323 research outputs found
SoK: Cryptographically Protected Database Search
Protected database search systems cryptographically isolate the roles of
reading from, writing to, and administering the database. This separation
limits unnecessary administrator access and protects data in the case of system
breaches. Since protected search was introduced in 2000, the area has grown
rapidly; systems are offered by academia, start-ups, and established companies.
However, there is no best protected search system or set of techniques.
Design of such systems is a balancing act between security, functionality,
performance, and usability. This challenge is made more difficult by ongoing
database specialization, as some users will want the functionality of SQL,
NoSQL, or NewSQL databases. This database evolution will continue, and the
protected search community should be able to quickly provide functionality
consistent with newly invented databases.
At the same time, the community must accurately and clearly characterize the
tradeoffs between different approaches. To address these challenges, we provide
the following contributions:
1) An identification of the important primitive operations across database
paradigms. We find there are a small number of base operations that can be used
and combined to support a large number of database paradigms.
2) An evaluation of the current state of protected search systems in
implementing these base operations. This evaluation describes the main
approaches and tradeoffs for each base operation. Furthermore, it puts
protected search in the context of unprotected search, identifying key gaps in
functionality.
3) An analysis of attacks against protected search for different base
queries.
4) A roadmap and tools for transforming a protected search system into a
protected database, including an open-source performance evaluation platform
and initial user opinions of protected search.Comment: 20 pages, to appear to IEEE Security and Privac
HardIDX: Practical and Secure Index with SGX
Software-based approaches for search over encrypted data are still either
challenged by lack of proper, low-leakage encryption or slow performance.
Existing hardware-based approaches do not scale well due to hardware
limitations and software designs that are not specifically tailored to the
hardware architecture, and are rarely well analyzed for their security (e.g.,
the impact of side channels). Additionally, existing hardware-based solutions
often have a large code footprint in the trusted environment susceptible to
software compromises. In this paper we present HardIDX: a hardware-based
approach, leveraging Intel's SGX, for search over encrypted data. It implements
only the security critical core, i.e., the search functionality, in the trusted
environment and resorts to untrusted software for the remainder. HardIDX is
deployable as a highly performant encrypted database index: it is logarithmic
in the size of the index and searches are performed within a few milliseconds
rather than seconds. We formally model and prove the security of our scheme
showing that its leakage is equivalent to the best known searchable encryption
schemes. Our implementation has a very small code and memory footprint yet
still scales to virtually unlimited search index sizes, i.e., size is limited
only by the general - non-secure - hardware resources
Practical Architectures for Deployment of Searchable Encryption in a Cloud Environment
Public cloud service providers provide an infrastructure that gives businesses and individuals access to computing power and storage space on a pay-as-you-go basis. This allows these entities to bypass the usual costs associated with having their own data centre such as: hardware, construction, air conditioning and security costs, for example, making this a cost-effective solution for data storage. If the data being stored is of a sensitive nature, encrypting it prior to outsourcing it to a public cloud is a good method of ensuring the confidentiality of the data. With the data being encrypted, however, searching over it becomes unfeasible. In this paper, we examine different architectures for supporting search over encrypted data and discuss some of the challenges that need to be overcome if these techniques are to be engineered into practical systems
Privacy-preserving efficient searchable encryption
Data storage and computation outsourcing to third-party managed data centers,
in environments such as Cloud Computing, is increasingly being adopted
by individuals, organizations, and governments. However, as cloud-based outsourcing
models expand to society-critical data and services, the lack of effective
and independent control over security and privacy conditions in such settings
presents significant challenges.
An interesting solution to these issues is to perform computations on encrypted
data, directly in the outsourcing servers. Such an approach benefits
from not requiring major data transfers and decryptions, increasing performance
and scalability of operations. Searching operations, an important application
case when cloud-backed repositories increase in number and size, are good examples
where security, efficiency, and precision are relevant requisites. Yet existing
proposals for searching encrypted data are still limited from multiple perspectives,
including usability, query expressiveness, and client-side performance and
scalability.
