15 research outputs found

    CGST: Provably Secure Lightweight Certificateless Group Signcryption Technique Based on Fractional Chaotic Maps

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    In recent years, there has been a lot of research interest in analyzing chaotic constructions and their associated cryptographic structures. Compared with the essential combination of encryption and signature, the signcryption scheme has a more realistic solution for achieving message confidentiality and authentication simultaneously. However, the security of a signcryption scheme is questionable when deployed in modern safety-critical systems, especially as billions of sensitive user information is transmitted over open communication channels. In order to address this problem, a lightweight, provably secure certificateless technique that uses Fractional Chaotic Maps (FCM) for group-oriented signcryption (CGST) is proposed. The main feature of the CGST-FCM technique is that any group signcrypter may encrypt data/information with the group manager (GM) and have it sent to the verifier seamlessly. This implies the legitimacy of the signcrypted information/data is verifiable using the public conditions of the group, but they cannot link it to the conforming signcrypter. In this scenario, valid signcrypted information/data cannot be produced by the GM or any signcrypter in that category alone. However, the GM is allowed to reveal the identity of the signcrypter when there is a legal conflict to restrict repudiation of the signature. Generally, the CGST-FCM technique is protected from the indistinguishably chosen ciphertext attack (IND-CCA). Additionally, the computationally difficult Diffie-Hellman (DH) problems have been used to build unlinkability, untraceability, unforgeability, and robustness of the projected CGST-FCM scheme. Finally, the security investigation of the presented CGST-FCM technique shows appreciable consistency and high efficiency when applied in real-time security applications

    Research on security and privacy in vehicular ad hoc networks

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    Los sistemas de redes ad hoc vehiculares (VANET) tienen como objetivo proporcionar una plataforma para diversas aplicaciones que pueden mejorar la seguridad vial, la eficiencia del tráfico, la asistencia a la conducción, la regulación del transporte, etc. o que pueden proveer de una mejor información y entretenimiento a los usuarios de los vehículos. Actualmente se está llevando a cabo un gran esfuerzo industrial y de investigación para desarrollar un mercado que se estima alcance en un futuro varios miles de millones de euros. Mientras que los enormes beneficios que se esperan de las comunicaciones vehiculares y el gran número de vehículos son los puntos fuertes de las VANET, su principal debilidad es la vulnerabilidad a los ataques contra la seguridad y la privacidad.En esta tesis proponemos cuatro protocolos para conseguir comunicaciones seguras entre vehículos. En nuestra primera propuesta empleamos a todas las unidades en carretera (RSU) para mantener y gestionar un grupo en tiempo real dentro de su rango de comunicación. Los vehículos que entren al grupo de forma anónima pueden emitir mensajes vehículo a vehículo (V2V) que inmediatamente pueden ser verificados por los vehículos del mismo grupo (y grupos de vecinos). Sin embargo, en la primera fase del despliegue de este sistema las RSU pueden no estar bien distribuídas. Consecuentemente, se propone un conjunto de mecanismos para hacer frente a la seguridad, privacidad y los requisitos de gestión de una VANET a gran escala sin la suposición de que las RSU estén densamente distribuidas. La tercera propuesta se centra principalmente en la compresión de las evidencias criptográficas que nos permitirán demostrar, por ejemplo, quien era el culpable en caso de accidente. Por último, investigamos los requisitos de seguridad de los sistemas basados en localización (LBS) sobre VANETs y proponemos un nuevo esquema para la preservación de la privacidad de la localización en estos sistemas sobre dichas redes.Vehicular ad hoc network (VANET) systems aim at providing a platform for various applications that can improve traffic safety and efficiency, driver assistance, transportation regulation, infotainment, etc. There is substantial research and industrial effort to develop this market. It is estimated that the market for vehicular communications will reach several billion euros. While the tremendous benefits expected from vehicular communications and the huge number of vehicles are strong points of VANETs, their weakness is vulnerability to attacks against security and privacy.In this thesis, we propose four protocols for secure vehicle communications. In our first proposal, we employ each road-side unit (RSU) to maintain and manage an on-the-fly group within its communication range. Vehicles entering the group can anonymously broadcast vehicle-to-vehicle (V2V) messages, which can be instantly verified by the vehicles in the same group (and neighbor groups). However, at the early stage of VANET deployment, the RSUs may not be well distributed. We then propose a set of mechanisms to address the security, privacy, and management requirements of a large-scale VANET without the assumption of densely distributed RSUs. The third proposal is mainly focused on compressing cryptographic witnesses in VANETs. Finally, we investigate the security requirements of LBS in VANETs and propose a new privacy-preserving LBS scheme for those networks

    Revisiting the Feasibility of Public Key Cryptography in Light of IIoT Communications

