Antoni Martínez-Ballesté, Hatem Rashwan, Domenec Puig, Agusti Solanas

International Journal of Information Security 17 (3), 279-290

Description: Worldwide, thousands of video surveillance cameras record our daily activities. People are aware that video surveillance is deployed for the sake of security. However, the privacy of individuals would be endangered if the proper measures were not considered. Privacy-aware video surveillance has historically been addressed by proposals based on detecting individuals and other sensitive parts of the video and hiding them using a variety of techniques. In this paper, we present a comprehensive solution tackling video processing, video protection and management of the Information System. We claim that a video surveillance system can protect our safety and, at the same time, guarantee our privacy. We describe the design and implementation of a privacy-aware video surveillance platform that, in order to be trustworthy, accomplishes with the properties of high detection accuracy, real-time performance and protected video utility. We have tested the proposed platform, and we demonstrate the feasibility of our approach for privacy protection.

Agusti Solanas, Jesus Manjon

RFID Security: Techniques, Protocols and System-On-Chip Design, 289

Description: The deployment of the RFID technology can put the privacy of its users in jeopardy. With the aim of averting the fears of the RFID potential users, a plethora of security and privacy methods have been designed. However, due to the important growth of this technology, scalability problems have arisen and the proper deployment of the technology has become a challenge. In this chapter, we provide a brief overview of the most relevant methods for providing security and privacy to the users of the RFID technology. We pay a special attention to the hash locks proposal and we recall a method based on the distribution of RFID readers, with the aim to provide security and privacy in a scalable fashion. In order to test our method, we have developed a simulator that is presented in this chapter. By using this simulator we study the distribution of several kinds of readers on a variety of scenarios, and we report some of the obtained results.

Fran Casino, Peio Lopez-Iturri, Erik Aguirre, Leyre Azpilicueta, Francisco Falcone, Agusti Solanas

IEEE Access 8, 83070-83080

Description: In this paper, an enhancement of a hybrid simulation technique based on combining collabo- rative filtering with deterministic 3D ray launching algorithm is proposed. Our approach implements a new methodology of data depuration from low definition simulations to reduce noisy simulation cells. This is achieved by processing the maximum number of permitted reflections, applying memory based collaborative filtering, using a nearest neighbors’ approach. The depuration of the low definition ray launching simulation results consists on discarding the estimated values of the cells reached by a number of rays lower than a set value. Discarded cell values are considered noise due to the high error that they provide comparing them to high definition ray launching simulation results. Thus, applying the collaborative filtering technique both to empty and noisy cells, the overall accuracy of the proposed methodology is improved. Specifically, the size of the data collected from the scenarios was reduced by more than 40% after identifying and extracting noisy/erroneous values. In addition, despite the reduced amount of training samples, the new methodology provides an accuracy gain above 8% when applied to the real-world scenario under test, compared with the original approach. Therefore, the proposed methodology provides more precise results from a low definition dataset, increasing accuracy while exhibiting lower complexity in terms of computation and data storage. The enhanced hybrid method enables the analysis of larger complex scenarios with high transceiver density, providing coverage/capacity estimations in the design of heterogeneous IoT network applications.

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