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schneierB. SchneierSCHNEIER:A7B25D2C5A43BA70F51844062D44F458
HistoryNov 08, 2023 - 12:08 p.m.

Decoupling for Security

2023-11-0812:08:09
B. Schneier
www.schneier.com
16
decoupling
security
cloud services
privacy
least privilege
data protection
data in motion
data at rest
data in use
organizational decoupling
functional decoupling
risk management
cloud threat prevention

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AI Score

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This is an excerpt from a longer paper. You can read the whole thing (complete with sidebars and illustrations) here.

Our message is simple: it is possible to get the best of both worlds. We can and should get the benefits of the cloud while taking security back into our own hands. Here we outline a strategy for doing that.

What Is Decoupling?

In the last few years, a slew of ideas old and new have converged to reveal a path out of this morass, but they haven't been widely recognized, combined, or used. These ideas, which we'll refer to in the aggregate as "decoupling," allow us to rethink both security and privacy.

Here's the gist. The less someone knows, the less they can put you and your data at risk. In security this is called Least Privilege. The decoupling principle applies that idea to cloud services by making sure systems know as little as possible while doing their jobs. It states that we gain security and privacy by separating private data that today is unnecessarily concentrated.

To unpack that a bit, consider the three primary modes for working with our data as we use cloud services: data in motion, data at rest, and data in use. We should decouple them all.

Our data is in motion as we exchange traffic with cloud services such as videoconferencing servers, remote file-storage systems, and other content-delivery networks. Our data at rest, while sometimes on individual devices, is usually stored or backed up in the cloud, governed by cloud provider services and policies. And many services use the cloud to do extensive processing on our data, sometimes without our consent or knowledge. Most services involve more than one of these modes.

To ensure that cloud services do not learn more than they should, and that a breach of one does not pose a fundamental threat to our data, we need two types of decoupling. The first is organizational decoupling: dividing private information among organizations such that none knows the totality of what is going on. The second is functional decoupling: splitting information among layers of software. Identifiers used to authenticate users, for example, should be kept separate from identifiers used to connect their devices to the network.

In designing decoupled systems, cloud providers should be considered potential threats, whether due to malice, negligence, or greed. To verify that decoupling has been done right, we can learn from how we think about encryption: you've encrypted properly if you're comfortable sending your message with your adversary's communications system. Similarly, you've decoupled properly if you're comfortable using cloud services that have been split across a noncolluding group of adversaries.

Read the full essay

This essay was written with Barath Raghavan, and previously appeared in IEEE Spectrum.

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AI Score

Confidence

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