A Lightweight Privacy-Preserving Fair Meeting Location Determination Scheme

Equipped with mobile devices, people relied on location-based services can expediently and reasonably organize their activities. But location information may disclose people\u27s sensitive information, such as interests, health status. Besides, the limited resources of mobile devices restrict the further development of location-based services. In this paper, aiming at the fair meeting position determination service, we design a lightweight privacy-preserving solution. In our scheme, mobile users only need to submit service requests. A cloud server and a location services provider are responsible for service response, where the cloud server achieves most of the calculation, and the location services provider determines the fair meeting location based on the computational results of the cloud server and broadcasts it to mobile users. The proposed scheme adopts homomorphic encryptions and random permutation methods to preserve the location privacy of mobile users. The security analyses show that the proposed scheme is privacy-preserving under our defined threat models. Besides, the presented solution only needs to calculate n Euclidean distances, and hence, our scheme has linear computation and communication complexity

Lightweight Privacy-Preserving Ride-Sharing Protocols for Autonomous Cars

Peer reviewe

Privacy in Mobile Computing for Location-Sharing-Based Services

Location-Sharing-Based Services (LSBS) complement Location-Based Services by using locations from a group of users, and not just individuals, to provide some contextualized service based on the locations in the group. However, there are growing concerns about the misuse of location data by third-parties, which fuels the need for more privacy controls in such services. We address the relevant problem of privacy in LSBSs by providing practical and effective solutions to the privacy problem in one such service, namely the fair rendez-vous point (FRVP) determination service. The privacy preserving FRVP (PPFRVP) problem is general enough and nicely captures the computations and privacy requirements in LSBSs. In this paper, we propose two privacy-preserving algorithms for the FRVP problem and analytically evaluate their privacy in both passive and active adversarial scenarios. We study the practical feasibility and performance of the proposed approaches by implementing them on Nokia mobile devices. By means of a targeted user-study, we attempt to gain further understanding of the popularity, the privacy and acceptance of the proposed solutions

"Once Upon a Place": Compute Your Meeting Location Privately

Popular services such as Doodle Mobile and Tymelie are extremely useful planning tools that enable mobile-phone users to determine common meeting time(s) for events. Similar planning tools for determining optimal meeting locations, based on the location preferences of the users, are highly desirable for event planning and management in popular mobile phone applications, such as taxi sharing, route planning and mobile participatory sensing. Yet, they have received very little attention by researchers. An important, and often overlooked, facet of such planning applications is the privacy of the participating users and their preferences; users want to agree on a meeting location without necessarily revealing their location preferences to the service provider or to the other users. In this paper, we address the problem of privacy-preserving optimal meeting-location computation, especially focusing on its applicability to current mobile devices and applications. We first define the notion of privacy in such computations. Second, we model the problem of optimal meeting-location computation as a privacy-preserving k-center problem and we design two solutions; both solutions take advantage of the homomorphic properties of well-known cryptosystems by Boneh-Goh-Nissim, ElGamal and Paillier in order to perform oblivious computations. Third, we implement the proposed solutions on a testbed of the latest generation Nokia mobile devices and study their performance. Finally, we assess the utility and expectations, in terms of privacy and usability, of the proposed solutions by means of a targeted survey and user-study of mobile-phone users

