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

BLA2C2: Design of a Novel Blockchain-based Light-Weight Authentication & Access Control Layer for Cloud Deployments

Cloud deployments are consistently under attack, from both internal and external adversaries. These attacks include, but are not limited to brute force, masquerading, improper access, session hijacking, cross site scripting (XSS), etc. To mitigate these attacks, a wide variety of authentication & access control models are proposed by researchers, and each of them vary in terms of their internal implementation characteristics. It was observed that these models are either highly complex, or lack in terms of security under multiple attacks, which limits their applicability for real-time deployments. Moreover, some of these models are not flexible and cannot be deployed under dynamic cloud scenarios (like constant reconfigurations of Virtual Machines, dynamic authentication use-cases, etc.). To overcome these issues, this text proposes design of a novel blockchain-based Light-weight authentication & access control layer that can be used for dynamic cloud deployments. The proposed model initially applies a header-level light-weight sanitization layer that removes Cross Site Scripting, SQL Injection, and other data-level attacks. This is followed by a light-weight authentication layer, that assists in improving login-level security for external attacks. The authentication layer uses IP matching with reverse geolocation mapping in order to estimate outlier login attempts. This layer is cascaded with an efficient blockchain-based access control model, which assists in mitigating session hijacking, masquerading, sybil and other control-level attacks. The blockchain model is developed via integration of Grey Wolf Optimization (GWO) to reduce unnecessary complexities, and provides faster response when compared with existing blockchain-based security deployments. Efficiency of the model was estimated in terms of accuracy of detection for different attack types, delay needed for detection of these attacks, and computational complexity during attack mitigation operations. This performance was compared with existing models, and it was observed that the proposed model showcases 8.3% higher accuracy, with 10.5% lower delay, and 5.9% lower complexity w.r.t. standard blockchain-based & other security models. Due to these enhancements, the proposed model was capable of deployment for a wide variety of large-scale scenarios

A survey of state-of-the-art methods for securing medical databases

This review article presents a survey of recent work devoted to advanced state-of-the-art methods for securing of medical databases. We concentrate on three main directions, which have received attention recently: attribute-based encryption for enabling secure access to confidential medical databases distributed among several data centers; homomorphic encryption for providing answers to confidential queries in a secure manner; and privacy-preserving data mining used to analyze data stored in medical databases for verifying hypotheses and discovering trends. Only the most recent and significant work has been included

SEM-ACSIT:Secure and Efficient Multiauthority Access Control for IoT Cloud Storage

Data access control in a cloud storage system is regarded as a promising technique for enhanced efficiency and security utilizing a ciphertext-policy attribute-based encryption (CP-ABE) approach. However, due to a large number of data users as well as limited resources and heterogeneity of data devices in Internet of Things (IoT), existing access control schemes for the cloud storage are not effectively applicable to IoT applications. In this article, we construct a new CP-ABE-based storage model for data storing and secure access in a cloud for IoT applications. Our new framework introduces an attribute authority management (AAM) module in the cloud storage system functioned as an agent that provides a user-friendly access control and highly reduces the storage overhead of public keys. Then, we propose a novel secure and efficient multiauthority access control scheme of the cloud storage system for IoT, namely, SEM-ACSIT, which obtains both backward security and forward security when an attribute of a user is revoked. By exploiting encryption outsourcing, simplified key structuring and the AAM module, the computational overhead of a user is immensely decreased. Moreover, a user access control list (UACL) in the cloud server is constructed newly to support authorization access for a specific user. The analysis and simulation results demonstrate that our SEM-ACSIT scheme achieves powerful security with less computational overhead and lower storage costs than the existing schemes

