Implementation of a Strongly Robust Identity-Based Encryption Scheme over Type-3 Pairings

Identity-based encryption (IBE) is a powerful mechanism for maintaining security. However, systems based on IBE are unpopular when compared with those of the public-key encryption (PKE). In our opinion, one of the reasons is a gap between theory and practice. For example, a generic transformation of weakly/strongly robust IBE from any IBE has been proposed by Abdalla et al., no robust IBE scheme is explicitly given. This means that, theoretically, anyone can construct a weakly/strongly robust IBE scheme by employing this transformation. However, this seems not easily applicable to non-cryptographers. In this paper, we first introduce the Gentry IBE scheme constructed over Type-3 pairings by employing the transformation proposed by Abe et al., and second we explicitly give strongly/weakly robust Gentry IBE schemes by employing the Abdalla et al. transformation. Finally, we show its implementation result and show that we can add strong robustness to the Gentry IBE scheme with a very few additional costs. We employ the mcl library to support a Barreto-Naehrig curve defined over the 462-bit prime. The encryption requires about 5 ms, whereas the decryption requires about 9 ms

Secure Protocols for Privacy-preserving Data Outsourcing, Integration, and Auditing

As the amount of data available from a wide range of domains has increased tremendously in recent years, the demand for data sharing and integration has also risen. The cloud computing paradigm provides great flexibility to data owners with respect to computation and storage capabilities, which makes it a suitable platform for them to share their data. Outsourcing person-specific data to the cloud, however, imposes serious concerns about the confidentiality of the outsourced data, the privacy of the individuals referenced in the data, as well as the confidentiality of the queries processed over the data. Data integration is another form of data sharing, where data owners jointly perform the integration process, and the resulting dataset is shared between them. Integrating related data from different sources enables individuals, businesses, organizations and government agencies to perform better data analysis, make better informed decisions, and provide better services. Designing distributed, secure, and privacy-preserving protocols for integrating person-specific data, however, poses several challenges, including how to prevent each party from inferring sensitive information about individuals during the execution of the protocol, how to guarantee an effective level of privacy on the released data while maintaining utility for data mining, and how to support public auditing such that anyone at any time can verify that the integration was executed correctly and no participants deviated from the protocol. In this thesis, we address the aforementioned concerns by presenting secure protocols for privacy-preserving data outsourcing, integration and auditing. First, we propose a secure cloud-based data outsourcing and query processing framework that simultaneously preserves the confidentiality of the data and the query requests, while providing differential privacy guarantees on the query results. Second, we propose a publicly verifiable protocol for integrating person-specific data from multiple data owners, while providing differential privacy guarantees and maintaining an effective level of utility on the released data for the purpose of data mining. Next, we propose a privacy-preserving multi-party protocol for high-dimensional data mashup with guaranteed LKC-privacy on the output data. Finally, we apply the theory to the real world problem of solvency in Bitcoin. More specifically, we propose a privacy-preserving and publicly verifiable cryptographic proof of solvency scheme for Bitcoin exchanges such that no information is revealed about the exchange's customer holdings, the value of the exchange's total holdings is kept secret, and multiple exchanges performing the same proof of solvency can contemporaneously prove they are not colluding

Secure data sharing in cloud computing: a comprehensive review

Cloud Computing is an emerging technology, which relies on sharing computing resources. Sharing of data in the group is not secure as the cloud provider cannot be trusted. The fundamental difficulties in distributed computing of cloud suppliers is Data Security, Sharing, Resource scheduling and Energy consumption. Key-Aggregate cryptosystem used to secure private/public data in the cloud. This key is consistent size aggregate for adaptable decisions of ciphertext in cloud storage. Virtual Machines (VMs) provisioning is effectively empowered the cloud suppliers to effectively use their accessible resources and get higher benefits. The most effective method to share information resources among the individuals from the group in distributed storage is secure, flexible and efficient. Any data stored in different cloud data centers are corrupted, recovery using regenerative coding. Security is provided many techniques like Forward security, backward security, Key-Aggregate cryptosystem, Encryption and Re-encryption etc. The energy is reduced using Energy-Efficient Virtual Machines Scheduling in Multi-Tenant Data Centers