Technologies respectueuses de la vie privée pour le covoiturage

L'émergence des téléphones mobiles et objets connectés a profondément changé notre vie quotidienne. Ces dispositifs, grâce à la multitude de capteurs qu'ils embarquent, permettent l'accès à un large spectre de services. En particulier, les capteurs de position ont contribué au développement des services de localisation tels que la navigation, le covoiturage, le suivi de la congestion en temps réel... En dépit du confort offert par ces services, la collecte et le traitement des données de localisation portent de sérieuses atteintes à la vie privée des utilisateurs. En effet, ces données peuvent renseigner les fournisseurs de services sur les points d'intérêt (domicile, lieu de travail, orientation sexuelle), les habitudes ainsi que le réseau social des utilisateurs. D'une façon générale, la protection de la vie privée des utilisateurs peut être assurée par des dispositions légales ou techniques. Même si les mesures d'ordre légal peuvent dissuader les fournisseurs de services et les individus malveillants à enfreindre le droit à la vie privée des utilisateurs, les effets de telles mesures ne sont observables que lorsque l'infraction est déjà commise et détectée. En revanche, l'utilisation des technologies renforçant la protection de la vie privée (PET) dès la phase de conception des systèmes permet de réduire le taux de réussite des attaques contre la vie privée des utilisateurs. L'objectif principal de cette thèse est de montrer la viabilité de l'utilisation des PET comme moyens de protection des données de localisation dans les services de covoiturage. Ce type de service de localisation, en aidant les conducteurs à partager les sièges vides dans les véhicules, contribue à réduire les problèmes de congestion, d'émissions et de dépendance aux combustibles fossiles. Dans cette thèse, nous étudions les problèmes de synchronisation d'itinéraires et d'appariement relatifs au covoiturage avec une prise en compte explicite des contraintes de protection des données de localisation (origine, destination). Les solutions proposées dans cette thèse combinent des algorithmes de calcul d'itinéraires multimodaux avec plusieurs techniques de protection de la vie privée telles que le chiffrement homomorphe, l'intersection sécurisée d'ensembles, le secret partagé, la comparaison sécurisée d'entier. Elles garantissent des propriétés de protection de vie privée comprenant l'anonymat, la non-chainabilité et la minimisation des données. De plus, elles sont comparées à des solutions classiques, ne protégeant pas la vie privée. Nos expérimentations indiquent que les contraintes de protection des données privées peuvent être prise en compte dans les services de covoiturage sans dégrader leurs performances.The emergence of mobile phones and connected objects has profoundly changed our daily lives. These devices, thanks to the multitude of sensors they embark, allow access to a broad spectrum of services. In particular, position sensors have contributed to the development of location-based services such as navigation, ridesharing, real-time congestion tracking... Despite the comfort offered by these services, the collection and processing of location data seriously infringe the privacy of users. In fact, these data can inform service providers about points of interests (home, workplace, sexual orientation), habits and social network of the users. In general, the protection of users' privacy can be ensured by legal or technical provisions. While legal measures may discourage service providers and malicious individuals from infringing users' privacy rights, the effects of such measures are only observable when the offense is already committed and detected. On the other hand, the use of privacy-enhancing technologies (PET) from the design phase of systems can reduce the success rate of attacks on the privacy of users. The main objective of this thesis is to demonstrate the viability of the usage of PET as a means of location data protection in ridesharing services. This type of location-based service, by allowing drivers to share empty seats in vehicles, helps in reducing congestion, CO2 emissions and dependence on fossil fuels. In this thesis, we study the problems of synchronization of itineraries and matching in the ridesharing context, with an explicit consideration of location data (origin, destination) protection constraints. The solutions proposed in this thesis combine multimodal routing algorithms with several privacy-enhancing technologies such as homomorphic encryption, private set intersection, secret sharing, secure comparison of integers. They guarantee privacy properties including anonymity, unlinkability, and data minimization. In addition, they are compared to conventional solutions, which do not protect privacy. Our experiments indicate that location data protection constraints can be taken into account in ridesharing services without degrading their performance

Recent Advances in Industrial and Applied Mathematics

This open access book contains review papers authored by thirteen plenary invited speakers to the 9th International Congress on Industrial and Applied Mathematics (Valencia, July 15-19, 2019). Written by top-level scientists recognized worldwide, the scientific contributions cover a wide range of cutting-edge topics of industrial and applied mathematics: mathematical modeling, industrial and environmental mathematics, mathematical biology and medicine, reduced-order modeling and cryptography. The book also includes an introductory chapter summarizing the main features of the congress. This is the first volume of a thematic series dedicated to research results presented at ICIAM 2019-Valencia Congress