This thesis focuses on the design and evaluation of mechanisms for searching
encrypted data with improved efficiency, scalability, and usability. There are
two particular concerns addressed in the thesis: on one hand, the thesis aims at
supporting multiple media formats, especially text, images, and multimodal data
(i.e. data with multiple media formats simultaneously); on the other hand the
thesis addresses client-side overhead, and how it can be minimized in order to
support client applications executing in both high-performance desktop devices
and resource-constrained mobile devices.
From the research performed to address these issues, three core contributions
were developed and are presented in the thesis: (i) CloudCryptoSearch, a middleware
system for storing and searching text documents with privacy guarantees,
while supporting multiple modes of deployment (user device, local proxy, or computational cloud) and exploring different tradeoffs between security, usability, and performance; (ii) a novel framework for efficiently searching encrypted images
based on IES-CBIR, an Image Encryption Scheme with Content-Based Image
Retrieval properties that we also propose and evaluate; (iii) MIE, a Multimodal
Indexable Encryption distributed middleware that allows storing, sharing, and
searching encrypted multimodal data while minimizing client-side overhead and
supporting both desktop and mobile devices
An In-Depth Analysis on Efficiency and Vulnerabilities on a Cloud-Based Searchable Symmetric Encryption Solution
Searchable Symmetric Encryption (SSE) has come to be as an integral cryptographic approach in a world where digital privacy is essential. The capacity to search through encrypted data whilst maintaining its integrity meets the most important demand for security and confidentiality in a society that is increasingly dependent on cloud-based services and data storage. SSE offers efficient processing of queries over encrypted datasets, allowing entities to comply with data privacy rules while preserving database usability. Our research goes into this need, concentrating on the development and thorough testing of an SSE system based on Curtmola’s architecture and employing Advanced Encryption Standard (AES) in Cypher Block Chaining (CBC) mode. A primary goal of the research is to conduct a thorough evaluation of the security and performance of the system. In order to assess search performance, a variety of database settings were extensively tested, and the system's security was tested by simulating intricate threat scenarios such as count attacks and leakage abuse. The efficiency of operation and cryptographic robustness of the SSE system are critically examined by these reviews
M-SSE: an effective searchable symmetric encryption with enhanced security for mobile devices
Searchable Encryption (SE) allows mobile devices with limited computing and storage resources to outsource data to an untrusted cloud server. Users are able to search and retrieve the outsourced, however, it suffers from information and privacy leakage. The reason is that most of the previous works rely on the single cloud model, which allows that the cloud server get all the search information from users. In this paper, we present a new scheme M-SSE that achieves both forward and backward security based on a multi-cloud technique. The new scheme is secure against both adaptive file injection attack and size pattern attack by utilizing multiple cloud servers. Experiment results show that our scheme is effective compared with the other existing schemes
Forward and Backward Private Searchable Encryption from Constrained Cryptographic Primitives
Using dynamic Searchable Symmetric Encryption, a user with limited storage resources can securely outsource a database to an untrusted server, in such a way that the database can still be searched and updated efficiently. For these schemes, it would be desirable that updates do not reveal any information a priori about the modifications they carry out, and that deleted results remain inaccessible to the server a posteriori. If the first property, called forward privacy, has been the main motivation of recent works, the second one, backward privacy, has been overlooked.
In this paper, we study for the first time the notion of backward privacy for searchable encryption. After giving formal definitions for different flavors of backward privacy, we present several schemes achieving both forward and backward privacy, with various efficiency trade-offs.
Our constructions crucially rely on primitives such as constrained pseudo-random functions and puncturable encryption schemes. Using these advanced cryptographic primitives allows for a fine-grained control of the power of the adversary, preventing her from evaluating functions on selected inputs, or decrypting specific ciphertexts. In turn, this high degree of control allows our SSE constructions to achieve the stronger forms of privacy outlined above. As an example, we present a framework to construct forward-private schemes from range-constrained pseudo-random functions.
Finally, we provide experimental results for implementations of our schemes, and study their practical efficiency
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