I had a Routine Medical Thing yesterday which required me being hooked up to a bunch of monitors for heart rate, blood pressure, etc. for a while. All very good. I don’t know for sure, but I assume that all that data was filtered down and then streamed into my digital medical record at the hospital. (If it wasn’t, that is a terrible waste, but not germane for the moment.)

Anyway seeing the monitors collecting “bedside data” as it is apparently called put me in mind of a presentation I saw a few weeks ago at a management meeting for Red Hat. The presenter had developed an alerting system that looks at bedside data and guesses whether a patient might be starting to develop sepsis, the often-fatal blood infection that is one of the big risks of spending any time in the hospital. If you catch sepsis early it’s easy to treat, but in a matter of a half a day it becomes life threatening. So an automatic alert to the nursing station not only saves nurses time, but also patients’ lives.

Of course systems like this have to run inside of a hospital’s network, because patient data has to be kept private (due to HIPAA, and also common sense to be honest). So the sepsis alert system has to run inside each hospital and be hooked up directly to whatever data stream the vendor who supplies the bedside systems makes available. This of course makes it difficult or even impossible to correlate any of this data across hospitals for research. It also means the hospitals themselves, who are in fact in the business of collecting huge amounts of this kind of data — MRI scans, DNA sequences (soon), bedside data logs — are completely overwhelmed. They are generating huge amounts of data and have nowhere to put it.

We are doing a whole bunch of work at Red Hat Research and Boston University in this area — there is lots of good thinking on ways to gain useful knowledge from data, without breaking the privacy of the data’s owner. Ultimately though I think what will happen is a shift in thinking about data ownership, data encryption, and data use. I think this will be generational, to be honest. So-called “Millenials” famously do not care who knows what about them, or so it is claimed. My nephew Sam, however, who is at fifteen part of the generation after that, refuses to get a Facebook account. Why? “They collect everything about you, it’s creepy AF,” he says. (I’ll let you work out for yourselves what “AF” means.) I’m told his opinion is common among his peers, and if it is it means that we will shortly run into a real demand for personal encryption, anonymity, and control over what can be collected and released. The days of services randomly collecting whatever tracking data they like, by whatever means they wish, will seem as naive in twenty years as cars without seat belts do today.

There are practical issues to be dealt with here, of course — if my bedside monitoring data belongs to me, how do I control who gets to see it? What if I’m unconscious? In reality though we need to deal with all these kinds of things anyway. As with all technology, the ability to do things leaps well ahead before society catches up.

I spent yesterday in a workshop with a bunch of very smart folks who spend their days trying to break things. You can debate at some length the ethics of this behavior, but that’s not really the point as far as I’m concerned. What really struck me in the workshop was humanity’s ability to create astonishingly complex systems, and our corresponding inability to understand them fully. Complexity carries a cost, as it turns out, and the full bill is rarely apparent until we are well down the road.

Our keynote speaker at the workshop was Daniel Gruss, a professor from the Graz University of Technology in Austria. I’ve come to know Daniel a bit since he and a separate team led by Daniel Genkin at the University of Michigan simultaneously found the Meltdown and Spectre exploits which were published back in January 2018. Daniel’s sly smile when he presents on these topics — he appears to find it all highly amusing — belies his real concern over these vulnerabilities and the systems and institutions that keep producing them.

Here is the link to Daniel’s talk at the workshop. It’s worth watching.

The key thing to understand about micro-architecture vulnerabilities, and in fact many IT security issues, is that they come about in response to customer demand for features and performance. Spectre, in particular, is only possible because processor makers long ago introduced a feature called “speculative execution,” which to be honest is an amazing feat of technology in and of itself. What speculative execution actually does is use free processor time to guess what a program is going to do next, before it actually does it. This works because the time required to retrieve data from system main memory is so much larger than the time required to execute a few instructions that may not be needed. When speculative execution wins, it is because the processor has already executed some code that turns out to have been the right code once the data from slow memory comes back. When it loses, it is because the data points down the other code path, in which case the processor throws away the results of its gamble and continues as if nothing had happened. It turns out the processor guesses right often enough that this feature results in major performance gains, with the result that it is present in all modern CPUs.