Towards Secure Identity-Based Cryptosystems for Cloud Computing

The convenience provided by cloud computing has led to an increasing trend of many business organizations, government agencies and individual customers to migrate their services and data into cloud environments. However, once clients’ data is migrated to the cloud, the overall security control will be immediately shifted from data owners to the hands of service providers. When data owners decide to use the cloud environment, they rely entirely on third parties to make decisions about their data and, therefore, the main challenge is how to guarantee that the data is accessible by data owners and authorized users only. Remote user authentication to cloud services is traditionally achieved using a combination of ID cards and passwords/PINs while public key infrastructure and symmetric key encryptions are still the most common techniques for enforcing data security despite the missing link between the identity of data owners and the cryptographic keys. Furthermore, the key management in terms of the generation, distribution, and storage are still open challenges to traditional public-key systems. Identity-Based Cryptosystems (IBCs) are new generations of public key encryptions that can potentially solve the problems associated with key distribution in public key infrastructure in addition to providing a clear link between encryption keys and the identities of data owners. In IBCs, the need for pre-distributed keys before any encryption/decryption will be illuminated, which gives a great deal of flexibility required in an environment such as the cloud. Fuzzy identity-based cryptosystems are promising extensions of IBCs that rely on biometric modalities in generating the encryption and decryption keys instead of traditional identities such as email addresses. This thesis argues that the adoption of fuzzy identity-based cryptosystems seems an ideal option to secure cloud computing after addressing a number of vulnerabilities related to user verification, key generation, and key validation stages. The thesis is mainly concerned with enhancing the security and the privacy of fuzzy identity-based cryptosystems by proposing a framework with multiple security layers. The main contributions of the thesis can be summarised as follows. 1. Improving user verification based on using a Challenge-Response Multifactor Biometric Authentication (CR-MFBA) in fuzzy identity-based cryptosystems that reduce the impacts of impersonators attacks. 2. Reducing the dominance of the “trusted authority” in traditional fuzzy identity-based cryptosystems by making the process of generating the decryption keys a cooperative process between the trusted authority server and data owners. This leads to shifting control over the stored encrypted data from the trusted authority to the data owners. 3. Proposing a key-validity method that relies on employing the Shamir Secret Sharing, which also contributes to giving data owners more control over their data. 4. Further improving the control of data owners in fuzzy identity-based cryptosystems by linking the decryption keys parameters with their biometric modalities. 5. Proposing a new asymmetric key exchange protocol based on utilizing the scheme of fuzzy identity-based cryptosystems to shared encrypted data stored on cloud computing

Hidden in the Cloud : Advanced Cryptographic Techniques for Untrusted Cloud Environments

In the contemporary digital age, the ability to search and perform operations on encrypted data has become increasingly important. This significance is primarily due to the exponential growth of data, often referred to as the "new oil," and the corresponding rise in data privacy concerns. As more and more data is stored in the cloud, the need for robust security measures to protect this data from unauthorized access and misuse has become paramount. One of the key challenges in this context is the ability to perform meaningful operations on the data while it remains encrypted. Traditional encryption techniques, while providing a high level of security, render the data unusable for any practical purpose other than storage. This is where advanced cryptographic protocols like Symmetric Searchable Encryption (SSE), Functional Encryption (FE), Homomorphic Encryption (HE), and Hybrid Homomorphic Encryption (HHE) come into play. These protocols not only ensure the confidentiality of data but also allow computations on encrypted data, thereby offering a higher level of security and privacy. The ability to search and perform operations on encrypted data has several practical implications. For instance, it enables efficient Boolean queries on encrypted databases, which is crucial for many "big data" applications. It also allows for the execution of phrase searches, which are important for many machine learning applications, such as intelligent medical data analytics. Moreover, these capabilities are particularly relevant in the context of sensitive data, such as health records or financial information, where the privacy and security of user data are of utmost importance. Furthermore, these capabilities can help build trust in digital systems. Trust is a critical factor in the adoption and use of digital services. By ensuring the confidentiality, integrity, and availability of data, these protocols can help build user trust in cloud services. This trust, in turn, can drive the wider adoption of digital services, leading to a more inclusive digital society. However, it is important to note that while these capabilities offer significant advantages, they also present certain challenges. For instance, the computational overhead of these protocols can be substantial, making them less suitable for scenarios where efficiency is a critical requirement. Moreover, these protocols often require sophisticated key management mechanisms, which can be challenging to implement in practice. Therefore, there is a need for ongoing research to address these challenges and make these protocols more efficient and practical for real-world applications. The research publications included in this thesis offer a deep dive into the intricacies and advancements in the realm of cryptographic protocols, particularly in the context of the challenges and needs highlighted above. Publication I presents a novel approach to hybrid encryption, combining the strengths of ABE and SSE. This fusion aims to overcome the inherent limitations of both techniques, offering a more secure and efficient solution for key sharing and access control in cloud-based systems. Publication II further expands on SSE, showcasing a dynamic scheme that emphasizes forward and backward privacy, crucial for ensuring data integrity and confidentiality. Publication III and Publication IV delve into the potential of MIFE, demonstrating its applicability in real-world scenarios, such as designing encrypted private databases and additive reputation systems. These publications highlight the transformative potential of MIFE in bridging the gap between theoretical cryptographic concepts and practical applications. Lastly, Publication V underscores the significance of HE and HHE as a foundational element for secure protocols, emphasizing its potential in devices with limited computational capabilities. In essence, these publications not only validate the importance of searching and performing operations on encrypted data but also provide innovative solutions to the challenges mentioned. They collectively underscore the transformative potential of advanced cryptographic protocols in enhancing data security and privacy, paving the way for a more secure digital future

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