When it comes to information security, no sector can be overlooked. Both private sector and intelligence data gathered by government agencies require care in their handling, storage, and transmission. And while there are a number of universally-accepted best practices for maintaining data confidentiality, the unique nature of information relevant to national interest necessitates additional measures.
Much of the work of information security is the result of policy and training, but tools like the Sertainty Data Privacy Platform also play a central role in securing data in both the public and private sectors.
What Is Intelligence Data?
Generally, intelligence data refers to any data gathered by intelligence operatives or agencies. This data can be collected for a variety of purposes, from predicting and mitigating potential threats to informing government policy and even military operations. This can include information about people, finances, transportation, infrastructure, or any other data that may be of use in a particular scenario.
Often, the identities of the agents gathering the data, as well as the methods used, are highly protected. This amplifies the need for airtight privacy, as each step of the process must remain strictly confidential, even from other agents within the organization.
Similarities Between Private and Intelligence Data Security
At its core, data privacy is a universal concern. Any organization, whether public or private, that gathers information relies on a certain level of exclusivity in order to make that data useful. Not only is secure data vital to making informed decisions, but it can also provide a business edge over the competition. Likewise, in many industries, information security protocols are required in order to obtain (and maintain) the licenses and certifications needed to conduct business.
When it comes to creating an organizational security policy in the modern world, there are a number of factors that need to be accounted for — whether you’re protecting private or intelligence data.
The foundation of any organization’s security plan, regardless of its industry, can’t be one-dimensional. A defense-in-depth approach combines multiple levels of security protocols into a single, cohesive privacy plan. This can include elements such as firewalls, encrypted networks, security training, and any other layer of protection.
Another vital piece of the puzzle in a comprehensive security plan involves user authentication. Users may be familiar with the process of imputing a code received on a separate device, but two-factor authentication can include even more secure measures, such as physical access keys, biometric scans, and answering security questions.
Remote Access Protocols
Unlike in the past, virtually all data storage networks need to be accessible to users outside of a specific office or closed LAN. This can apply to work-from-home employees and intelligence field operatives alike, and ensuring that only approved users can enter the system is vital. Furthermore, both of the above concepts around safeguards and encryption can and should play a role in how remote access protocols are designed.
Special Considerations for Intelligence Data
The above represent some of the most common security measures, all of which can be found in many civilian applications. Others, however, are less common outside of high-sensitivity industries.
There are two primary factors that make intelligence data different from other private information. For one, the potential implications of an intelligence data leak are far greater than those in any private company. Consequences can be felt on a national or even global level. This level of significance means that there is absolutely no room for mistakes of any kind.
The second factor is the need for multi-level confidentiality. As we mentioned above, in addition to the data itself, the identities, locations, and methods by which it was obtained are often extremely sensitive. Due to the need for internal privacy, conventional perimeter security is often insufficient.
Let’s take a look at some of the unique ways in which intelligence data can be protected, as well as examine the value of Zero-Trust security.
Perhaps the most critical element of intelligence data security strategies involves keeping different sources and stores of information separate from each other. The reasons that compartmentalization is so important are twofold. Firstly, even if one data store is compromised, compartmentalization ensures that the breach is contained to that single, limited store. The other primary benefit is that users have less potential to interact with each other, allowing for an increased level of anonymity.
Rather than relying on a secured messenger application, sending sensitive communications in the intelligence world is often handled using asymmetric access. In these types of systems, two virtual keys are needed to receive messages: one public key, findable within a database, and one private key, accessible to only a specific designated user. Sending messages can be done using a public key, but each user’s private key is needed to open the messages intended for them.
Sensitive Compartmentalized Information Facilities
In the most sensitive cases, extremely important data can only be accessed within the confines of a Sensitive Compartmentalized Information Facility (SCIF). To gain access to the information stored in these physical locations, users must be pre-screened and authorized, as well as pass through a series of checks and authentications. Once inside, they can access and discuss the information stored there but cannot send or receive any communications while they are in the facility.
Zero-Trust with Sertainty
In virtually every area we’ve discussed, traditional network security falls short in a number of key areas. Insider threats, human error, and a number of other inevitable vulnerabilities can leave information of all kinds open to malicious actors. Unlike other technology platforms, which are fundamentally limited in their scope, Sertainty data protection is ideal for both intelligence data and private applications.
Self-protecting data from Sertainty has redefined how information is protected to ensure data privacy even where firewalls fail. Using cutting-edge protocols and embedding intelligence directly into datasets, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised, data remains secure.