Secure data sharing in cloud and IoT by leveraging attribute-based encryption and blockchain

“Data sharing is very important to enable different types of cloud and IoT-based services. For example, organizations migrate their data to the cloud and share it with employees and customers in order to enjoy better fault-tolerance, high-availability, and scalability offered by the cloud. Wearable devices such as smart watch share user’s activity, location, and health data (e.g., heart rate, ECG) with the service provider for smart analytic. However, data can be sensitive, and the cloud and IoT service providers cannot be fully trusted with maintaining the security, privacy, and confidentiality of the data. Hence, new schemes and protocols are required to enable secure data sharing in the cloud and IoT. This work outlines our research contribution towards secure data sharing in the cloud and IoT. For secure data sharing in the cloud, this work proposes several novel attribute-based encryption schemes. The core contributions to this end are efficient revocation, prevention of collusion attacks, and multi-group support. On the other hand, for secure data sharing in IoT, a permissioned blockchain-based access control system has been proposed. The system can be used to enforce fine-grained access control on IoT data where the access control decision is made by the blockchain-based on the consensus of the participating nodes”--Abstract, page iv

Proxy Key Re-encapsulation Mechanism for Group Communications

Many practical applications use hybrid encryption mechanism to deal with large plaintext messages or real-time communication since the performance of the public key encryption scheme is poor. The key encapsulation is a crucial part in hybrid encryption mechanism, which allows a sender to generate a random session key and distribute it to recipient. In this paper we present a proxy key re-encapsulation scheme for group communication. The proxy in our scheme is allowed to transform the encapsulated message corresponding to group A\u27s public key into one that can be decapsulated by the member in group B. It can be used in cases when a group users need to perform sensitive operation without holding the necessary secret key

Privacy-enhancing distributed protocol for data aggregation based on blockchain and homomorphic encryption

The recent increase in reported incidents of security breaches compromising users' privacy call into question the current centralized model in which third-parties collect and control massive amounts of personal data. Blockchain has demonstrated that trusted and auditable computing is possible using a decentralized network of peers accompanied by a public ledger. Furthermore, Homomorphic Encryption (HE) guarantees confidentiality not only on the computation but also on the transmission, and storage processes. The synergy between Blockchain and HE is rapidly increasing in the computing environment. This research proposes a privacy-enhancing distributed and secure protocol for data aggregation backboned by Blockchain and HE technologies. Blockchain acts as a distributed ledger which facilitates efficient data aggregation through a Smart Contract. On the top, HE will be used for data encryption allowing private aggregation operations. The theoretical description, potential applications, a suggested implementation and a performance analysis are presented to validate the proposed solution.This work has been partially supported by the Basque Country Government under the ELKARTEK program, project TRUSTIND (KK- 2020/00054). It has also been partially supported by the H2020 TERMINET project (GA 957406)

