Why it matters

GeneticSecurity.org studies the security, privacy, integrity, provenance, persistence, and resilience of genetic material, genomic data, genomic infrastructure, and genetic resources.

Privacy is one part of this field. An altered reference dataset, unavailable laboratory system, mislabeled specimen, or lost seed accession can create a security failure without any disclosure. This framework follows the asset across physical, digital, and institutional boundaries.

Seven dimensions of genetic security

Confidentiality

Who can see or obtain genetic material or genomic information?

Integrity

Can samples, data, pipelines, or interpretations be altered, substituted, contaminated, or corrupted?

Availability

Can legitimate users access critical genomic systems and data when needed?

Provenance

Can the origin, custody, transformations, and analytical history of a genetic asset be verified?

Consent

Was this particular collection, analysis, sharing, inference, or retention authorized?

Persistence

What happens when a compromised biological identifier cannot realistically be replaced?

Relational Exposure

What becomes inferable about relatives, communities, populations, or genetic-resource networks?

Six domains

Genetic material

Blood, saliva, tissue, hair, cells, discarded material, stored specimens, biobanks, germplasm, and microbial collections.

Genomic data

Raw sequence reads, FASTQ, BAM/CRAM, VCF, SNP profiles, reports, databases, cloud copies, backups, and exports.

Genomic infrastructure

Sequencers, laboratory networks, LIMS, workstations, clusters, APIs, maintenance paths, dependencies, and reference datasets.

Genetic privacy

Consumer genetics, consent, secondary use, genealogy, brokerage, law-enforcement access, retention, and group privacy.

Genetic intelligence and inference

Kinship, ancestry, phenotype, identity, population inference, risk prediction, and AI-assisted analysis.

Genetic resources

Seedbanks, plant germplasm, livestock genetics, biodiversity repositories, and agricultural resource continuity.

Genetic security lifecycle

  1. Collect
  2. Identify
  3. Sequence
  4. Process
  5. Store
  6. Analyze
  7. Share
  8. Infer
  9. Preserve / retire

At each stage, ask who can act, which purpose permits the action, what evidence records the transformation, and what remains recoverable.

Analytical concepts

Begin with the asset, then follow its uses

Imagine a research participant giving a saliva sample. The collection tube is one asset. The sequence file produced from it is another. A report, a backup, and a relationship inferred from that file each create a different security question. Protecting the tube does not automatically protect the report, and deleting the report does not necessarily dispose of the sample.

This hypothetical example explains why the field needs more than one perspective. A laboratory may be responsible for specimen identity, a computing team for access controls, and a research team for permitted uses. The handoffs between those teams deserve as much attention as the individual systems. A useful review follows the same sample through collection, analysis, sharing, and eventual disposal or preservation.

Three questions to ask first

What exactly is being protected? “DNA” can mean a physical specimen, a few measured markers, a sequence dataset, or a conclusion drawn from an analysis. Naming the asset avoids treating all of these as interchangeable.

Who could be affected? Start with the specimen source or account holder, then consider relatives, a defined community, or the users of a genetic resource. Describe the connection before estimating its reach. Shared biology creates possible relationships; it does not establish that every relative has suffered harm.

What would a successful safeguard preserve? Sometimes the aim is confidentiality. In other cases, it is the ability to prove that a result belongs to the right specimen, recover a laboratory service, or preserve a unique accession for future use. A clear answer makes the choice of controls easier to explain and evaluate.

Cornerstone reading

Evidence and classification methodology

Case families