Secure Data Sharing in Cloud Computing: A Comprehensive Review

Cloud Computing is an emerging technology, which relies on sharing computing resources. Sharing of data in the group is not secure as the cloud provider cannot be trusted. The fundamental difficulties in distributed computing of cloud suppliers is Data Security, Sharing, Resource scheduling and Energy consumption. Key-Aggregate cryptosystem used to secure private/public data in the cloud. This key is consistent size aggregate for adaptable decisions of ciphertext in cloud storage. Virtual Machines (VMs) provisioning is effectively empowered the cloud suppliers to effectively use their accessible resources and get higher benefits. The most effective method to share information resources among the individuals from the group in distributed storage is secure, flexible and efficient. Any data stored in different cloud data centers are corrupted, recovery using regenerative coding. Security is provided many techniques like Forward security, backward security, Key-Aggregate cryptosystem, Encryption and Re-encryption etc. The energy is reduced using Energy-Efficient Virtual Machines Scheduling in Multi-Tenant Data Centers

Post-Quantum Era Privacy Protection for Intelligent Infrastructures

As we move into a new decade, the global world of Intelligent Infrastructure (II) services integrated into the Internet of Things (IoT) are at the forefront of technological advancements. With billions of connected devices spanning continents through interconnected networks, security and privacy protection techniques for the emerging II services become a paramount concern. In this paper, an up-to-date privacy method mapping and relevant use cases are surveyed for II services. Particularly, we emphasize on post-quantum cryptography techniques that may (or must when quantum computers become a reality) be used in the future through concrete products, pilots, and projects. The topics presented in this paper are of utmost importance as (1) several recent regulations such as Europe's General Data Protection Regulation (GDPR) have given privacy a significant place in digital society, and (2) the increase of IoT/II applications and digital services with growing data collection capabilities are introducing new threats and risks on citizens' privacy. This in-depth survey begins with an overview of security and privacy threats in IoT/IIs. Next, we summarize some selected Privacy-Enhancing Technologies (PETs) suitable for privacy-concerned II services, and then map recent PET schemes based on post-quantum cryptographic primitives which are capable of withstanding quantum computing attacks. This paper also overviews how PETs can be deployed in practical use cases in the scope of IoT/IIs, and maps some current projects, pilots, and products that deal with PETs. A practical case study on the Internet of Vehicles (IoV) is presented to demonstrate how PETs can be applied in reality. Finally, we discuss the main challenges with respect to current PETs and highlight some future directions for developing their post-quantum counterparts

