323 research outputs found
SQL on Structurally-Encrypted Databases
We show how to encrypt a relational database in such a way that it can efficiently support a large class of SQL queries. Our construction is based solely on structured encryption (STE) and does not make use of any property-preserving encryption (PPE) schemes such as deterministic and order-preserving encryption. As such, our approach leaks considerably less than PPE-based solutions which have recently been shown to reveal a lot of information in certain settings (Naveed et al., CCS \u2715). Our construction is efficient and---under some conditions on the database and queries---can have asymptotically-optimal query complexity. We also show how to extend our solution to be dynamic while maintaining the scheme\u27s optimal query complexity
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
SafeRegions: performance evaluation of multi-party protocols on HBase
On-line applications and services are now a critical part of our everyday life. Using these services typically requires us to trust our personal or company's information to a large number of third-party entities. These entities enforce several security measures to avoid unauthorized accesses but data is still stored on common database systems that are designed without data privacy concerns in mind. As a result, data is vulnerable against anyone with direct access to the database, which may be external attackers, malicious insiders, spies or even subpoenas. Building strong data privacy mechanisms on top of common database systems is possible but has a significant impact on the system's resources, computational capabilities and performance. Notably, the amount of useful computation that may be done over strongly encrypted data is close to none, which defeats the purpose of offloading computation to third-party services. In this paper, we propose to shift the need to trust in the honesty and security of service providers to simply trust that they will not collude. This is reasonable as cloud providers, being competitors, do not share data among themselves. We focus on NoSQL databases and present SafeRegions, a novel prototype of a distributed and secure NoSQL database that is built on top of HBase and that guarantees strong data privacy while still providing most of HBase's query capabilities. SafeRegions relies on secret sharing and multiparty computation techniques to provide a NoSQL database built on top of multiple, non-colluding service providers that appear as a single one to the user. Strikingly, service providers, individually, cannot disclose any of the user's data but, together, are able to offer data storage and processing capabilities. Additionally, we evaluate SafeRegions exposing performance trade-offs imposed by security mechanisms and provide useful insights for future research on performance optimization
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
Why Your Encrypted Database Is Not Secure
Encrypted databases, a popular approach to protecting data from compromised database management systems (DBMS’s), use abstract threat models that capture neither realistic databases, nor realistic attack scenarios. In particular, the “snapshot attacker” model used to support the security claims for many encrypted databases does not reflect the information about past queries available in any snapshot attack on an actual DBMS.
We demonstrate how this gap between theory and reality causes encrypted databases to fail to achieve their “provable security” guarantees
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