One Way Hash Functions and Data Privacy Compliance.
This article will discuss how a one way hash function can be used in the context of privacy compliance for regulations like the GDPR. Storing customer’s personal data is an inevitability for scaling businesses in today’s technical world. One way hash functions are a useful tool to store sensitive customer data such as passwords and social security numbers in a blind manner that reduces your risk. We’ll talk about what one way hash functions are, why you should care, and their place in a data privacy compliance context.
The Information Security Challenge
We’ve all seen the headlines about high profile data breaches for sensitive customer data. These breaches are occurring at the highest level companies and information security companies themselves are not immune to targeting by hackers.
Since information security professionals largely find ways to protect against known attacks and hackers are constantly devising new attacks, hackers have the advantage. Because of this, application providers must a) assume that stored data will be breached and b) take appropriate steps to protect the data so that the impacts of a breach are minimized.
Enter the one way hash function.
About One Way Hash Functions
The graphic above illustrates how one way hash functions work. An arbitrary input, such as an email address or password, is provided and run through the hashing function and the result is a fixed-length alphanumeric string of characters.
The provided input will always result in the same fixed length set of characters but it is impossible to determine what the original input was because the encryption algorithm only goes one way.
This gives us a fantastic tool to store customers personal data in such a manner that the application provider has no knowledge of the originally provided input.
For example, lets say a fictitious user is logging in with a password “pass123”.
When the user registers with the password, it is run through a one way hashing function and the resulting hash code “x6y1otB” is generated.
The application provider stores this hash code in their database and has no knowledge of the original password. Yet, when the user attempt to login the next time, the original “pass123” hashes back to “x6y1otB” and we can confirm that they did indeed supply the correct password without ever knowing what it was.
This is a powerful protection in an information security sense because if a hacker was to gain access to the database and steal the stored passwords they will only see the hash codes that were stored and would not be able to decipher what the original password was.
This gives application providers a chance to inform users of a breach, lock out accounts and force password changes while the vulnerability is corrected. It saves a tremendous amount of hassle for the end consumer because their data remains far safer than if the password was stored in plain text and then was subsequently compromised.
If the password was stored in plain text, the hacker would have been able to login to the compromised user’s account and do far more damage.
Emerging Privacy Law
Savvy application providers have been implementing techniques likes this for several reasons.
- Reduces Liability
- Decreases Risk
- Increases Customer Satisfaction
- Decreases the Attractiveness of Attack to Hackers
Data privacy has become a hot topic over recent years and implementing information security is no longer just a tactic employed by top companies for their benefit of their consumers – it’s become a legal requirement.
Data privacy laws such as the GDPR and California Consumer Privacy Act rarely specify the exact solutions required for securing personally identifiable consumer information but they make it clear that efforts to secure customer information must be made, and documented, and must periodically be audited by an appointed data privacy officer within the organization.
As such, the one way hash function has become an important tool in the application providers belt to secure and process personal information.
About The Author
Hunter has more than 10 years’ experience in the software industry building and configuring software for companies such as American Express, Black Knight, Homes & Land, Verizon and more. Hunter earned his bachelor’s degree in Information Technology from Florida State University in 2009 and began his career consulting for Accenture out of the New York City office. After accruing significant experience working with Fortune 500 Clients on complex software projects as an analyst, he discovered his love for coding and building software. While practicing the craft he earned an MBA from Florida State in 2017. In 2018 he founded Tortoise and Hare Software to begin providing business value in digital consulting engagements to small and medium sized businesses and helping them along in their journey toward the Fortune 500. See LinkedIn fore more.
The accuracy principle states that controllers and processor should make reasonable efforts to ensure personal data is accurate. They must allow citizens to challenge the accuracy of data and take steps to rectify or erase the data associated with the challenge. Verification is sometimes needed to ensure data is accurate. Controllers and processors should consider the impact to the individual and whether they collected the data or the user provided it when determining appropriate verification steps. Organizations should document challenges and their responses thoroughly and in a timely manner. They should also document the thought process for determining whether personal data needs to be verified and the verification steps taken if necessary.
Data minimization is the concept of collecting the minimum amount of data needed to carry out the stated purpose and no more. When conducting a data minimization evaluation you must ensure that the data collected is adequate and relevant to your stated purpose as well as limited. The onus is on the organization to document compliance with this principle. We recommend documenting a review of this principle each time new personal data is collected or processed. Conduct at least an annual audit of personal data that has been collected or processed to ensure that changes in the business have not impacted compliance with the data minimization principle.
The GDPR’s purpose limitation principle constrains the use of personal data to the original purposes or those purposes compatible with the original purpose. There are a handful of pre-approved compatible purposes such as archiving purposes in the public interest, scientific and historical purposes, and statistical purposes. Under the GDPR, the burden falls on controllers and processors to document their purposes and reasoning behind them. These must be documented externally to be transparent to the end user, and internally with regular audits. Care must be taken when deciding a purpose is compatible with the original. An analysis must be conducted to determine compatibility and it’s a good idea to document the reasoning behind claiming a purpose is compatible with the original. Make sure to consider linkages to the original purpose, and consequences to the end user.
The first principle of the GDPR, Lawfulness Fairness and Transparency focuses mostly on the underlying reasons for collecting and processing personal information and how it will be used. It outlines the need for a lawful basis for processing and discusses the 6 bases for processing that have been identified. The bases of consent is the most recommend basis and organizations would do well to ensure they establish proper consent collection mechanisms. It ensures that data is collected fairly and that the collection does not present unjust injury to an individual or group of individuals, regardless of how many other individuals are unaffected. It ensures that organizations are being transparent in the way they inform their users on the type of information that is collected and the way it will be processed and used. The responsibility lies within the collecting organization to document compliance with principles of the GDPR. Establishing a process for documenting a lawful basis for processing, fairness, and transparency in collection will leave organization prepared for regulatory scrutiny, help avoid lawsuits and fines.
The General Data Protection Regulation (GDPR) and Data Protection Act of 2018 (DPA) are complex, in depth, complementary legal documents which act as a code of conduct for businesses involved in the processing of personal data. Henceforth these regulations will be referred to as the GDPR. There are many aspects of compliance with these regulations and the best place to keep up to date and understand aspects of compliance is the Information Commissioner’s Office’s (ICO) Guide to General Data Protection Regulation. This article highlights the aspects of compliance that SteadyHOPS provides.