Cryptographic Techniques for Securing Data in the Cloud

El paradigma de la computació al núvol proporciona accés remot a potents infraestructures a cost reduït. Tot i que l’adopció del núvol ofereix nombrosos beneficis, la migració de dades sol requerir un alt nivell de confiança en el proveïdor de serveis i introdueix problemes de privacitat. En aquesta tesi es dissenyen tècniques per a permetre a usuaris del núvol protegir un conjunt de dades externalitzades. Les solucions proposades emanen del projecte H2020 de la Comissió Europea “CLARUS: User-Centered Privacy and Security in the Cloud”. Els problemes explorats són la cerca sobre dades xifrades, la delegació de càlculs d’interpolació, els esquemes de compartició de secrets i la partició de dades. Primerament, s’estudia el problema de la cerca sobre dades xifrades mitjançant els esquemes de xifrat cercable simètric (SSE), i es desenvolupen tècniques que permeten consultes per rangs dos-dimensionals a SSE. També es tracta el mateix problema utilitzant esquemes de xifrat cercable de clau pública (PEKS), i es presenten esquemes PEKS que permeten consultes conjuntives i de subconjunt. En aquesta tesi també s’aborda la delegació privada de computacions Kriging. Kriging és un algoritme d’interpolació espaial dissenyat per a aplicacions geo-estadístiques. Es descriu un mètode per a delegar interpolacions Kriging de forma privada utilitzant xifrat homomòrfic. Els esquemes de compartició de secrets són una primitiva fonamental en criptografia, utilitzada a diverses solucions orientades al núvol. Una de les mesures d’eficiència relacionades més importants és la taxa d’informació òptima. Atès que calcular aquesta taxa és generalment difícil, s’obtenen propietats que faciliten la seva descripció. Finalment, es tracta el camp de la partició de dades per a la protecció de la privacitat. Aquesta tècnica protegeix la privacitat de les dades emmagatzemant diversos fragments a diferents ubicacions. Aquí s’analitza aquest problema des d’un punt de vista combinatori, fitant el nombre de fragments i proposant diversos algoritmes.El paradigma de la computación en la nube proporciona acceso remoto a potentes infraestructuras a coste reducido. Aunque la adopción de la nube ofrece numerosos beneficios, la migración de datos suele requerir un alto nivel de confianza en el proveedor de servicios e introduce problemas de privacidad. En esta tesis se diseñan técnicas para permitir a usuarios de la nube proteger un conjunto de datos externalizados. Las soluciones propuestas emanan del proyecto H2020 de la Comisión Europea “CLARUS: User-Centered Privacy and Security in the Cloud”. Los problemas explorados son la búsqueda sobre datos cifrados, la delegación de cálculos de interpolación, los esquemas de compartición de secretos y la partición de datos. Primeramente, se estudia el problema de la búsqueda sobre datos cifrados mediante los esquemas de cifrado simétrico buscable (SSE), y se desarrollan técnicas para permitir consultas por rangos dos-dimensionales en SSE. También se trata el mismo problema utilizando esquemas de cifrado buscable de llave pública (PEKS), y se presentan esquemas que permiten consultas conyuntivas y de subconjunto. Adicionalmente, se aborda la delegación privada de computaciones Kriging. Kriging es un algoritmo de interpolación espacial diseñado para aplicaciones geo-estadísticas. Se describe un método para delegar interpolaciones Kriging privadamente utilizando técnicas de cifrado homomórfico. Los esquemas de compartición de secretos son una primitiva fundamental en criptografía, utilizada en varias soluciones orientadas a la nube. Una de las medidas de eficiencia más importantes es la tasa de información óptima. Dado que calcular esta tasa es generalmente difícil, se obtienen propiedades que facilitan su descripción. Por último, se trata el campo de la partición de datos para la protección de la privacidad. Esta técnica protege la privacidad de los datos almacenando varios fragmentos en distintas ubicaciones. Analizamos este problema desde un punto de vista combinatorio, acotando el número de fragmentos y proponiendo varios algoritmos.The cloud computing paradigm provides users with remote access to scalable and powerful infrastructures at a very low cost. While the adoption of cloud computing yields a wide array of benefits, the act of migrating to the cloud usually requires a high level of trust in the cloud service provider and introduces several security and privacy concerns. This thesis aims at designing user-centered techniques to secure an outsourced data set in cloud computing. The proposed solutions stem from the European Commission H2020 project “CLARUS: User-Centered Privacy and Security in the Cloud”. The explored problems are searching over encrypted data, outsourcing Kriging interpolation computations, secret sharing and data splitting. Firstly, the problem of searching over encrypted data is studied using symmetric searchable encryption (SSE) schemes, and techniques are developed to enable efficient two-dimensional range queries in SSE. This problem is also studied through public key encryption with keyword search (PEKS) schemes, efficient PEKS schemes achieving conjunctive and subset queries are proposed. This thesis also aims at securely outsourcing Kriging computations. Kriging is a spatial interpolation algorithm designed for geo-statistical applications. A method to privately outsource Kriging interpolation is presented, based in homomorphic encryption. Secret sharing is a fundamental primitive in cryptography, used in many cloud-oriented techniques. One of the most important efficiency measures in secret sharing is the optimal information ratio. Since computing the optimal information ratio of an access structure is generally hard, properties are obtained to facilitate its description. Finally, this thesis tackles the privacy-preserving data splitting technique, which aims at protecting data privacy by storing different fragments of data at different locations. Here, the data splitting problem is analyzed from a combinatorial point of view, bounding the number of fragments and proposing various algorithms to split the data