The downside of speculative execution is that when the processor guesses wrong, it can leave orphaned data in the processor cache until it is cleaned up later. A determined attacker can use this fact to read data she shouldn’t be able to read, including things like your encryption keys and your password. This is called a “side-channel attack” because it relies on a side effect of normal processing — the abandoned data in the cache — rather than a direct vulnerability in the program that is running.

It is important to note that this kind of attack is significantly harder to carry out than a simple phishing expedition that fools users into typing their username and password somewhere they shouldn’t. The fact that it is possible to learn private facts without first breaking into a system should be scary for large institutions — governments, banks, the large cloud providers — but less so for an average person with a laptop and a phone. Nonetheless, it is a real vulnerability, and although operating system vendors like Red Hat have done heavy work making it harder to exploit, the vulnerabilities are on the chip and there is only so much that can be done to mitigate them. What’s worse is that chipmakers don’t seem to be in any rush to produce real fixes to the problem, and they justify this by saying — accurately — that customers don’t care. Even large institutions with lots to lose are more interested in chasing performance than in protecting their data (or, more importantly, that of their citizens or their customers).

There is another important piece of this puzzle that Daniel (and other security researchers) are passionate about. With one notable exception that I will touch on in a moment, all processors are based on proprietary designs which are guarded very closely. This might not be a problem if processors were simply engines designed to churn through programming instructions in a linear way, but they are far more complex than this. The speculative execution and predictive branching features I mention above are only one of hundreds or even thousands of complex subsystems on the chip, all there to improve performance, none well documented. Daniel and the rest of the security community do their work by sniffing in the dark, trying to guess where a vulnerability might lie. They do this because if they find a vulnerability and tell everyone about it, we can hopefully prevent it being used against us by adversaries with bad intent. There is no doubt that these adversaries exist in government, organized crime, and elsewhere, and that the researchers they employ are every bit as skilled as Daniel, and that when they find a way to break into a system they are not going to be telling the press about it. So the processor makers, by keeping their designs and the security vulnerabilities inherent in them private, expose all of us to an unknown, unquantifiable risk.

I mentioned an exception. It turns out that there is a growing open-source community around a freely available Instruction Set Architecture called RISC-V. An Instruction Set Architecture is simpler than it sounds — it is essentially the set of instructions that a processor is guaranteed to implement. (The Intel ISA we have been using since the IBM PC came out is called the x86 architecture.) Anyone is free to take the RISC-V ISA and build a processor design that implements it, and in fact several folks in academia and industry are using the RISC-V ISA to design processors. Some processor designs are themselves open sourced like BlackParrot (BU/UW), Rocket (U C Berkeley), SweRV (Western Digital) and Ariane (ETH Zurich). Ideally these groups would open source not just the design but also the toolchain and the physical tools that they use to build the actual chips — but one step at a time.

Now, RISC-V, in order to be relevant, has to have optimizations that can compete with the proprietary chipmakers’ designs, which means it too will certainly have vulnerabilities. (Daniel Gruss is fond of saying that every optimization introduces an opportunity for a security flaw.) The difference is that with RISC-V everyone can see them. So, even though these are incredibly complex systems and it is unlikely that even a very skilled engineer can understand the entire thing all at once, it is possible that a community of people working together can do real analysis that will mitigate all kinds of security flaws… and that, in turn, will allow customers to understand exactly what security they are giving away in order to get better performance.

Daniel Genkin, the Spectre researcher at U of M, spends a lot of time talking about how we need to stop talking about security as an all-or-nothing thing, and instead start talking about it in terms of contracts. Something like “This chip has these performance characteristics, and also limits speculative execution to these kinds of safe operations or this kind of non-private data.” You can imagine that this would at last let customers start making intelligent decisions about how to spend their purchasing dollars. I suspect that as the world becomes home to more processor types and architectures, that processor makers will start offering these kinds of tradeoffs — especially if their chips are based on an open design where they can actually show buyers what they’re getting. Operating in this way won’t eliminate vulnerabilities, by any means, but it would at least let us say we’re trying.

UPDATE: I missed an important part of what RISC-V is — it is an ISA, not a processor design. There are a number of open-source processor designs that implement the RISC-V ISA.