural nets; AI technology; EMD based model; adaptive method; artificial intelligence; data-driven; decomposition-forecasting-ensemble approach; extrema mean empirical mode decomposition; forecasting method; forecasting problem; machine learning; multilayer network structure; signal processing; time series forecasting; wavelet neural network; Empirical mode decomposition; Forecasting; Indexes; Market research; Neural networks; Predictive models; Time series analysis; empirical mode decomposition; forecasting; wavelet neural network (ID#: 15-6468)


Czarnul, P.; Rosciszewski, P.; Matuszek, M.; Szymanski, J., “Simulation of Parallel Similarity Measure Computations for Large Data Sets,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp. 472-477, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175980
Abstract: The paper presents our approach to implementation of similarity measure for big data analysis in a parallel environment. We describe the algorithm for parallelisation of the computations. We provide results from a real MPI application for computations of similarity measures as well as results achieved with our simulation software. The simulation environment allows us to model parallel systems of various sizes with various components such as CPUs, GPUs, network interconnects, and model parallel applications in a meta language. The simulations allow us to determine in details how computations will be performed on a particular hardware. They also allow to predict the shapes of time curves beyond the area where empirical results can be obtained due to limited computational resources such as memory capacity.
Keywords: Big Data; data analysis; digital simulation; message passing; parallel processing; Big Data analysis; MPI application; parallel similarity measure; parallelisation algorithm; simulation software; Algorithm design and analysis; Big data; Clustering algorithms; Computational modeling; Data models; Hardware; big data analysis; distance based categorisation; simulation of parallelization. (ID#: 15-6469)


Kasprzak, W.; Stefanczyk, M.; Wilkowski, A., “Printed Steganography Applied for the Authentication of Identity Photos in Face Verification,” in Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, vol., no., pp.512-517, 24-26 June 2015. doi:10.1109/CYBConf.2015.7175987
Abstract: Steganography methods are proposed for the authentication of the holder's photo in an ICAO-consistent (travel) document. The embedded message is heavily influenced by the print-scan process, as the electronic image is first printed to be included into the document (or identity card) and is scanned next to constitute the reference template in an automatic face verification procedure. Two sufficiently robust steganography methods are designed, modifications of the “Fujitsu method” and the “triangle net” method. A third method, a commercial Digimarc tool is also applied. The methods are tested w.r.t. to face image authentication ability in a face verification procedure, using two commercial biometric SDK-s. Test results demonstrate the feasibility in biometric verification and high authentication quality of proposed approach.
Keywords: biometrics (access control); face recognition; steganography; Digimarc tool; Fujitsu method; ICAO-consistent travel document; biometric SDK-s; biometric verification; electronic image; face image authentication; face verification; identity photo authentication; print-scan process; printed steganography; triangle net method; Authentication; Biomedical imaging; Correlation; Distortion; Face; Testing; Watermarking; face biometrics; image authentication; printed steganography. (ID#: 15-6470)


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