Securing clouds using cryptography and traffic classification

Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. Over the last decade, cloud computing has gained popularity and wide acceptance, especially within the health sector where it offers several advantages such as low costs, flexible processes, and access from anywhere. Although cloud computing is widely used in the health sector, numerous issues remain unresolved. Several studies have attempted to review the state of the art in eHealth cloud privacy and security however, some of these studies are outdated or do not cover certain vital features of cloud security and privacy such as access control, revocation and data recovery plans. This study targets some of these problems and proposes protocols, algorithms and approaches to enhance the security and privacy of cloud computing with particular reference to eHealth clouds. Chapter 2 presents an overview and evaluation of the state of the art in eHealth security and privacy. Chapter 3 introduces different research methods and describes the research design methodology and processes used to carry out the research objectives. Of particular importance are authenticated key exchange and block cipher modes. In Chapter 4, a three-party password-based authenticated key exchange (TPAKE) protocol is presented and its security analysed. The proposed TPAKE protocol shares no plaintext data; all data shared between the parties are either hashed or encrypted. Using the random oracle model (ROM), the security of the proposed TPAKE protocol is formally proven based on the computational Diffie-Hellman (CDH) assumption. Furthermore, the analysis included in this chapter shows that the proposed protocol can ensure perfect forward secrecy and resist many kinds of common attacks such as man-in-the-middle attacks, online and offline dictionary attacks, replay attacks and known key attacks. Chapter 5 proposes a parallel block cipher (PBC) mode in which blocks of cipher are processed in parallel. The results of speed performance tests for this PBC mode in various settings are presented and compared with the standard CBC mode. Compared to the CBC mode, the PBC mode is shown to give execution time savings of 60%. Furthermore, in addition to encryption based on AES 128, the hash value of the data file can be utilised to provide an integrity check. As a result, the PBC mode has a better speed performance while retaining the confidentiality and security provided by the CBC mode. Chapter 6 applies TPAKE and PBC to eHealth clouds. Related work on security, privacy preservation and disaster recovery are reviewed. Next, two approaches focusing on security preservation and privacy preservation, and a disaster recovery plan are proposed. The security preservation approach is a robust means of ensuring the security and integrity of electronic health records and is based on the PBC mode, while the privacy preservation approach is an efficient authentication method which protects the privacy of personal health records and is based on the TPAKE protocol. A discussion about how these integrated approaches and the disaster recovery plan can ensure the reliability and security of cloud projects follows. Distributed denial of service (DDoS) attacks are the second most common cybercrime attacks after information theft. The timely detection and prevention of such attacks in cloud projects are therefore vital, especially for eHealth clouds. Chapter 7 presents a new classification system for detecting and preventing DDoS TCP flood attacks (CS_DDoS) for public clouds, particularly in an eHealth cloud environment. The proposed CS_DDoS system offers a solution for securing stored records by classifying incoming packets and making a decision based on these classification results. During the detection phase, CS_DDOS identifies and determines whether a packet is normal or from an attacker. During the prevention phase, packets classified as malicious are denied access to the cloud service, and the source IP is blacklisted. The performance of the CS_DDoS system is compared using four different classifiers: a least-squares support vector machine (LS-SVM), naïve Bayes, K-nearest-neighbour, and multilayer perceptron. The results show that CS_DDoS yields the best performance when the LS-SVM classifier is used. This combination can detect DDoS TCP flood attacks with an accuracy of approximately 97% and a Kappa coefficient of 0.89 when under attack from a single source, and 94% accuracy and a Kappa coefficient of 0.9 when under attack from multiple attackers. These results are then discussed in terms of the accuracy and time complexity, and are validated using a k-fold cross-validation model. Finally, a method to mitigate DoS attacks in the cloud and reduce excessive energy consumption through managing and limiting certain flows of packets is proposed. Instead of a system shutdown, the proposed method ensures the availability of service. The proposed method manages the incoming packets more effectively by dropping packets from the most frequent requesting sources. This method can process 98.4% of the accepted packets during an attack. Practicality and effectiveness are essential requirements of methods for preserving the privacy and security of data in clouds. The proposed methods successfully secure cloud projects and ensure the availability of services in an efficient way

NEW SECURE SOLUTIONS FOR PRIVACY AND ACCESS CONTROL IN HEALTH INFORMATION EXCHANGE

In the current digital age, almost every healthcare organization (HCO) has moved from storing patient health records on paper to storing them electronically. Health Information Exchange (HIE) is the ability to share (or transfer) patients’ health information between different HCOs while maintaining national security standards like the Health Insurance Portability and Accountability Act (HIPAA) of 1996. Over the past few years, research has been conducted to develop privacy and access control frameworks for HIE systems. The goal of this dissertation is to address the privacy and access control concerns by building practical and efficient HIE frameworks to secure the sharing of patients’ health information. The first solution allows secure HIE among different healthcare providers while focusing primarily on the privacy of patients’ information. It allows patients to authorize a certain type of health information to be retrieved, which helps prevent any unintentional leakage of information. The privacy solution also provides healthcare providers with the capability of mutual authentication and patient authentication. It also ensures the integrity and auditability of health information being exchanged. The security and performance study for the first protocol shows that it is efficient for the purpose of HIE and offers a high level of security for such exchanges. The second framework presents a new cloud-based protocol for access control to facilitate HIE across different HCOs, employing a trapdoor hash-based proxy signature in a novel manner to enable secure (authenticated and authorized) on-demand access to patient records. The proposed proxy signature-based scheme provides an explicit mechanism for patients to authorize the sharing of specific medical information with specific HCOs, which helps prevent any undesired or unintentional leakage of health information. The scheme also ensures that such authorizations are authentic with respect to both the HCOs and the patient. Moreover, the use of proxy signatures simplifies security auditing and the ability to obtain support for investigations by providing non-repudiation. Formal definitions, security specifications, and a detailed theoretical analysis, including correctness, security, and performance of both frameworks are provided which demonstrate the improvements upon other existing HIE systems

