Accountable Authority Ciphertext-Policy Attribute-Based Encryption with White-Box Traceability and Public Auditing in the Cloud

As a sophisticated mechanism for secure fine-grained access control, ciphertext-policy attribute-based encryption (CP-ABE) is a highly promising solution for commercial applications such as cloud computing. However, there still exists one major issue awaiting to be solved, that is, the prevention of key abuse. Most of the existing CP-ABE systems missed this critical functionality, hindering the wide utilization and commercial application of CP-ABE systems to date. In this paper, we address two practical problems about the key abuse of CP-ABE: (1) The key escrow problem of the semi-trusted authority; and, (2) The malicious key delegation problem of the users. For the semi-trusted authority, its misbehavior (i.e., illegal key (re-)distribution) should be caught and prosecuted. And for a user, his/her malicious behavior (i.e., illegal key sharing) need be traced. We affirmatively solve these two key abuse problems by proposing the first accountable authority CP-ABE with white-box traceability that supports policies expressed in any monotone access structures. Moreover, we provide an auditor to judge publicly whether a suspected user is guilty or is framed by the authority

Attribute-based encryption for cloud computing access control: A survey

National Research Foundation (NRF) Singapore; AXA Research Fun

Ensuring Accountability and Outsourced Decryption in IoT Systems using Ciphertext-Policy Attribute-Based Encryption

Attribute based cryptography enhances the chances of secure communication on large scale. There are several features of attribute based encryption which have been proposed as different protocols. Most of these are suitable for access control in large systems like cloud services. Very few protocols focus on reducing the computational overhead for lower end devices like Internet of Things sensors and actuators. Hence, it is desirable to have a mix of features in protocols for IoT architecture. Our protocol enforces accountability of different parties involved while reducing the computational overhead during decryption on miniature devices. We prove that our protocol is RCCA-secure in selective security model and achieve accountability and unlinkability

An Emerging Secure and Expressive Data Access Control for Cloud Storage

Secure cloud storage, which is an emerging cloud service, is designed to protect the confidentiality of outsourced data but also to provide flexible data access for cloud users whose data is out of physical control. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is regarded as one of the most promising techniques that may be leveraged to secure the guarantee of the service. However, the use of CP-ABE may yield an inevitable security breach which is known as the misuse of access credential (i.e. decryption rights), due to the intrinsic “all-or-nothing” decryption feature of CP-ABE. In this paper, we investigate the two main cases of access credential misuse: one is on the semi-trusted authority side, and the other is on the side of cloud user. To mitigate the misuse, we propose the first accountable authority and revocable CP-ABE based cloud storage system with white-box traceability and auditing, referred to as CryptCloud+. We also present the security analysis and further demonstrate the utility of our system via experiments

Outsourced CP-ABE with Whitebox Accountability in IoT Systems

Cryptography based on identity and attributes enhances the chance of secure communication on a large scale. Several attribute-based encryption schemes achieve different objectives when used in various protocols. Most of these are suitable for large systems like cloud services. There are a few protocols which focus on reducing the computational overhead for lower end devices like Internet of Things sensors and actuators. It is desirable to have a mix of features in protocols for IoT security architecture. We first propose a scheme to ensure accountability in CPABE scheme FAME. The protocol is proven CPA-secure with full security in random oracle model. We also prove its accountability. We also propose a hybrid protocol that enforces user accountability and outsourced decryption in IoT systems and achieve full security in replayable chosen ciphertext attack (RCCA) under random oracle model

Data Sharing on Untrusted Storage with Attribute-Based Encryption

Storing data on untrusted storage makes secure data sharing a challenge issue. On one hand, data access policies should be enforced on these storage servers; on the other hand, confidentiality of sensitive data should be well protected against them. Cryptographic methods are usually applied to address this issue -- only encrypted data are stored on storage servers while retaining secret key(s) to the data owner herself; user access is granted by issuing the corresponding data decryption keys. The main challenges for cryptographic methods include simultaneously achieving system scalability and fine-grained data access control, efficient key/user management, user accountability and etc. To address these challenge issues, this dissertation studies and enhances a novel public-key cryptography -- attribute-based encryption (ABE), and applies it for fine-grained data access control on untrusted storage. The first part of this dissertation discusses the necessity of applying ABE to secure data sharing on untrusted storage and addresses several security issues for ABE. More specifically, we propose three enhancement schemes for ABE: In the first enhancement scheme, we focus on how to revoke users in ABE with the help of untrusted servers. In this work, we enable the data owner to delegate most computation-intensive tasks pertained to user revocation to untrusted servers without disclosing data content to them. In the second enhancement scheme, we address key abuse attacks in ABE, in which authorized but malicious users abuse their access privileges by sharing their decryption keys with unauthorized users. Our proposed scheme makes it possible for the data owner to efficiently disclose the original key owner\u27s identity merely by checking the input and output of a suspicious user\u27s decryption device. Our third enhancement schemes study the issue of privacy preservation in ABE. Specifically, our proposed schemes hide the data owner\u27s access policy not only to the untrusted servers but also to all the users. The second part presents our ABE-based secure data sharing solutions for two specific applications -- Cloud Computing and Wireless Sensor Networks (WSNs). In Cloud Computing cloud servers are usually operated by third-party providers, which are almost certain to be outside the trust domain of cloud users. To secure data storage and sharing for cloud users, our proposed scheme lets the data owner (also a cloud user) generate her own ABE keys for data encryption and take the full control on key distribution/revocation. The main challenge in this work is to make the computation load affordable to the data owner and data consumers (both are cloud users). We address this challenge by uniquely combining various computation delegation techniques with ABE and allow both the data owner and data consumers to securely mitigate most computation-intensive tasks to cloud servers which are envisaged to have unlimited resources. In WSNs, wireless sensor nodes are often unattendedly deployed in the field and vulnerable to strong attacks such as memory breach. For securing storage and sharing of data on distributed storage sensor nodes while retaining data confidentiality, sensor nodes encrypt their collected data using ABE public keys and store encrypted data on storage nodes. Authorized users are given corresponding decryption keys to read data. The main challenge in this case is that sensor nodes are extremely resource-constrained and can just afford limited computation/communication load. Taking this into account we divide the lifetime of sensor nodes into phases and distribute the computation tasks into each phase. We also revised the original ABE scheme to make the overhead pertained to user revocation minimal for sensor nodes. Feasibility of the scheme is demonstrated by experiments on real sensor platforms