Data security in cloud storage services

Cloud Computing is considered to be the next-generation architecture for ICT where it moves the application software and databases to the centralized large data centers. It aims to offer elastic IT services where clients can benefit from significant cost savings of the pay-per-use model and can easily scale up or down, and do not have to make large investments in new hardware. However, the management of the data and services in this cloud model is under the control of the provider. Consequently, the cloud clients have less control over their outsourced data and they have to trust cloud service provider to protect their data and infrastructure from both external and internal attacks. This is especially true with cloud storage services. Nowadays, users rely on cloud storage as it offers cheap and unlimited data storage that is available for use by multiple devices (e.g. smart phones, tablets, notebooks, etc.). Besides famous cloud storage providers, such as Amazon, Google, and Microsoft, more and more third-party cloud storage service providers are emerging. These services are dedicated to offering more accessible and user friendly storage services to cloud customers. Examples of these services include Dropbox, Box.net, Sparkleshare, UbuntuOne or JungleDisk. These cloud storage services deliver a very simple interface on top of the cloud storage provided by storage service providers. File and folder synchronization between different machines, sharing files and folders with other users, file versioning as well as automated backups are the key functionalities of these emerging cloud storage services. Cloud storage services have changed the way users manage and interact with data outsourced to public providers. With these services, multiple subscribers can collaboratively work and share data without concerns about their data consistency, availability and reliability. Although these cloud storage services offer attractive features, many customers have not adopted these services. Since data stored in these services is under the control of service providers resulting in confidentiality and security concerns and risks. Therefore, using cloud storage services for storing valuable data depends mainly on whether the service provider can offer sufficient security and assurance to meet client requirements. From the way most cloud storage services are constructed, we can notice that these storage services do not provide users with sufficient levels of security leading to an inherent risk on users\u27 data from external and internal attacks. These attacks take the form of: data exposure (lack of data confidentiality); data tampering (lack of data integrity); and denial of data (lack of data availability) by third parties on the cloud or by the cloud provider himself. Therefore, the cloud storage services should ensure the data confidentiality in the following state: data in motion (while transmitting over networks), data at rest (when stored at provider\u27s disks). To address the above concerns, confidentiality and access controllability of outsourced data with strong cryptographic guarantee should be maintained. To ensure data confidentiality in public cloud storage services, data should be encrypted data before it is outsourced to these services. Although, users can rely on client side cloud storage services or software encryption tools for encrypting user\u27s data; however, many of these services fail to achieve data confidentiality. Box, for example, does not encrypt user files via SSL and within Box servers. Client side cloud storage services can intentionally/unintentionally disclose user decryption keys to its provider. In addition, some cloud storage services support convergent encryption for encrypting users\u27 data exposing it to “confirmation of a file attack. On the other hand, software encryption tools use full-disk encryption (FDE) which is not feasible for cloud-based file sharing services, because it encrypts the data as virtual hard disks. Although encryption can ensure data confidentiality; however, it fails to achieve fine-grained access control over outsourced data. Since, public cloud storage services are managed by un-trusted cloud service provider, secure and efficient fine-grained access control cannot be realized through these services as these policies are managed by storage services that have full control over the sharing process. Therefore, there is not any guarantee that they will provide good means for efficient and secure sharing and they can also deduce confidential information about the outsourced data and users\u27 personal information. In this work, we would like to improve the currently employed security measures for securing data in cloud store services. To achieve better data confidentiality for data stored in the cloud without relying on cloud service providers (CSPs) or putting any burden on users, in this thesis, we designed a secure cloud storage system framework that simultaneously achieves data confidentiality, fine-grained access control on encrypted data and scalable user revocation. This framework is built on a third part trusted (TTP) service that can be employed either locally on users\u27 machine or premises, or remotely on top of cloud storage services. This service shall encrypts users data before uploading it to the cloud and decrypts it after downloading from the cloud; therefore, it remove the burden of storing, managing and maintaining encryption/decryption keys from data owner\u27s. In addition, this service only retains user\u27s secret key(s) not data. Moreover, to ensure high security for these keys, it stores them on hardware device. Furthermore, this service combines multi-authority ciphertext policy attribute-based encryption (CP-ABE) and attribute-based Signature (ABS) for achieving many-read-many-write fine-grained data access control on storage services. Moreover, it efficiently revokes users\u27 privileges without relying on the data owner for re-encrypting massive amounts of data and re-distributing the new keys to the authorized users. It removes the heavy computation of re-encryption from users and delegates this task to the cloud service provider (CSP) proxy servers. These proxy servers achieve flexible and efficient re-encryption without revealing underlying data to the cloud. In our designed architecture, we addressed the problem of ensuring data confidentiality against cloud and against accesses beyond authorized rights. To resolve these issues, we designed a trusted third party (TTP) service that is in charge of storing data in an encrypted format in the cloud. To improve the efficiency of the designed architecture, the service allows the users to choose the level of severity of the data and according to this level different encryption algorithms are employed. To achieve many-read-many-write fine grained access control, we merge two algorithms (multi-authority ciphertext policy attribute-based encryption (MA- CP-ABE) and attribute-based Signature (ABS)). Moreover, we support two levels of revocation: user and attribute revocation so that we can comply with the collaborative environment. Last but not least, we validate the effectiveness of our design by carrying out a detailed security analysis. This analysis shall prove the correctness of our design in terms of data confidentiality each stage of user interaction with the cloud

