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Open access

Tibor Jager and Andy Rupp

Abstract

We formalize and construct black-box accumulation (BBA), a useful building block for numerous important user-centric protocols including loyalty systems, refund systems, and incentive systems (as, e.g., employed in participatory sensing and vehicle-to-grid scenarios). A core requirement all these systems share is a mechanism to let users collect and sum up values (call it incentives, bonus points, reputation points, etc.) issued by some other parties in a privacy-preserving way such that curious operators may not be able to link the different transactions of a user. At the same time, a group of malicious users may not be able to cheat the system by pretending to have collected a higher amount than what was actually issued to them.

As a first contribution, we fully formalize the core functionality and properties of this important building block. Furthermore, we present a generic and non-interactive construction of a BBA system based on homomorphic commitments, digital signatures, and non-interactive zero-knowledge proofs of knowledge. For our construction, we formally prove security and privacy properties. Finally, we propose a concrete instantiation of our construction using Groth-Sahai commitments and proofs as well as the optimal structure-preserving signature scheme of Abe et al. and analyze its efficiency.

Open access

Tarek R. Besold, Kai-Uwe Kühnberger and Tony Veale

Abstract

Over the last decade, computational creativity as a field of scientific investigation and computational systems engineering has seen growing popularity. Still, the levels of development between projects aiming at systems for artistic production or performance and endeavours addressing creative problem-solving or models of creative cognitive capacities is diverging. While the former have already seen several great successes, the latter still remain in their infancy. This volume collects reports on work trying to close the accrued gap.

Open access

Gyöngyvér Kiss

Abstract

This paper deals with an implementation of the elliptic curve primality proving (ECPP) algorithm of Atkin and Morain. As the ECPP algorithm is not deterministic, we are developing a strategy to avoid certain situations in which the original implementation could get stuck and to get closer to the situation where the probability that the algorithm terminates successfully is 1. We apply heuristics and tricks in order to test the strategy in our implementation in Magma on numbers of up to 7000 decimal digits and collect data to show the advantages over previous implementations in practice.

Open access

Zbigniew Chaniecki, Krzysztof Grudzień, Tomasz Jaworski, Grzegorz Rybak, Andrzej Romanowski and Dominik Sankowski

Abstract

The paper presents results of the scale-up silo flow investigation in based on accelerometer signal analysis and Wi-Fi transmission, performed in distributed laboratory environment. Prepared, by the authors, a set of 8 accelerometers allows to measure a three-dimensional acceleration vector. The accelerometers were located outside silo, on its perimeter. The accelerometers signal changes allowed to analyze dynamic behavior of solid (vibrations/pulsations) at silo wall during discharging process. These dynamic effects are caused by stick-slip friction between the wall and the granular material. Information about the material pulsations and vibrations is crucial for monitoring the interaction between silo construction and particle during flow. Additionally such spatial position of accelerometers sensor allowed to collect information about nonsymmetrical flow inside silo.

Open access

Zhe Li, Chen Ma and Tian-Fan Zhang

Abstract

Depth data is an effective tool to locate the intelligent agent in space because it accurately records the 3D geometry information on the surface of the scanned object, and is not affected by factors like shadow and light. However, if there are many planes in the work scene, it is difficult to identify objects and process the resulting huge amount of data. In view of this problem and targeted at object calibration, this paper puts forward a depth data calibration method based on Gauss mixture model. The method converts the depth data to point cloud, filters the noise and collects samples, which effectively reduces the computational load in the following steps. Besides, the authors cluster the point cloud vector with the Gaussian mixture model, and obtain the target and background planes by using the random sampling consensus algorithm to fit the planes. The combination of target Region Of Intelligent agent (ROI) and point cloud significantly reduces the computational load and improves the computing speed. The effect and accuracy of the algorithm is verified by the test of the actual object.

Open access

A. Bartoli, A. De Lorenzo, E. Medvet and F. Tarlao

Abstract

Recent phishing campaigns are increasingly targeted to specific, small population of users and last for increasingly shorter life spans. There is thus an urgent need for developing defense mechanisms that do not rely on any forms of blacklisting or reputation: there is simply no time for detecting novel phishing campaigns and notify all interested organizations quickly enough. Such mechanisms should be close to browsers and based solely on the visual appearance of the rendered page. One of the major impediments to research in this area is the lack of systematic knowledge about how phishing pages actually look like. In this work we describe the technical challenges in collecting a large and diverse collection of screenshots of phishing pages and propose practical solutions. We also analyze systematically the visual similarity between phishing pages and pages of targeted organizations, from the point of view of a similarity metric that has been proposed as a foundation for visual phishing detection and from the point of view of a human operator.

Open access

Xiaolu Xie

. Tebbini, E. B. Braiek. Smart Real Time Adaptive Gaussian Filter Supervised Neural Network for Efficient Gray Scale and RGB Image De-Noising. - Intelligent Automation & Soft Computing, 2014, pp. 203-211. 8. Fang, J., Q. Cao. Total Variation Image De-Noising Bases on the Improved Sobel Operator. - Journal of Multimedia, 2013, pp. 84-91. 9. Yin, L., D. Chen, C. Li. Two-Dimensional Wavelet Transform De-Noising Algorithm in Collecting Intelligent Agriculture Image. - Journal of Software, 2013, pp. 84-89.

Open access

Roger B. Grinde

-1942, Jul. 2007. https://doi.org/10.1016/j.cor.2005.07.022 [11] M. Fischetti and P. Toth, “An Additive Approach for the Optimal Solution of the Prize-Collecting Traveling Salesman Problem,” in Vehicle Routing: Methods and Studies, B. L. Golden and A. A. Assad Eds. Amsterdam: North-Holland, pp. 319-343, 1988. [12] E. Balas, “The prize collecting traveling salesman problem,” Networks, vol. 19, no. 6, pp. 621-636, Oct. 1989. https://doi.org/10.1002/net.3230190602 [13] B. L. Golden, L. Levy and R. Vohra, “The Orienteering

Open access

Liwei Fu and Sen Wu

. Cybernetics A Publication of the IEEE Systems Man & Cybernetics Society, Vol. 43 , 2012, No 3, pp. 982-994. 12. Kraus, J. M., C. Müssel, G. Palm et al. Multi-Objective Selection for Collecting Cluster Alternatives. – Computational Statistics, Vol. 26 , 2011, No 2, pp. 341-353. 13. Zhang, G. X., L. Q. Pan. School of Electrical Engineering, University S. J., Chengdu. A Survey of Membrane Computing as a New Branch of Natural Computing. – Chinese Journal of Computers, Vol. 33 , 2010, No 2, pp. 208-214. 14. Busi, N. Using Well-Structured Transition Systems

Open access

Zhixin Tie

References 1. Barth, J. S. System and Method for Collecting and Displaying Information about Many Computer Systems. U. S. Patent No US 8131842B1, March 6, 2012. 2. Stallings, W. SNMP, SNMPv2, SNMPv3 and RMON 1 and 2. Third Ed. Addison Wesley, 1999. 3. Zeng, W., Y. Wang. Design and Implementation of Server Monitoring System Based on SNMP. - In: Proceedings of 1st IITA International Joint Conference on Artificial Intelligence, China, Hainan Island, April 2009, 680-682. 4. Yuchen g, L., L