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    Digital certificates are regarded as the most secure and scalable way of implementing authentication services in the Internet today. They are used by most popular security protocols, including Transport Layer Security (TLS) and Datagram Transport Layer Security (DTLS). The lifecycle management of digital certificates relies on centralized Certification Authority (CA)-based Public Key Infrastructures (PKIs). However, the implementation of PKIs and certificate lifecycle management procedures in Industrial Internet of Things (IIoT) environments presents some challenges, mainly due to the high resource consumption that they imply and the lack of trust in the centralized CAs. This paper identifies and describes the main challenges to implement certificate-based public key cryptography in IIoT environments and it surveys the alternative approaches proposed so far in the literature to address these challenges. Most proposals rely on the introduction of a Trusted Third Party to aid the IIoT devices in tasks that exceed their capacity. The proposed alternatives are complementary and their application depends on the specific challenge to solve, the application scenario, and the capacities of the involved IIoT devices. This paper revisits all these alternatives in light of industrial communication models, identifying their strengths and weaknesses, and providing an in-depth comparative analysis.This work was financially supported by the European commission through ECSEL-JU 2018 program under the COMP4DRONES project (grant agreement N∘ 826610), with national financing from France, Spain, Italy, Netherlands, Austria, Czech, Belgium and Latvia. It was also partially supported by the Ayudas Cervera para Centros Tecnológicos grant of the Spanish Centre for the Development of Industrial Technology (CDTI) under the project EGIDA (CER-20191012), and in part by the Department of Economic Development and Competitiveness of the Basque Government through the project TRUSTIND—Creating Trust in the Industrial Digital Transformation (KK-2020/00054)

    A patient agent controlled customized blockchain based framework for internet of things

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    Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph

    Searchable Encryption for Cloud and Distributed Systems

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    The vast development in information and communication technologies has spawned many new computing and storage architectures in the last two decades. Famous for its powerful computation ability and massive storage capacity, cloud services, including storage and computing, replace personal computers and software systems in many industrial applications. Another famous and influential computing and storage architecture is the distributed system, which refers to an array of machines or components geographically dispersed but jointly contributes to a common task, bringing premium scalability, reliability, and efficiency. Recently, the distributed cloud concept has also been proposed to benefit both cloud and distributed computing. Despite the benefits of these new technologies, data security and privacy are among the main concerns that hinder the wide adoption of these attractive architectures since data and computation are not under the control of the end-users in such systems. The traditional security mechanisms, e.g., encryption, cannot fit these new architectures since they would disable the fast access and retrieval of remote storage servers. Thus, an urgent question turns to be how to enable refined and efficient data retrieval on encrypted data among numerous records (i.e., searchable encryption) in the cloud and distributed systems, which forms the topic of this thesis. Searchable encryption technologies can be divided into Searchable Symmetric Encryption (SSE) and Public-key Encryption with Keyword Search (PEKS). The intrinsical symmetric key hinders data sharing since it is problematic and insecure to reveal one’s key to others. However, SSE outperforms PEKS due to its premium efficiency and is thus is prefered in a number of keyword search applications. Then multi-user SSE with rigorous and fine access control undoubtedly renders a satisfactory solution of both efficiency and security, which is the first problem worthy of our much attention. Second, functions and versatility play an essential role in a cloud storage application but it is still tricky to realize keyword search and deduplication in the cloud simultaneously. Large-scale data usually renders significant data redundancy and saving cloud storage resources turns to be inevitable. Existing schemes only facilitate data retrieval due to keywords but rarely consider other demands like deduplication. To be noted, trivially and hastily affiliating a separate deduplication scheme to the searchable encryption leads to disordered system architecture and security threats. Therefore, attention should be paid to versatile solutions supporting both keyword search and deduplication in the cloud. The third problem to be addressed is implementing multi-reader access for PEKS. As we know, PEKS was born to support multi-writers but enabling multi-readers in PEKS is challenging. Repeatedly encrypting the same keyword with different readers’ keys is not an elegant solution. In addition to keyword privacy, user anonymity coming with a multi-reader setting should also be formulated and preserved. Last but not least, existing schemes targeting centralized storage have not taken full advantage of distributed computation, which is considerable efficiency and fast response. Specifically, all testing tasks between searchable ciphertexts and trapdoor/token are fully undertaken by the only centralized cloud server, resulting in a busy system and slow response. With the help of distributed techniques, we may now look forward to a new turnaround, i.e., multiple servers jointly work to perform the testing with better efficiency and scalability. Then the intractable multi-writer/multi-reader mode supporting multi-keyword queries may also come true as a by-product. This thesis investigates searchable encryption technologies in cloud storage and distributed systems and spares effort to address the problems mentioned above. Our first work can be classified into SSE. We formulate the Multi-user Verifiable Searchable Symmetric Encryption (MVSSE) and propose a concrete scheme for multi-user access. It not only offers multi-user access and verifiability but also supports extension on updates as well as a non-single keyword index. Moreover, revocable access control is obtained that the search authority is validated each time a query is launched, different from existing mechanisms that once the search authority is granted, users can search forever. We give simulation-based proof, demonstrating our proposal possesses Universally Composable (UC)-security. Second, we come up with a redundancy elimination solution on top of searchable encryption. Following the keyword comparison approach of SSE, we formulate a hybrid primitive called Message-Locked Searchable Encryption (MLSE) derived in the way of SSE’s keyword search supporting keyword search and deduplication and present a concrete construction that enables multi-keyword query and negative keyword query as well as deduplication at a considerable small cost, i.e., the tokens are used for both search and deduplication. And it can further support Proof of Storage (PoS), testifying the content integrity in cloud storage. The semantic security is proved in Random Oracle Model using the game-based methodology. Third, as the branch of PEKS, the Broadcast Authenticated Encryption with Keyword Search (BAEKS) is proposed to bridge the gap of multi-reader access for PEKS, followed by a scheme. It not only resists Keyword Guessing Attacks (KGA) but also fills in the blank of anonymity. The scheme is proved secure under Decisional Bilinear Diffie-Hellman (DBDH) assumption in the Random Oracle Model. For distributed systems, we present a Searchable Encryption based on Efficient Privacy-preserving Outsourced calculation framework with Multiple keys (SE-EPOM) enjoying desirable features, which can be classified into PEKS. Instead of merely deploying a single server, multiple servers are employed to execute the test algorithm in our scheme jointly. The refined search, i.e., multi-keyword query, data confidentiality, and search pattern hiding, are realized. Besides, the multi-writer/multi-reader mode comes true. It is shown that under the distributed circumstance, much efficiency can be substantially achieved by our construction. With simulation-based proof, the security of our scheme is elaborated. All constructions proposed in this thesis are formally proven according to their corresponding security definitions and requirements. In addition, for each cryptographic primitive designed in this thesis, concrete schemes are initiated to demonstrate the availability and practicality of our proposal