The development of distributed and peer-to-peer systems for future smart grids

The widespread application of smart grid concept has promoted the development of modern power systems featured with smart facilities, distributed resources and advanced ICT, and shifted towards complex cyber-physical and internet-of-things (IoT) embedded system. The traditional centralized system structure or management mode is faced with the challenges of coping with the growing network traffic, computing burden, demand for flexible services, and risks from cyber-attacks. In this regard, the development of distributed systems, as a valuable research theme, has sparked attentions from researchers and practitioners, which involves several crucial concerns including data security, reliability, and privacy. As a potential solution, blockchain (BC) technology shows its proper applicability due to its characteristics, but it encounters some problems such as unsatisfied resource efficiency. Meanwhile, the increasing integration of distributed system and distributed renewable generation in power system has raised challenges in the system stability and efficient management. In above context, this research focuses on the development of distributed and peer-to-peer (P2P) systems for future smart grids. Firstly, the research comprehensively reviews the-state-of-art of BC and IoT in smart grids, then put forwards their potential application scenarios in future grids with discussing the related challenges. Afterwards, this research integrates homomorphic cryptography with the technical components of BC as a basic paradigm to propose a distributed, secure and privacy-preserving smart meter data aggregation framework, providing the utility with high robust data management services. In addition, an agent bidding based trading scheme is designed for users to purchase electricity from the small-scale renewable power plant under stand-alone system, making individual bidding data not exposed in the storage and entire trading process even if the distributed system nodes are eavesdropped. In order to cope with the negative influences from distributed generation, this research proposes a deviation penalty method to help narrow the gap between the real-time demand/output and pre-determined transaction outcomes in P2P trading under power distribution system. At the end of this thesis, the potential future research works are discussed

Recent Advances in Industrial and Applied Mathematics

This open access book contains review papers authored by thirteen plenary invited speakers to the 9th International Congress on Industrial and Applied Mathematics (Valencia, July 15-19, 2019). Written by top-level scientists recognized worldwide, the scientific contributions cover a wide range of cutting-edge topics of industrial and applied mathematics: mathematical modeling, industrial and environmental mathematics, mathematical biology and medicine, reduced-order modeling and cryptography. The book also includes an introductory chapter summarizing the main features of the congress. This is the first volume of a thematic series dedicated to research results presented at ICIAM 2019-Valencia Congress

Automating SLA enforcement in the cloud computing

Cloud computing is playing an increasingly important role, not only by facilitating digital trading platforms but also by transforming conventional services from client-server models to cloud computing. This domain has given the global economic and technological benefits, it offers to both the service providers and service subscribers. Digital marketplaces are no longer limited only to trade tangible commodities but also facilitates enormous service virtualization across various industries. Software as a Service (SaaS) being the largest service segment, dominates the global cloud migration. Infrastructure as a Service (IaaS) and cloud-based application development also known as Platform as a Service (PaaS) are also next-generation computing platforms for their ultimate futuristic demand by both, public and private sector. These service segments are now hosted on cloud platforms to compute, store, and network, an enormous amount of service requests, which process data incredibly fast and economically. Organizations also perform data analytics and other similar computing amenities to manage their business without maintaining on-premise computing infrastructures which are hard to maintain. This computing capability has extensively improved the popularity and increased the demand for cloud services to an extent, that businesses worldwide are heavily migrating their computing resources to these platforms. Diverse cloud service providers take the responsibility of provisioning such cloud-based services for subscribers. In return, a certain subscription fee is charged to them periodically and depending upon the service package, availability and security. On the flip side, such intensive technology shift and outsourcing reliance have also introduced scenarios that any failure on their part leads to serious consequences to the business community at large. In recent years technology industry has observed critical and increased service outages at various cloud service providers(CSP) such as Amazon AWS, Microsoft, Google, which ultimately interrupts the entire supply chain and causes several well-known web services to be taken offline either due to a human error, failed change control implementation or in more recently due to targeted cyber-attacks like DDoS. These web-based solutions such as compute, storage, network or other similar services are provisioned to cloud service subscribers (CSS) platforms. Regardless of a cloud service deployment, a legal binding such as a Service Level Agreement (SLA) is signed between the CSP and CSS. The SLA holds a service scope and guarantees in case of failure. There are probabilities where these SLA may be violated, revoked, or dishonoured by either party, mostly the CSP. An SLA violation along with an unsettled dispute leads to some financial losses for the service subscribers or perhaps cost them their business reputation. Eventually, the subscriber may request some form of compensation from the provider such as a service credit or a refund. In either case, the burden of proof lies with the subscribers, who have to capture and preserve those data or forensically sound system or service logs, supporting their claims. Most of the time, this is manually processed, which is both expensive and time-consuming. To address this problem, this research first analyses the gaps in existing arrangements. It then suggests automation of SLA enforcement within cloud environments and identifies the main properties of a solution to the problem covering various other avenues associated with the other operating environments. This research then subsequently proposes architectures, based on the concept of fair exchange, and shows that how intelligently the approach enforces cloud SLA using various techniques. Furthermore, by extending the research scope covering two key scenarios (a) when participants are loss averse and (b) when interacting participants can act maliciously. Our proposed architectures present robust schemes by enforcing the suggested solutions which are effective, efficient, and most importantly resilient to modern-day security and privacy challenges. The uniqueness of our research is that it does not only ensure the fairness aspect of digital trading but it also extends and logically implements a dual security layer throughout the service exchange. Using this approach protects business participants by securely automating the dispute resolutions in a more resilient fashion. It also shields their data privacy and security from diverse cyber challenges and other operational failures. These architectures are capable of imposing state-of-the-art defences through integrated secure modules along with full encryption schemes, mitigating security gaps previously not dealt with, based upon fair exchange protocols. The Protocol also accomplishes achieving service exchange scenarios either with or without dispute resolution. Finally, our proposed architectures are automated and interact with hardcoded procedures and verifications mechanism using a variant of trusted third parties and trusted authorities, which makes it difficult to cause potential disagreements and misbehaviours during a cloud-based service exchange by enforcing SLA

