The Experts below are selected from a list of 85794 Experts worldwide ranked by ideXlab platform
Salim Hariri - One of the best experts on this subject based on the ideXlab platform.
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static versus dynamic data information fusion analysis using dddas for cyber Security trust
International Conference on Conceptual Structures, 2014Co-Authors: Erik Blasch, Youssif Alnashif, Salim HaririAbstract:Abstract Information fusion includes signals, features, and decision -level analysis over various types of data including imagery, te xt, and cyber Security Detection. With the maturity of data processing, the e xplosion of big data, and the need fo r user acceptance; the Dynamic Data-Driven Application System (DDDAS) philosophy fosters insights into the usability of information systems solutions. In this paper, we e xp lore a notion of an adaptive adjustment of secure communication trust analysis that seeks a balance between standard static solutions versus dynamic -data driven updates. A use case is provided in determin ing trust for a cyber Security scenario exp loring comparisons of Bayesian versus evidential reasoning for dynamic Security Detection updates. Using the evidential reasoning proportional conflict redistribution (PCR) method, we demonstrate improved trust for dynamically changing Detections of denial of service attacks.
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ICCS - Static versus dynamic data information fusion analysis using DDDAS for cyber Security trust
Procedia Computer Science, 2014Co-Authors: Erik Blasch, Youssif Al-nashif, Salim HaririAbstract:Abstract Information fusion includes signals, features, and decision -level analysis over various types of data including imagery, te xt, and cyber Security Detection. With the maturity of data processing, the e xplosion of big data, and the need fo r user acceptance; the Dynamic Data-Driven Application System (DDDAS) philosophy fosters insights into the usability of information systems solutions. In this paper, we e xp lore a notion of an adaptive adjustment of secure communication trust analysis that seeks a balance between standard static solutions versus dynamic -data driven updates. A use case is provided in determin ing trust for a cyber Security scenario exp loring comparisons of Bayesian versus evidential reasoning for dynamic Security Detection updates. Using the evidential reasoning proportional conflict redistribution (PCR) method, we demonstrate improved trust for dynamically changing Detections of denial of service attacks.
Erik Blasch - One of the best experts on this subject based on the ideXlab platform.
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static versus dynamic data information fusion analysis using dddas for cyber Security trust
International Conference on Conceptual Structures, 2014Co-Authors: Erik Blasch, Youssif Alnashif, Salim HaririAbstract:Abstract Information fusion includes signals, features, and decision -level analysis over various types of data including imagery, te xt, and cyber Security Detection. With the maturity of data processing, the e xplosion of big data, and the need fo r user acceptance; the Dynamic Data-Driven Application System (DDDAS) philosophy fosters insights into the usability of information systems solutions. In this paper, we e xp lore a notion of an adaptive adjustment of secure communication trust analysis that seeks a balance between standard static solutions versus dynamic -data driven updates. A use case is provided in determin ing trust for a cyber Security scenario exp loring comparisons of Bayesian versus evidential reasoning for dynamic Security Detection updates. Using the evidential reasoning proportional conflict redistribution (PCR) method, we demonstrate improved trust for dynamically changing Detections of denial of service attacks.
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ICCS - Static versus dynamic data information fusion analysis using DDDAS for cyber Security trust
Procedia Computer Science, 2014Co-Authors: Erik Blasch, Youssif Al-nashif, Salim HaririAbstract:Abstract Information fusion includes signals, features, and decision -level analysis over various types of data including imagery, te xt, and cyber Security Detection. With the maturity of data processing, the e xplosion of big data, and the need fo r user acceptance; the Dynamic Data-Driven Application System (DDDAS) philosophy fosters insights into the usability of information systems solutions. In this paper, we e xp lore a notion of an adaptive adjustment of secure communication trust analysis that seeks a balance between standard static solutions versus dynamic -data driven updates. A use case is provided in determin ing trust for a cyber Security scenario exp loring comparisons of Bayesian versus evidential reasoning for dynamic Security Detection updates. Using the evidential reasoning proportional conflict redistribution (PCR) method, we demonstrate improved trust for dynamically changing Detections of denial of service attacks.
Wei Wang - One of the best experts on this subject based on the ideXlab platform.
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Game theoretical Security Detection strategy for networked systems
Information Sciences, 2018Co-Authors: Wei Wang, Changyun WenAbstract:Abstract In this paper, a game theoretical analysis method is presented to provide the optimal Security Detection strategies for heterogeneous networked systems. A two-stage game model is firstly established, in which the attacker and defender are considered as two players. In the first stage, the two players make decisions on whether to execute the attack/monitoring actions or to keep silence for each network unit. In the second stage, two important strategic varibles, i.e. the attack intensity and Detection threshold, are cautiously determined. The necessary and sufficient conditions to ensure the existence of the Nash equilibriums for the game with complete information are rigorously analyzed. The results reflect that with limited resources and capacities, the defender (attacker) tends to perform defense (attack) actions and further allocate more defense (less attack) resources to the units with larger assets. Besides, Bayesian and robust Nash equilibrium analysis is provided for the game with incomplete information. Finally, a sampling based Nash equilibrium verification and calculation approach is proposed for the game model with continuous kernels. Thus the convexity restrictions can be relaxed and the computational complexity is effectively reduced, with comparison to the existing recursive calculation methods. Numerical examples are given to validate our theoretical results.
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A Game Theory Based Collaborative Security Detection Method for Internet of Things Systems
IEEE Transactions on Information Forensics and Security, 2018Co-Authors: Wei WangAbstract:A collaborative Security Detection method is investigated for the Internet of Things (IoT) systems. Consensus protocol is utilized to implement the information sharing and fusion in a collaborative manner. A game theoretical analysis framework is developed for the collaborative Security Detection by considering the confrontation between the defender and the attacker. The objective is to achieve the maximum Security protection for the entire IoT systems. The existence and uniqueness of the Nash equilibrium of game model with complete consensus are analyzed. Then an iteration learning based calculation method is presented to determine the Nash equilibrium. Quantitative analysis is provided for the relationship between the Nash equilibriums of the game models in the cases of complete and incomplete consensus with infinite and finite number of iterations. Simulation results by considering DDoS attack are also provided to verify our theoretical results.
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A Web Security Data Detection Based on Group Scanning
2015 Eighth International Conference on Internet Computing for Science and Engineering (ICICSE), 2015Co-Authors: Xuan Shichang, Wei Wang, Dapeng Man, Wu YangAbstract:After studying the current principle andarchitecture of antivirus gateway for Web Security Detection, we found that the conventional virus scan is based on filescanning, which takes significant processing time. Whenscanning big size files, it may often cause disconnection of filetransferring with a time-out error message prompted out. Tosolve the problem of slow file virus scan, we propose a newmethod in which a packet scanning is introduced instead oftraditional file scanning. This method can be used to processfile receiving and scanning in parallel. The experiment resultsprove that this method significantly improve the performanceof Security Detection speed.
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A Method for Computer Software Security Detection
Advanced Materials Research, 2011Co-Authors: Yong Cheng, Wen Zhong Yang, Ling Yang, Wei Wang, Feng Wang, Yong ZhouAbstract:This paper proposed a method and a prototype using static analysis to detect Security of computer software. There are many buffer overflow vulnerabilities in released software. It uses the static object code analysis technology to detect buffer overflow, and analysis some unsafe function to determine whether the software has some default. It compares the different results of the proposed tool and traditional buffer overflow detecting tools, the false alarm rate is less than others, false negative rate is same as others.
Chris Chatwin - One of the best experts on this subject based on the ideXlab platform.
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an implementation and performance evaluation of a space variant ot mach filter for a Security Detection application using flir sensor
Applied Imagery Pattern Recognition Workshop, 2010Co-Authors: Akber Gardezi, Ahmed Alkandri, Philip Birch, Tabassum R Qureshi, Rupert Young, Chris ChatwinAbstract:A space variant Optimal Trade-off Maximum Average Correlation Height (OT-MACH) filter is designed specifically for images acquired from a forward looking infrared (FLIR) sensor, using the maximum of the power spectral density (PSD) of the input image instead of the white noise covariance factor. The kernel can be locally modified depending upon its position in the input frame, which enables adaptation of the filter dependant on background heat signature variances and also enables the normalization of the filter energy levels. The Detection capabilities of the filter were evaluated using different data sets of real images and 3D models for a suspected threat in order to define a thresholding parameter. The parameter was based on peak to correlation energy (PCE) and peak to side lobe ratio (PSR) of the correlation output which led to the definition of a criterion for predicting true and false Detections. The hardware implementation of the system has been discussed in terms of FPGA versus DSP chipsets and a performance benchmark has been created using millions of multiply-accumulate operations per second (MMAC) and the cost. In this paper we propose an implementation and performance evaluation of a Security Detection application which uses a space variant OT-MACH filter with different data sets. Also a performance benchmark has been created for the hardware implementation of the proposed system on popular FPGA and DSP chipsets.
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AIPR - An implementation and performance evaluation of a space variant OT-MACH filter for a Security Detection application using FLIR sensor
2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR), 2010Co-Authors: Akber Gardezi, Ahmed Alkandri, Philip Birch, Tabassum R Qureshi, Rupert Young, Chris ChatwinAbstract:A space variant Optimal Trade-off Maximum Average Correlation Height (OT-MACH) filter is designed specifically for images acquired from a forward looking infrared (FLIR) sensor, using the maximum of the power spectral density (PSD) of the input image instead of the white noise covariance factor. The kernel can be locally modified depending upon its position in the input frame, which enables adaptation of the filter dependant on background heat signature variances and also enables the normalization of the filter energy levels. The Detection capabilities of the filter were evaluated using different data sets of real images and 3D models for a suspected threat in order to define a thresholding parameter. The parameter was based on peak to correlation energy (PCE) and peak to side lobe ratio (PSR) of the correlation output which led to the definition of a criterion for predicting true and false Detections. The hardware implementation of the system has been discussed in terms of FPGA versus DSP chipsets and a performance benchmark has been created using millions of multiply-accumulate operations per second (MMAC) and the cost. In this paper we propose an implementation and performance evaluation of a Security Detection application which uses a space variant OT-MACH filter with different data sets. Also a performance benchmark has been created for the hardware implementation of the proposed system on popular FPGA and DSP chipsets.
Youssif Alnashif - One of the best experts on this subject based on the ideXlab platform.
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static versus dynamic data information fusion analysis using dddas for cyber Security trust
International Conference on Conceptual Structures, 2014Co-Authors: Erik Blasch, Youssif Alnashif, Salim HaririAbstract:Abstract Information fusion includes signals, features, and decision -level analysis over various types of data including imagery, te xt, and cyber Security Detection. With the maturity of data processing, the e xplosion of big data, and the need fo r user acceptance; the Dynamic Data-Driven Application System (DDDAS) philosophy fosters insights into the usability of information systems solutions. In this paper, we e xp lore a notion of an adaptive adjustment of secure communication trust analysis that seeks a balance between standard static solutions versus dynamic -data driven updates. A use case is provided in determin ing trust for a cyber Security scenario exp loring comparisons of Bayesian versus evidential reasoning for dynamic Security Detection updates. Using the evidential reasoning proportional conflict redistribution (PCR) method, we demonstrate improved trust for dynamically changing Detections of denial of service attacks.