    Secure and Privacy-Preserving Vehicular Communications

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    Road safety has been drawing increasing attention in the public, and has been subject to extensive efforts from both industry and academia in mitigating the impact of traffic accidents. Recent advances in wireless technology promise new approaches to facilitating road safety and traffic management, where each vehicle (or referred to as On-board unit (OBU)) is allowed to communicate with each other as well as with Roadside units (RSUs), which are located in some critical sections of the road, such as a traffic light, an intersection, and a stop sign. With the OBUs and RSUs, a self-organized network, called Vehicular Ad Hoc Network (VANET), can thus be formed. Unfortunately, VANETs have faced various security threats and privacy concerns, which would jeopardize the public safety and become the main barrier to the acceptance of such a new technology. Hence, addressing security and privacy issues is a prerequisite for a market-ready VANET. Although many studies have recently addressed a significant amount of efforts in solving the related problems, few of the studies has taken the scalability issues into consideration. When the traffic density is getting large, a vehicle may become unable to verify the authenticity of the messages sent by its neighbors in a timely manner, which may result in message loss so that public safety may be at risk. Communication overhead is another issue that has not been well addressed in previously reported studies. Many efforts have been made in recent years in achieving efficient broadcast source authentication and data integrity by using fast symmetric cryptography. However, the dynamic nature of VANETs makes it very challenging in the applicability of these symmetric cryptography-based protocols. In this research, we propose a novel Secure and Efficient RSU-aided Privacy Preservation Protocol, called SERP^3, in order to achieve efficient secure and privacy-preserving Inter-Vehicle Communications (IVCs). With the commitments of one-way key chains distributed to vehicles by RSUs, a vehicle can effectively authenticate any received message from vehicles nearby even in the presence of frequent change of its neighborship. Compared with previously reported public key infrastructure (PKI)-based packet authentication protocols for security and privacy, the proposed protocol not only retains the security and privacy preservation properties, but also has less packet loss ratio and lower communication overhead, especially when the road traffic is heavy. Therefore, the protocol solves the scalability and communication overhead issues, while maintaining acceptable packet latency. However, RSU may not exist in some situations, for example, in the early stage deployment phase of VANET, where unfortunately, SERP^3 is not suitable. Thus, we propose a complementary Efficient and Cooperative Message Validation Protocol, called ECMVP, where each vehicle probabilistically validates a certain percentage of its received messages based on its own computing capacity and then reports any invalid messages detected by it. Since the ultimate goal of designing VANET is to develop vehicle safety/non-safety related applications to improve road safety and facilitate traffic management, two vehicle applications are further proposed in the research to exploit the advantages of vehicular communications. First, a novel vehicle safety application for achieving a secure road traffic control system in VANETs is developed. The proposed application helps circumvent vehicles safely and securely through the areas in any abnormal situation, such as a car crash scene, while ensuring the security and privacy of the drivers from various threats. It not only enhances traveler safety but also minimizes capacity restrictions due to any unusual situation. Second, the dissertation investigates a novel mobile payment system for highway toll collection by way of vehicular communications, which addresses all the issues in the currently existing toll collection technologies