Leveraging Client Processing for Location Privacy in Mobile Local Search

Usage of mobile services is growing rapidly. Most Internet-based services targeted for PC based browsers now have mobile counterparts. These mobile counterparts often are enhanced when they use user\u27s location as one of the inputs. Even some PC-based services such as point of interest Search, Mapping, Airline tickets, and software download mirrors now use user\u27s location in order to enhance their services. Location-based services are exactly these, that take the user\u27s location as an input and enhance the experience based on that. With increased use of these services comes the increased risk to location privacy. The location is considered an attribute that user\u27s hold as important to their privacy. Compromise of one\u27s location, in other words, loss of location privacy can have several detrimental effects on the user ranging from trivial annoyance to unreasonable persecution. More and more companies in the Internet economy rely exclusively on the huge data sets they collect about users. The more detailed and accurate the data a company has about its users, the more valuable the company is considered. No wonder that these companies are often the same companies that offer these services for free. This gives them an opportunity to collect more accurate location information. Research community in the location privacy protection area had to reciprocate by modeling an adversary that could be the service provider itself. To further drive this point, we show that a well-equipped service provider can infer user\u27s location even if the location information is not directly available by using other information he collects about the user. There is no dearth of proposals of several protocols and algorithms that protect location privacy. A lot of these earlier proposals require a trusted third party to play as an intermediary between the service provider and the user. These protocols use anonymization and/or obfuscation techniques to protect user\u27s identity and/or location. This requirement of trusted third parties comes with its own complications and risks and makes these proposals impractical in real life scenarios. Thus it is preferable that protocols do not require a trusted third party. We look at existing proposals in the area of private information retrieval. We present a brief survey of several proposals in the literature and implement two representative algorithms. We run experiments using different sizes of databases to ascertain their practicability and performance features. We show that private information retrieval based protocols still have long ways to go before they become practical enough for local search applications. We propose location privacy preserving mechanisms that take advantage of the processing power of modern mobile devices and provide configurable levels of location privacy. We propose these techniques both in the single query scenario and multiple query scenario. In single query scenario, the user issues a query to the server and obtains the answer. In the multiple query scenario, the user keeps sending queries as she moves about in the area of interest. We show that the multiple query scenario increases the accuracy of adversary\u27s determination of user\u27s location, and hence improvements are needed to cope with this situation. So, we propose an extension of the single query scenario that addresses this riskier multiple query scenario, still maintaining the practicability and acceptable performance when implemented on a modern mobile device. Later we propose a technique based on differential privacy that is inspired by differential privacy in statistical databases. All three mechanisms proposed by us are implemented in realistic hardware or simulators, run against simulated but real life data and their characteristics ascertained to show that they are practical and ready for adaptation. This dissertation study the privacy issues for location-based services in mobile environment and proposes a set of new techniques that eliminate the need for a trusted third party by implementing efficient algorithms on modern mobile hardware