217 research outputs found
Using Granule to Search Privacy Preserving Voice in Home IoT Systems
The Home IoT Voice System (HIVS) such as Amazon Alexa or Apple Siri can provide voice-based interfaces for people to conduct the search tasks using their voice. However, how to protect privacy is a big challenge. This paper proposes a novel personalized search scheme of encrypting voice with privacy-preserving by the granule computing technique. Firstly, Mel-Frequency Cepstrum Coefficients (MFCC) are used to extract voice features. These features are obfuscated by obfuscation function to protect them from being disclosed the server. Secondly, a series of definitions are presented, including fuzzy granule, fuzzy granule vector, ciphertext granule, operators and metrics. Thirdly, the AES method is used to encrypt voices. A scheme of searchable encrypted voice is designed by creating the fuzzy granule of obfuscation features of voices and the ciphertext granule of the voice. The experiments are conducted on corpus including English, Chinese and Arabic. The results show the feasibility and good performance of the proposed scheme
Quantum Searchable Encryption for Cloud Data Based on Full-Blind Quantum Computation
Searchable encryption (SE) is a positive way to protect users sensitive data
in cloud computing setting, while preserving search ability on the server side,
i.e., it allows the server to search encrypted data without leaking information
about the plaintext data. In this paper, a multi-client universal circuit-based
full-blind quantum computation (FBQC) model is proposed. In order to meet the
requirements of multi-client accessing or computing encrypted cloud data, all
clients with limited quantum ability outsource the key generation to a trusted
key center and upload their encrypted data to the data center. Considering the
feasibility of physical implementation, all quantum gates in the circuit are
replaced with the combination of {\pi}/8 rotation operator set {Rz({\pi}/4),
Ry({\pi}/4), CRz({\pi}/4), CRy({\pi}/4), CCRz({\pi}/4), CCRy({\pi}/4)}. In
addition, the data center is only allowed to perform one {\pi}/8 rotation
operator each time, but does not know the structure of the circuit (i.e.,
quantum computation), so it can guarantee the blindness of computation. Then,
through combining this multi-client FBQC model and Grover searching algorithm,
we continue to propose a quantum searchable encryption scheme for cloud data.
It solves the problem of multi-client access mode under searchable encryption
in the cloud environment, and has the ability to resist against some quantum
attacks. To better demonstrate our scheme, an example of our scheme to search
on encrypted 2-qubit state is given in detail. Furthermore, the security of our
scheme is analysed from two aspects: external attacks and internal attacks, and
the result indicates that it can resist against such kinds of attacks and also
guarantee the blindness of data and computation.Comment: 20 pages, 13 figure
Access Management in Lightweight IoT: A Comprehensive review of ACE-OAuth framework
With the expansion of Internet of Things (IoT), the need for secure and scalable authentication and
authorization mechanism for resource-constrained devices is becoming increasingly important. This
thesis reviews the authentication and authorization mechanisms in resource-constrained Internet of
Things (IoT) environments. The thesis focuses on the ACE-OAuth framework, which is a lightweight
and scalable solution for access management in IoT. Traditional access management protocols are not
well-suited for the resource-constrained environment of IoT devices. This makes the lightweight
devices vulnerable to cyber-attacks and unauthorized access. This thesis explores the security
mechanisms and standards, the protocol flow and comparison of ACE-OAuth profiles. It underlines
their potential risks involved with the implementation. The thesis delves into the existing and
emerging trends technologies of resource-constrained IoT and identifies limitations and potential
threats in existing authentication and authorization methods.
Furthermore, comparative analysis of ACE profiles demonstrated that the DTLS profile enables
constrained servers to effectively handle client authentication and authorization. The OSCORE
provides enhanced security and non-repudiation due to the Proof-of-Possession (PoP) mechanism,
requiring client to prove the possession of cryptographic key to generate the access token.
The key findings in this thesis, including security implications, strengths, and weaknesses for ACE
OAuth profiles are covered in-depth. It shows that the ACE-OAuth framework’s strengths lie in its
customization capabilities and scalability. This thesis demonstrates the practical applications and
benefits of ACE-OAuth framework in diverse IoT deployments through implementation in smart
home and factory use cases. Through these discussions, the research advances the application of
authentication and authorization mechanisms and provides practical insights into overcoming the
challenges in constrained IoT settings
Security and Privacy for Green IoT-based Agriculture: Review, Blockchain solutions, and Challenges
open access articleThis paper presents research challenges on security and privacy issues in the field of green IoT-based agriculture. We start by describing a four-tier green IoT-based agriculture architecture and summarizing the existing surveys that deal with smart agriculture. Then, we provide a classification of threat models against green IoT-based agriculture into five categories, including, attacks against privacy, authentication, confidentiality, availability, and integrity properties. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward secure and privacy-preserving technologies for IoT applications and how they will be adapted for green IoT-based agriculture. In addition, we analyze the privacy-oriented blockchain-based solutions as well as consensus algorithms for IoT applications and how they will be adapted for green IoT-based agriculture. Based on the current survey, we highlight open research challenges and discuss possible future research directions in the security and privacy of green IoT-based agriculture
A Hybrid Multi-user Cloud Access Control based Block Chain Framework for Privacy Preserving Distributed Databases
Most of the traditional medical applications are insecure and difficult to compute the data integrity with variable hash size. Traditional medical data security systems are insecure and it depend on static parameters for data security. Also, distributed based cloud storage systems are independent of integrity computational and data security due to unstructured data and computational memory. As the size of the data and its dimensions are increasing in the public and private cloud servers, it is difficult to provide the machine learning based privacy preserving in cloud computing environment. Block-chain technology plays a vital role for large cloud databases. Most of the conventional block-chain frameworks are based on the existing integrity and confidentiality models. Also, these models are based on the data size and file format. In this model, a novel integrity verification and encryption framework is designed and implemented in cloud environment. In order to overcome these problems in the cloud computing environment, a hybrid integrity and security-based block-chain framework is designed and implemented on the large distributed databases. In this framework,a novel decision tree classifier is used along with non-linear mathematical hash algorithm and advanced attribute-based encryption models are used to improve the privacy of multiple users on the large cloud datasets. Experimental results proved that the proposed advanced privacy preserving based block-chain technology has better efficiency than the traditional block-chain based privacy preserving systems on large distributed databases
AI-enabled privacy-preservation phrase with multi-keyword ranked searching for sustainable edge-cloud networks in the era of industrial IoT
Abstract: Please refer to full text to view abstrac
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