TrustedDB: A Trusted Hardware based Database with Privacy and Data Confidentiality

TrustedDB: A Trusted Hardware based Database with Privacy and Data Confidentiality

ABSTRACT:

Traditionally, as soon as confidentiality becomes a concern, data is encrypted before outsourcing to a service provider. Any software-based cryptographic constructs then deployed, for server-side query processing on the encrypted data, inherently limit query expressiveness. Here, we introduce TrustedDB, an outsourced database prototype that allows clients to execute SQL queries with privacy and under regulatory compliance constraints by leveraging server-hosted, tamper-proof trusted hardware in critical query processing stages, thereby removing any limitations on the type of supported queries. Despite the cost overhead and performance limitations of trusted hardware, we show that the costs per query are orders of magnitude lower than any (existing or) potential future software-only mechanisms. TrustedDB is built and runs on actual hardware and its performance and costs are evaluated here.

EXISTING SYSTEM:

Existing research addresses several such security aspects, including access privacy and searches on encrypted data. In most of these efforts data is encrypted before outsourcing. Once encrypted however, inherent limitations in the types of primitive operations that can be performed on encrypted data lead to fundamental expressiveness and practicality constraints. Recent theoretical cryptography results provide hope by proving the existence of universal homeomorphisms, i.e., encryption mechanisms that allow computation of arbitrary functions without decrypting the inputs. Unfortunately actual instances of such mechanisms seem to be decades away from being practical

DISADVANTAGES OF EXISTING SYSTEM:

Trusted hardware is generally impractical due to its performance limitations and higher acquisition costs. As a result, with very few exceptions, these efforts have stopped short of proposing or building full - fledged database processing engines.

Computation inside secure processors is orders of magnitude cheaper than any equivalent cryptographic operation performed on the provider’s unsecured server hardware, despite the overall greater acquisition cost of secure hardware.

PROPOSED SYSTEM:

we posit that a full-fledged, privacy enabling secure database leveraging server-side trusted hardware can be built and run at a fraction of the cost of any (existing or future) cryptography-enabled private data processing on common server hardware. We validate this by designing and building TrustedDB, a SQL database processing engine that makes use of tamperproof cryptographic coprocessors such as the IBM 4764 in close proximity to the outsourced data. Tamper resistant designs however are significantly constrained in both computational ability and memory capacity which makes implementing fully featured database solutions using secure coprocessors (SCPUs) very challenging. TrustedDB achieves this by utilizing common unsecured server resources to the maximum extent possible. E.g., TrustedDB enables the SCPU to transparently access external storage while preserving data confidentiality with on-the-fly encryption. This eliminates the limitations on the size of databases that can be supported. Moreover, client queries are pre-processed to identify sensitive components to be run inside the SCPU. Non-sensitive operations are off-loaded to the untrusted host server. This greatly improves performance and reduces the cost of transactions.

ADVANTAGES OF PROPOSED SYSTEM:

(i)                The introduction of new cost models and insights that explain and quantify the advantages of deploying trusted hardware for data processing,

(ii)             the design, development, and evaluation of TrustedDB, a trusted hardware based relational database with full data confidentiality, and

(iii)           Detailed query optimization techniques in a trusted hardware-based query execution model.

MODULES:

1.     Query Parsing and Execution

2.     Query optimization process

3.     System Catalog

4.     Analysis of Basic Query Operations

MODULES DESCRIPTION:

Query Parsing and Execution

In the first stage a client defines a database schema and partially populates it. Sensitive attributes are marked using the SENSITIVE keyword which the client layer transparently processes by encrypting the corresponding attributes:

CREATE TABLE customer (ID integer primary key, Name char (72) SENSITIVE, Address char (120) SENSITIVE);

(1) Later, a client sends a query request to the host server through a standard SQL interface. The query is transparently encrypted at the client site using the public key of the SCPU. The host server thus cannot decrypt the query. (2) The host server forwards the encrypted query to the Request Handler inside the SCPU. (3) The Request Handler decrypts the query and forwards it to the Query Parser. The query is parsed generating a set of plans. Each plan is constructed by rewriting the original client query into a set of sub-queries, and, according to their target data set classification, each sub-query in the plan is identified as being either public or private. (4)The Query Optimizer then estimates the execution costs of each of the plans and selects the best plan (one with least cost) for execution forwarding it to the dispatcher.(5) The Query Dispatcher forwards the public queries to the host server and the private queries to the SCPU database engine while handling dependencies. The net result is that the maximum possible work is run on the host server’s cheap cycles. (6) The final query result is assembled, encrypted, digitally signed by the SCPU Query Dispatcher, and sent to the client.

Query optimization process:

At a high level query optimization in a database system works as follows.

(i) The Query Plan Generator constructs possibly multiple plans for the client query.

(ii) For each constructed plan the Query Cost Estimator computes an estimate of the execution cost of that plan.

(iii) The best plan i.e., one with the least cost, is then selected and passed on to the Query Plan Interpretor for execution.

The query optimization process in TrustedDB works similarly with key differences in the Query Cost Estimator due to the logical partitioning of data mentioned above.

System Catalog:

Any query plan is composed of multiple individual execution steps. To estimate the cost of the entire plan it is essential to estimate the cost of individual steps and aggregate them. In order to estimate these costs the Query Cost Estimator needs access to some key information. E.g., the availability of an index or the knowledge of possible distinct values of an attribute. These sets of information are collected and stored in the System Catalog. Most available DBMS today have some form of periodically updated System Catalog.

Analysis of Basic Query Operations:

The cost of a plan is the aggregate of the cost of the steps that comprise it. In this section we present how execution times for a certain set of basic query plan steps are estimated.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

·        System        :  Pentium IV 2.4 GHz.

·        Hard Disk   : 40 GB.

·        Monitor      : 15 inch VGA Colour.

·        Mouse         : Logitech Mouse.

·        Ram            : 512 MB

·        Keyboard    : Standard Keyboard

SOFTWARE REQUIREMENTS:

·        Operating System : Windows XP.

·        Coding Language : ASP.NET, C#.Net.

·        Database              : SQL Server 2005

REFERENCE:

Sumeet Bajaj, Radu Sion “TrustedDB: A Trusted Hardware based Database with Privacy and Data Confidentiality” - IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 26, NO. 3, MARCH 2014