New Security Definitions, Constructions and Applications of Proxy Re-Encryption

La externalización de la gestión de la información es una práctica cada vez más común, siendo la computación en la nube (en inglés, cloud computing) el paradigma más representativo. Sin embargo, este enfoque genera también preocupación con respecto a la seguridad y privacidad debido a la inherente pérdida del control sobre los datos. Las soluciones tradicionales, principalmente basadas en la aplicación de políticas y estrategias de control de acceso, solo reducen el problema a una cuestión de confianza, que puede romperse fácilmente por los proveedores de servicio, tanto de forma accidental como intencionada. Por lo tanto, proteger la información externalizada, y al mismo tiempo, reducir la confianza que es necesario establecer con los proveedores de servicio, se convierte en un objetivo inmediato. Las soluciones basadas en criptografía son un mecanismo crucial de cara a este fin. Esta tesis está dedicada al estudio de un criptosistema llamado recifrado delegado (en inglés, proxy re-encryption), que constituye una solución práctica a este problema, tanto desde el punto de vista funcional como de eficiencia. El recifrado delegado es un tipo de cifrado de clave pública que permite delegar en una entidad la capacidad de transformar textos cifrados de una clave pública a otra, sin que pueda obtener ninguna información sobre el mensaje subyacente. Desde un punto de vista funcional, el recifrado delegado puede verse como un medio de delegación segura de acceso a información cifrada, por lo que representa un candidato natural para construir mecanismos de control de acceso criptográficos. Aparte de esto, este tipo de cifrado es, en sí mismo, de gran interés teórico, ya que sus definiciones de seguridad deben balancear al mismo tiempo la seguridad de los textos cifrados con la posibilidad de transformarlos mediante el recifrado, lo que supone una estimulante dicotomía. Las contribuciones de esta tesis siguen un enfoque transversal, ya que van desde las propias definiciones de seguridad del recifrado delegado, hasta los detalles específicos de potenciales aplicaciones, pasando por construcciones concretas

Highly Scalable and Secure Mobile Applications in Cloud Computing Systems

Cloud computing provides scalable processing and storage resources that are hosted on a third-party provider to permit clients to economically meet real-time service demands. The confidentiality of client data outsourced to the cloud is a paramount concern since the provider cannot necessarily be trusted with read access to voluminous sensitive client data. A particular challenge of mobile cloud computing is that a cloud application may be accessed by a very large and dynamically changing population of mobile devices requiring access control. The thesis addresses the problems of achieving efficient and highly scalable key management for resource-constrained users of an untrusted cloud, and also of preserving the privacy of users. A model for key distribution is first proposed that is based on dynamic proxy re-encryption of data. Keys are managed inside the client domain for trust reasons, computationally-intensive re-encryption is performed by the cloud provider, and key distribution is minimized to conserve communication. A mechanism manages key evolution for a continuously changing user population. Next, a novel form of attribute-based encryption is proposed that authorizes users based on the satisfaction of required attributes. The greater computational load from cryptographic operations is performed by the cloud provider and a trusted manager rather than the mobile data owner. Furthermore, data re-encryption may be optionally performed by the cloud provider to reduce the expense of user revocation. Another key management scheme based on threshold cryptography is proposed where encrypted key shares are stored in the cloud, taking advantage of the scalability of storage in the cloud. The key share material erodes over time to allow user revocation to occur efficiently without additional coordination by the data owner; multiple classes of user privileges are also supported. Lastly, an alternative exists where cloud data is considered public knowledge, but the specific information queried by a user must be kept private. A technique is presented utilizing private information retrieval, where the query is performed in a computationally efficient manner without requiring a trusted third-party component. A cloaking mechanism increases the privacy of a mobile user while maintaining constant traffic cost