    Security and Privacy Preservation in Mobile Crowdsensing

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    Mobile crowdsensing (MCS) is a compelling paradigm that enables a crowd of individuals to cooperatively collect and share data to measure phenomena or record events of common interest using their mobile devices. Pairing with inherent mobility and intelligence, mobile users can collect, produce and upload large amounts of data to service providers based on crowdsensing tasks released by customers, ranging from general information, such as temperature, air quality and traffic condition, to more specialized data, such as recommended places, health condition and voting intentions. Compared with traditional sensor networks, MCS can support large-scale sensing applications, improve sensing data trustworthiness and reduce the cost on deploying expensive hardware or software to acquire high-quality data. Despite the appealing benefits, however, MCS is also confronted with a variety of security and privacy threats, which would impede its rapid development. Due to their own incentives and vulnerabilities of service providers, data security and user privacy are being put at risk. The corruption of sensing reports may directly affect crowdsensing results, and thereby mislead customers to make irrational decisions. Moreover, the content of crowdsensing tasks may expose the intention of customers, and the sensing reports might inadvertently reveal sensitive information about mobile users. Data encryption and anonymization techniques can provide straightforward solutions for data security and user privacy, but there are several issues, which are of significantly importance to make MCS practical. First of all, to enhance data trustworthiness, service providers need to recruit mobile users based on their personal information, such as preferences, mobility pattern and reputation, resulting in the privacy exposure to service providers. Secondly, it is inevitable to have replicate data in crowdsensing reports, which may possess large communication bandwidth, but traditional data encryption makes replicate data detection and deletion challenging. Thirdly, crowdsensed data analysis is essential to generate crowdsensing reports in MCS, but the correctness of crowdsensing results in the absence of malicious mobile users and service providers become a huge concern for customers. Finally yet importantly, even if user privacy is preserved during task allocation and data collection, it may still be exposed during reward distribution. It further discourage mobile users from task participation. In this thesis, we explore the approaches to resolve these challenges in MCS. Based on the architecture of MCS, we conduct our research with the focus on security and privacy protection without sacrificing data quality and users' enthusiasm. Specifically, the main contributions are, i) to enable privacy preservation and task allocation, we propose SPOON, a strong privacy-preserving mobile crowdsensing scheme supporting accurate task allocation. In SPOON, the service provider recruits mobile users based on their locations, and selects proper sensing reports according to their trust levels without invading user privacy. By utilizing the blind signature, sensing tasks are protected and reports are anonymized. In addition, a privacy-preserving credit management mechanism is introduced to achieve decentralized trust management and secure credit proof for mobile users; ii) to improve communication efficiency while guaranteeing data confidentiality, we propose a fog-assisted secure data deduplication scheme, in which a BLS-oblivious pseudo-random function is developed to enable fog nodes to detect and delete replicate data in sensing reports without exposing the content of reports. Considering the privacy leakages of mobile users who report the same data, the blind signature is utilized to hide users' identities, and chameleon hash function is leveraged to achieve contribution claim and reward retrieval for anonymous greedy mobile users; iii) to achieve data statistics with privacy preservation, we propose a privacy-preserving data statistics scheme to achieve end-to-end security and integrity protection, while enabling the aggregation of the collected data from multiple sources. The correctness verification is supported to prevent the corruption of the aggregate results during data transmission based on the homomorphic authenticator and the proxy re-signature. A privacy-preserving verifiable linear statistics mechanism is developed to realize the linear aggregation of multiple crowdsensed data from a same device and the verification on the correctness of aggregate results; and iv) to encourage mobile users to participating in sensing tasks, we propose a dual-anonymous reward distribution scheme to offer the incentive for mobile users and privacy protection for both customers and mobile users in MCS. Based on the dividable cash, a new reward sharing incentive mechanism is developed to encourage mobile users to participating in sensing tasks, and the randomization technique is leveraged to protect the identities of customers and mobile users during reward claim, distribution and deposit

    Data Service Outsourcing and Privacy Protection in Mobile Internet

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    Mobile Internet data have the characteristics of large scale, variety of patterns, and complex association. On the one hand, it needs efficient data processing model to provide support for data services, and on the other hand, it needs certain computing resources to provide data security services. Due to the limited resources of mobile terminals, it is impossible to complete large-scale data computation and storage. However, outsourcing to third parties may cause some risks in user privacy protection. This monography focuses on key technologies of data service outsourcing and privacy protection, including the existing methods of data analysis and processing, the fine-grained data access control through effective user privacy protection mechanism, and the data sharing in the mobile Internet
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