Advances in signatures, encryption, and E-Cash from bilinear groups

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 147-161).We present new formal definitions, algorithms, and motivating applications for three natural cryptographic constructions. Our constructions are based on a special type of algebraic group called bilinear groups. 1. Re-Signatures: We present the first public key signature scheme where a semi-trusted proxy, given special information, can translate Alice's signature on a message into Bob's signature on the same message. The special information, however, allows nothing else, i.e., the proxy cannot translate from Bob to Alice, nor can it sign on behalf of either Alice or Bob. We show that a path through a graph can be cheaply authenticated using this scheme, with applications to electronic passports. 2. Re-Encryption: We present the first public key cryptosystem where a semi-trusted proxy, given special information, can translate an encryption of a message under Alice's key into an encryption of the same message under Bob's key. Again, the special information allows nothing else, i.e. the proxy cannot translate from Bob to Alice, decrypt on behalf of either Alice or Bob, or learn anything else about the message. We apply this scheme to create a new mechanism for secure distributed storage.(cont.) 3. Compact; E-Cash with Tracing and Bounded-Anonymity: We present an offline e-cash system where 2 coins can be stored in O(e + k) bits and withdrawn or spent in 0(f + k) time, where k is the security parameter. The best previously known schemes required at least one of these complexities to be 0(2t . k). In our system, a user's transactions are anonymous and unlinkable, unless she performs a forbidden action, such as double-spending a coin. Performing a forbidden action reveals the identity of the user, and optionally allows to trace all of her past transactions. We provide solutions without using a trusted party. We argue why features of our system are likely to be crucial to the adoption of any e-cash system.by Susan Hohenberger.Ph.D

Efficient Location Privacy In Mobile Applications

Location awareness is an essential part of today\u27s mobile devices. It is a well-established technology that offers significant benefits to mobile users. While location awareness has triggered the exponential growth of mobile computing, it has also introduced new privacy threats due to frequent location disclosures. Movement patterns could be used to identify individuals and also leak sensitive information about them, such as health condition, lifestyle, political/religious affiliations, etc. In this dissertation we address location privacy in the context of mobile applications. First we look into location privacy in the context of Dynamic Spectrum Access (DSA) technology. DSA is a promising framework for mitigating the spectrum shortage caused by fixed spectrum allocation policies. In particular, DSA allows license-exempt users to access the licensed spectrum bands when not in use by their respective owners. Here, we focus on the database-driven DSA model, where mobile users issue location-based queries to a white-space database in order to identify idle channels in their area. We present a number of efficient protocols that allow users to retrieve channel availability information from the white-space database while maintaining their location secret. In the second part of the dissertation we look into location privacy in the context of location-aware mobile advertising. Location-aware mobile advertising is expanding very rapidly and is forecast to grow much faster than any other industry in the digital era. Unfortunately, with the rise and expansion of online behavioral advertising, consumers have grown very skeptical of the vast amount of data that is extracted and mined from advertisers today. As a result, the consensus has shifted towards stricter privacy requirements. Clearly, there exists an innate conflict between privacy and advertisement, yet existing advertising practices rely heavily on non-disclosure agreements and policy enforcement rather than computational privacy guarantees. In the second half of this dissertation, we present a novel privacy-preserving location-aware mobile advertisement framework that is built with privacy in mind from the ground up. The framework consists of several methods which ease the tension that exists between privacy and advertising by guaranteeing, through cryptographic constructions, that (i) mobile users receive advertisements relative to their location and interests in a privacy-preserving manner, and (ii) the advertisement network can only compute aggregate statistics of ad impressions and click-through-rates. Through extensive experimentation, we show that our methods are efficient in terms of both computational and communication cost, especially at the client side

