Differentially Private Stream Processing at Scale

We design, to the best of our knowledge, the first differentially private (DP) stream processing system at scale. Our system --Differential Privacy SQL Pipelines (DP-SQLP)-- is built using a streaming framework similar to Spark streaming, and is built on top of the Spanner database and the F1 query engine from Google. Towards designing DP-SQLP we make both algorithmic and systemic advances, namely, we (i) design a novel DP key selection algorithm that can operate on an unbounded set of possible keys, and can scale to one billion keys that users have contributed, (ii) design a preemptive execution scheme for DP key selection that avoids enumerating all the keys at each triggering time, and (iii) use algorithmic techniques from DP continual observation to release a continual DP histogram of user contributions to different keys over the stream length. We empirically demonstrate the efficacy by obtaining at least $16\times$ reduction in error over meaningful baselines we consider

Federated Learning in Mobile Edge Networks: A Comprehensive Survey

In recent years, mobile devices are equipped with increasingly advanced sensing and computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up countless possibilities for meaningful applications. Traditional cloudbased Machine Learning (ML) approaches require the data to be centralized in a cloud server or data center. However, this results in critical issues related to unacceptable latency and communication inefficiency. To this end, Mobile Edge Computing (MEC) has been proposed to bring intelligence closer to the edge, where data is produced. However, conventional enabling technologies for ML at mobile edge networks still require personal data to be shared with external parties, e.g., edge servers. Recently, in light of increasingly stringent data privacy legislations and growing privacy concerns, the concept of Federated Learning (FL) has been introduced. In FL, end devices use their local data to train an ML model required by the server. The end devices then send the model updates rather than raw data to the server for aggregation. FL can serve as an enabling technology in mobile edge networks since it enables the collaborative training of an ML model and also enables DL for mobile edge network optimization. However, in a large-scale and complex mobile edge network, heterogeneous devices with varying constraints are involved. This raises challenges of communication costs, resource allocation, and privacy and security in the implementation of FL at scale. In this survey, we begin with an introduction to the background and fundamentals of FL. Then, we highlight the aforementioned challenges of FL implementation and review existing solutions. Furthermore, we present the applications of FL for mobile edge network optimization. Finally, we discuss the important challenges and future research directions in F

Blockchain based secure message dissemination in vehicular networks

Vehicular ad-hoc networks (VANETs) are one of the key elements in Intelligent Transportation System (ITS) to enable information exchange among vehicles and Roadside Units (RSUs) via vehicle-to-vehicle (V2V) and vehicle-to- nfrastructure (V2I) communications. With continuously increasing number of vehicles on road, there are numerous security and privacy challenges associated with VANETs. Communication among vehicles is needed to be secure and bandwidth efficient. Also, the messages exchanged between vehicles must be authentic so as to maintain a trusted network in a privacy-preserving manner. Furthermore, a sustainable economic model is required to incentivise honest and cooperative vehicles. Traditional security and privacy solutions in centralised networks are not applicable to VANETs due to its distributed nature, heterogeneity, high mobility and low latency requirements. Meanwhile, the new development of blockchain has been attracting significant interests due to its key features including consensus to evaluate message credibility and immutable storage in distributed ledger, which provides an alternative solution to the security and privacy challenges in VANETs. This thesis aims to present blockchain solutions for the security and privacy of VANETs meeting the stringent requirements of low latency and bandwidth-efficient message dissemination. VANETs are simulated in OMNeT++ to validate the proposed solutions. Specifically, two novel blockchain consensus algorithms have been developed for message authentication and relay selection in presence of malicious vehicles. The first employs a voting based message validation and relay selection, which reduces the failure rate in message validation by 11% as compared to reputation based consensus. The second utilises federated learning supported by blockchain as a better privacy-preserving solution, which is 65.2% faster than the first voting based solution. Both approaches include blockchain-based incentive mechanisms and game theory analysis to observe strategic behaviour of honest and malicious vehicles. To further study the privacy aspect of vehicular networks, the integration of blockchain with physical layer security is also theoretically analysed in Vehicle-to-Everything (V2X) communications scenarios. The integration results in 8.2 Mbps increased goodput as compared to the blockchain solution alone. In essence, our research work shows that blockchain can offer better control and security, as compared to centralised solutions, if properly adjusted according to the application and network requirements. Thus, the proposed solutions can provide guidelines for practically feasible application of blockchain in vehicular networks

Actas de las VI Jornadas Nacionales (JNIC2021 LIVE)

Estas jornadas se han convertido en un foro de encuentro de los actores más relevantes en el ámbito de la ciberseguridad en España. En ellas, no sólo se presentan algunos de los trabajos científicos punteros en las diversas áreas de ciberseguridad, sino que se presta especial atención a la formación e innovación educativa en materia de ciberseguridad, y también a la conexión con la industria, a través de propuestas de transferencia de tecnología. Tanto es así que, este año se presentan en el Programa de Transferencia algunas modificaciones sobre su funcionamiento y desarrollo que han sido diseñadas con la intención de mejorarlo y hacerlo más valioso para toda la comunidad investigadora en ciberseguridad

IDEAS-1997-2021-Final-Programs

This document records the final program for each of the 26 meetings of the International Database and Engineering Application Symposium from 1997 through 2021. These meetings were organized in various locations on three continents. Most of the papers published during these years are in the digital libraries of IEEE(1997-2007) or ACM(2008-2021)

Physical Layer Challenges and Solutions in Seamless Positioning via GNSS, Cellular and WLAN Systems

As different positioning applications have started to be a common part of our lives, positioning methods have to cope with increasing demands. Global Navigation Satellite System (GNSS) can offer accurate location estimate outdoors, but achieving seamless large-scale indoor localization remains still a challenging topic. The requirements for simple and cost-effective indoor positioning system have led to the utilization of wireless systems already available, such as cellular networks and Wireless Local Area Network (WLAN). One common approach with the advantage of a large-scale standard-independent implementation is based on the Received Signal Strength (RSS) measurements.This thesis addresses both GNSS and non-GNSS positioning algorithms and aims to offer a compact overview of the wireless localization issues, concentrating on some of the major challenges and solutions in GNSS and RSS-based positioning. The GNSS-related challenges addressed here refer to the channel modelling part for indoor GNSS and to the acquisition part in High Sensitivity (HS)-GNSS. The RSSrelated challenges addressed here refer to the data collection and calibration, channel effects such as path loss and shadowing, and three-dimensional indoor positioning estimation.This thesis presents a measurement-based analysis of indoor channel models for GNSS signals and of path loss and shadowing models for WLAN and cellular signals. Novel low-complexity acquisition algorithms are developed for HS-GNSS. In addition, a solution to transmitter topology evaluation and database reduction solutions for large-scale mobile-centric RSS-based positioning are proposed. This thesis also studies the effect of RSS offsets in the calibration phase and various floor estimators, and offers an extensive comparison of different RSS-based positioning algorithms

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023

Jornadas Nacionales de Investigación en Ciberseguridad (8ª. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernización tecnolóxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida