Encryption of sensitive data becomes more and more important for applications. For example patient names, SSN, address-data or credit card-numbers etc..

Cache supports different flavors of encryption. Block-level database encryption and data-element encryption. The block-level database encryption protects an entire database. The decryption/encryption is done when a block is written/read to or from the database and has very little impact on the performance.

With data-element encryption only certain data-fields are encrypted. Fields that contain sensitive data like patient data or credit-card numbers. Data-element encryption is also useful if a re-encryption is required periodically. With data-element encryption it is the responsibility of the application to encrypt/decrypt the data.

Both encryption methods leverage the managed key encryption infrastructure of Caché.

The following article describes a sample use-case where data-element encryption is used to encrypt person data.

But what if you have hundreds of thousands of records with an encrypted datafield and you have the need to search that field? Decryption of the field-values prior to the search is not an option. What about indices?

This article describes a possible solution and develops step-by-step a small example how you can use SQL and indices to search encrypted fields.

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A request came from a customer to estimate how long it would take to encrypt a database with cvencrypt utility.

This question is a little bit like how long is a piece of string — it depends. But its an interesting question. The answer primarily depends on the performance of CPU and storage on the target platform the customer is using, so the answer is more about coming up with a simple methodology that can be used to benchmark the CPU and storage while running cvencrypt.

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Asymmetric cryptography is a cryptographic system that uses pairs of keys: public keys which may be disseminated widely, and private keys which are known only to the owner. The generation of such keys depends on cryptographic algorithms based on mathematical problems to produce one-way functions. Effective security only requires keeping the private key private; the public key can be openly distributed without compromising security.

In such a system, any person can encrypt a message using the receiver's public key, but that encrypted message can only be decrypted with the receiver's private key.

Robust authentication is also possible. A sender can combine a message with a private key to create a short digital signature on the message. Anyone with the sender's corresponding public key can combine the same message and the supposed digital signature associated with it to verify whether the signature was valid, i.e. made by the owner of the corresponding private key. (C) Wikipedia.

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· Feb 24, 2017 1m read
Collision for SHA-1 hash algorithm

The recent announcement of a collision for the SHA-1 hash algorithm has caused some consternation:


Here is some background to help put this in perspective.

Cryptographic hash functions can have a variety of properties. The property at issue here is:

"Collision resistance - it is computationally infeasible to find any two distinct inputs x, x' which hash to the same output, i.e., such that h(x) = h(x')."

(Menezes, van Oorchot, and Vanstone, "Handbook of Applied Cryptography", section 9.2.2)

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In this article, we will establish an encrypted JDBC connection between Tableau Desktop and InterSystems IRIS database using a JDBC driver.
While documentation on configuring TLS with Java clients covers all possible topics on establishing an encrypted JDBC connection, configuring it with Tableau might be a little bit tricky, so I decided to write it down.

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Several steps should be done in order to secure the connection through xDBC clients to an IRIS Server instance using TLS. Most of the information can be obtained from the documentation about TLS on IRIS here, about configuring the security layer for encrypted connections. In the next paragraphs we will cover an step-by-step guide on how to configure and test the connection using SQL Clients apps using ODBC and JDBC.

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About regulations

Personal data privacy regulations have become an indispensable requirement for projects dealing with personal data. The compliance with these laws is based on 4 principles:

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IRIS can use a KMS (Key Managment Service) as of release 2023.3. Intersystems documentation is a good resource on KMS implementation but does not go into details of the KMS set up on the system, nor provide an easily followable example of how one might set this up for basic testing.

The purpose of this article is to supplement the docs with a brief explanation of KMS, an example of its use in IRIS, and notes for setup of a testing system on AWS EC2 RedHat Linux system using the AWS KMS. It is assumed in this document that the reader/implementor already has access/knowledge to set up an AWS EC2 Linux system running IRIS (2023.3 or later), and that they have proper authority to access the AWS KMS and AWS IAM (for creating roles and polices), or that they will be able to get this access either on their own or via their organizations Security contact in charge of their AWS access.

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