Group Key Management in Wireless Ad-Hoc and Sensor Networks

A growing number of secure group applications in both civilian and military domains is being deployed in WAHNs. A Wireless Ad-hoc Network (WARN) is a collection of autonomous nodes or terminals that communicate with each other by forming a multi-hop radio network and maintaining connectivity in a decentralized manner. A Mobile Ad-hoc Network (MANET) is a special type of WARN with mobile users. MANET nodes have limited communication, computational capabilities, and power. Wireless Sensor Networks (WSNs) are sensor networks with massive numbers of small, inexpensive devices pervasive throughout electrical and mechanical systems and ubiquitous throughout the environment that monitor and control most aspects of our physical world. In a WAHNs and WSNs with un-trusted nodes, nodes may falsify information, collude to disclose system keys, or even passively refuse to collaborate. Moreover, mobile adversaries might invade more than one node and try to reveal all system secret keys. Due to these special characteristics, key management is essential in securing such networks. Current protocols for secure group communications used in fixed networks tend to be inappropriate. The main objective of this research is to propose, design and evaluate a suitable key management approach for secure group communications to support WAHNs and WSNs applications. Key management is usually divided into key analysis, key assignment, key generation and key distribution. In this thesis, we tried to introduce key management schemes to provide secure group communications in both WAHNs and WSNs. Starting with WAHNs, we developed a key management scheme. A novel architecture for secure group communications was proposed. Our proposed scheme handles key distribution through Combinatorial Key Distribution Scheme (CKDS). We followed with key generation using Threshold-based Key Generation in WAHNs (TKGS). For key assignment, we proposed Combinatorial Key Assignment Scheme (CKAS), which assigns closer key strings to co-located nodes. We claim that our architecture can readily be populated with components to support objectives such as fault tolerance, full-distribution and scalability to mitigate WAHNs constraints. In our architecture, group management is integrated with multicast at the application layer. For key management in WSNs, we started with DCK, a modified scheme suitable for WSNs. In summary, the DCK achieves the following: (1) cluster leader nodes carry the major part of the key management overhead; (2) DCK consumes less than 50% of the energy consumed by SHELL in key management; (3) localizing key refreshment and handling node capture enhances the security by minimizing the amount of information known by each node about other portions of the network; and (4) since DCK does not involve the use of other clusters to maintain local cluster data, it scales better from a storage point of view with the network size represented by the number of clusters. We went further and proposed the use of key polynomials with DCK to enhance the resilience of multiple node capturing. Comparing our schemes to static and dynamic key management, our scheme was found to enhance network resilience at a smaller polynomial degree t and accordingly with less storage per node

A security concept for distributed data processing systems

Today, the amount of raw data available is abundant. As only a small part of this data is in a form fit for further processing, there is many data left to analyze and process. At the same time, cloud services are ubiquitous and allow even small businesses to perform large tasks of distributed data processing without the significant costs required for a suitable computational infrastructure. However, as more and more users transfer their data into the cloud for processing and storage, concerns about data security arise. An extensive review of data security research in today's cloud solutions confirms these concerns to be justified. The existing strategies for securing one's data are not adequate for many use cases. Therefore, this work proposes a holistic security concept for distributed data processing in the cloud. For the purpose of providing security in heterogeneous cloud environments, it statically analyzes a data flow prior to execution and determines the optimal security measurements. Without imposing strict requirements on the cloud services involved, it can be deployed in a broad range of scenarios. The concept's generic design can be adopted by existing data rocessing tools. An exemplary implementation is provided for the mashup tool FlexMash. Requirements, such as data confidentiality, integrity, access control, and scalability were evaluated to be met.Die heutige Menge an vorhandenen Daten ist enorm. Viele davon müssen zunächst verarbeitet und analysiert werden, da nur ein geringer Teil dieser Daten für die weitere Verarbeitung geeignet ist. Cloud-basierte Dienste sind allgegenwärtig und erlauben es auch kleineren Unternehmen Datenverarbeitung durchzuführen, ohne die Kosten von notwendiger Infrastruktur tragen zu müssen. Mit einer zunehmenden Zahl an Nutzern von Clouds wachsen jedoch auch Bedenken der Sicherheit. Eine ausführliche Durchsicht der aktuellen Forschung zu diesem Thema bestätigt diese Bedenken und existierende Strategien zur Sicherung der eigenen Daten berücksichtigen viele Fälle nicht. Daher stellt diese Arbeit ein ganzheitliches Sicherheitskonzept für die verteilte Datenverarbeitung in der Cloud vor. Damit Sicherheit in heterogenen Cloudumgebungen gewährleistet werden kann, wird ein Datenfluss vor der Ausführung statisch analysiert und es werden die für diesen Fluss optimalen Sicherheitsmaßnahmen festgelegt. Das Konzept besitzt einen breiten Anwendungsbereich, da keine straffen Anforderungen an die genutzten Dienste gestellt werden. Das generische Design des Konzepts ermöglicht eine einfache Integration in bereits existierende Datenverarbeitungsanwendungen, wie beispielhaft an FlexMash gezeigt wird. Anforderungen, wie die Vertraulichkeit von Daten, deren Integrität, Zugriffskontrolle und Skalierbarkeit des Systems konnten erreicht werden

Data Service Outsourcing and Privacy Protection in Mobile Internet

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