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Industry Espionage as a Service? In my old university, the people working on the genome studies had to sign a draconian NDA and they had a dedicated air-gapped

Industry Espionage as a Service? In my old university, the people working on the genome studies had to sign a draconian NDA and they had a dedicated air-gapped compute cluster for it. If your genomics study can produce a patent for a new diagnostic method or maybe even a drug precursor molecule, that'll be way more valuable than everything you spent on security. And already 8 years ago, hacking attempts by what was thought of as foreign government actors was a common experience in life science research. When I had to give a talk about our methods, we scrambled all the gene IDs for fear of the slides getting leaked. So based on how people working in that field behave, I presume they would never ever agree to upload the data to servers outside of their control. Accordingly, I can only imagine this service to be used accidentally by inexperienced students (who are then on the hook for violating their NDA).

rswail 5y ago
If you don't believe AWS's attestations about their security encryption and customer isolation and the associated certifications, then agreed, you shouldn't be sharing your data. That restricts you to your own infrastructure then. There are tradeoffs in both directions.
IAmEveryone 5y ago
I worked at a Max Planck genetics lab and never saw an NDA, or even any reference to the notion of keeping anything secret. The are also dozens of online databases for all sorts of data from biology. Reading between the lines, you seem to attach certain ideas to the term „genetics“?
- dekhn 5y ago
  they're talking about clinical trials with PII, and some associated genetic sequencing data.
dekhn 5y ago
whoever set up your system was overly paranoid. there are exabytes of PII in Amazon now. Air gapping was never a good security method.
reacharavindh 5y ago
I have administered an HPC cluster for a research group working on genetics and genomics. There was some data that was the “secret sauce” mostly because it was curated over a long period of time with industrial collaborators and bound by several agreements that it would be a huge task in itself to navigate the proper permissions to ever release them publicly. The default policy was to consider all of them secret and available only on a project need basis for researchers closely associated with the institute. Now, it is technically possible to have this data in AWS with assurances of encryption and some sane security measures like not leaving it open to public. However, the big catch is - the compute part of the cluster is on-premise. We did the math of moving the compute to AWS, and it was several orders of magnitude expensive(consider that the group did not need to pay for power, network links, and maintenance of the server room by virtue of being part of the university). The only “extra cost” of being on-premise was my salary, which is substantially small portion of the increase by going to AWS. Also, guess what going to AWS doesn’t magically eliminate the need for a guy whose responsibility it is to ensure the cluster is operated, and for users to come in for help, and to manage the ecosystem in general. The argument of moving to the cloud is more complicated than it appears on the surface. I believe the HPC shops that have a lot of compute and very little need for elasticity will be the last to head to the cloud.
- zmmmmm 5y ago
  You have to take into account the structure of academic research funding as well: grant based with typical horizon of 1-3 years and then funding runs out. If you put all your data in the cloud, who is going to be paying for the "forever-costs" of storage, egress etc after you grants are gone? For researchers this typically comes "for free" with their institutional infrastructure while for cloud it introduces tremendous uncertainty because typically they are required to preserve data supporting publications etc, effectively forever while few grants actually fund that.

rswail 5y ago

If you don't believe AWS's attestations about their security encryption and customer isolation and the associated certifications, then agreed, you shouldn't be sharing your data. That restricts you to your own infrastructure then. There are tradeoffs in both directions.

IAmEveryone 5y ago

I worked at a Max Planck genetics lab and never saw an NDA, or even any reference to the notion of keeping anything secret. The are also dozens of online databases for all sorts of data from biology. Reading between the lines, you seem to attach certain ideas to the term „genetics“?

dekhn 5y ago
they're talking about clinical trials with PII, and some associated genetic sequencing data.

dekhn 5y ago

whoever set up your system was overly paranoid. there are exabytes of PII in Amazon now. Air gapping was never a good security method.

reacharavindh 5y ago

I have administered an HPC cluster for a research group working on genetics and genomics. There was some data that was the “secret sauce” mostly because it was curated over a long period of time with industrial collaborators and bound by several agreements that it would be a huge task in itself to navigate the proper permissions to ever release them publicly. The default policy was to consider all of them secret and available only on a project need basis for researchers closely associated with the institute. Now, it is technically possible to have this data in AWS with assurances of encryption and some sane security measures like not leaving it open to public. However, the big catch is - the compute part of the cluster is on-premise. We did the math of moving the compute to AWS, and it was several orders of magnitude expensive(consider that the group did not need to pay for power, network links, and maintenance of the server room by virtue of being part of the university). The only “extra cost” of being on-premise was my salary, which is substantially small portion of the increase by going to AWS. Also, guess what going to AWS doesn’t magically eliminate the need for a guy whose responsibility it is to ensure the cluster is operated, and for users to come in for help, and to manage the ecosystem in general. The argument of moving to the cloud is more complicated than it appears on the surface. I believe the HPC shops that have a lot of compute and very little need for elasticity will be the last to head to the cloud.

zmmmmm 5y ago
You have to take into account the structure of academic research funding as well: grant based with typical horizon of 1-3 years and then funding runs out. If you put all your data in the cloud, who is going to be paying for the "forever-costs" of storage, egress etc after you grants are gone? For researchers this typically comes "for free" with their institutional infrastructure while for cloud it introduces tremendous uncertainty because typically they are required to preserve data supporting publications etc, effectively forever while few grants actually fund that.