Advances in Information Security and Privacy

With the recent pandemic emergency, many people are spending their days in smart working and have increased their use of digital resources for both work and entertainment. The result is that the amount of digital information handled online is dramatically increased, and we can observe a significant increase in the number of attacks, breaches, and hacks. This Special Issue aims to establish the state of the art in protecting information by mitigating information risks. This objective is reached by presenting both surveys on specific topics and original approaches and solutions to specific problems. In total, 16 papers have been published in this Special Issue

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

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

Evidence-based Accountability Audits for Cloud Computing

Cloud computing is known for its on-demand service provisioning and has now become mainstream. Many businesses as well as individuals are using cloud services on a daily basis. There is a big variety of services that ranges from the provision of computing resources to services such as productivity suites and social networks. The nature of these services varies heavily in terms of what kind of information is being out-sourced to the cloud provider. Often, that data is sensitive, for instance when PII is being shared by an individual. Also, businesses that move (parts of) their processes to the cloud are actively participating in a major paradigm shift from having data on-premise to transfering data to a third-party provider. However, many new challenges come along with this trend, which are closely tied to the loss of control over data. When moving to the cloud, direct control over geographical storage location, who has access to it and how it is shared and processed is given up. Because of this loss of control, cloud customers have to trust cloud providers that they treat their data in an appropriate and responsible way. Cloud audits can be used to check how data has been processed in the cloud (i.e., by whom, for what purpose) and whether or not this happened in compliance with what has been defined in agreed-upon privacy and data storage, usage and maintenance (i.e., data handling) policies. This way, a cloud customer can regain some of the control he has given up by moving to the cloud. In this thesis, accountability audits are presented as a way to strengthen trust in cloud computing by providing assurance about the processing of data in the cloud according to data handling and privacy policies. In cloud accountability audits, various distributed evidence sources need to be considered. The research presented in this thesis discusses the use of various heterogeous evidence sources on all cloud layers. This way, a complete picture of the actual data handling practices that is based on hard facts can be presented to the cloud consumer. Furthermore, this strengthens transparency of data processing in the cloud, which can lead to improved trust in cloud providers, if they choose to adopt these mechanisms in order to assure their customers that their data is being handled according to their expectations. The system presented in this thesis enables continuous auditing of a cloud provider's adherence to data handling policies in an automated way that shortens audit intervals and that is based on evidence that is produced by cloud subsystems. An important aspect of many cloud offerings is the combination of multiple distinct cloud services that are offered by independent providers. Data is thereby freuqently exchanged between the cloud providers. This also includes trans-border flows of data, where one provider may be required to adhere to more strict data protection requirements than the others. The system presented in this thesis addresses such scenarios by enabling the collection of evidence at providers and evaluating it during audits. Securing evidence quickly becomes a challenge in the system design, when information that is needed for the audit is deemed sensitive or confidential. This means that securing the evidence at-rest as well as in-transit is of utmost importance, in order not to introduce a new liability by building an insecure data heap. This research presents the identification of security and privacy protection requirements alongside proposed solutions that enable the development of an architecture for secure, automated, policy-driven and evidence-based accountability audits

Design and evaluation of blockchain-based security protocols

Many security protocols rely on the assumption that the trusted third party (TTP) will behave “as it should”. However, this assumption is difficult to justify in the real world. A TTP may become malicious due to its hidden interests or having been compromised. It is publicly acknowledged that a failed TTP can easily destroy the entire security protocol. This thesis aims to provide results on how to use blockchain technologies to mitigate TTP challenges and thereby secure existing cryptographic protocols. Firstly, we formally define a smart contract-based TTP (denoted as TTP-I) and give two security protocols based on such a type of TTP as concrete instances. In this approach, a smart contract can either complement a TTP’s actions or take over the entire functions of the existing TTP. This helps to obtain many security properties such as transparency and accountability. Smart contracts, however, are not adequate to replace TTP that is capable of maintaining secret information since all the states changed by TTP-I are in plaintext and publicly accessible. To fill the gap, we propose another type of TTP (denoted as TTP-II) that enables confidential executions by combining smart contracts and Trusted Execution Environments (TEEs). To achieve this goal, we first investigate the state-of-the-art TEE-aided confidential smart contracts and then explore their core mechanisms. We further apply TTP-II to a traceable credential system and an accountable decryption system. These systems are proved secure and feasible. However, since blockchain systems suffer from scalability and performance issues, the development of blockchain-based cryptographic protocols is inevitably retarded. At last, to make better blockchain systems, we provide two core mechanisms: a weak consensus algorithm and a delegatable payment protocol. The weak consensus algorithm allows parallel block generation, improving the performance and scalability of upper-layer blockchain systems. The delegatable payment protocol creates an offline payment channel, improving the payment speed. Both proposed algorithms have been practically implemented and systematically evaluated. Notably, the weak consensus algorithm has already been taken up by industries. Video abstract: https://youtu.be/rkAatxBRau