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In digital forensics, a chain of custody is the documented history of who possessed or handled an item of digital evidence, when transfers occurred and what actions were taken. It connects an analyzed item with its recorded collection and subsequent handling. The record concerns provenance and accountability, while data integrity concerns whether the relevant data changed.^[ref]

For an original example, an evidence drive is recorded as collected by A at09:00, transferred to B at10:00 and delivered to C at12:00. If B's receipt and transfer record are missing, matching serial numbers at the endpoints do not explain what happened during the intervening interval. That is a gap in documentation, not by itself proof of alteration.

A cryptographic hash function supplies complementary evidence about a particular byte sequence. A matching digest can support continuity of the data under the hash function's security assumptions, but does not identify everyone who had access to it. A complete custody log likewise cannot establish the truth of every statement stored on a device.

A useful record therefore distinguishes the physical item, any acquired copies and the actions applied to each. Conclusions should state what that record supports; documentation alone does not determine every question about an incident.

Digital evidence is information represented in digital form that is used to support or test a claim about an event. A file, system log or recorded computer network activity can supply such information. An artifact becomes evidence through its relation to a question and the explanation of how it was obtained and interpreted; being stored on a computer does not make its contents true.^[ref]

Digital forensics separates collection from analysis. Chain of custody documents handling, and cryptographic hash functions help check continuity of acquired data. Those checks support the reliability of a particular artifact; they do not by themselves establish its author or the cause of the recorded event.^[ref]

An original mathematical distinction is useful. For a fixed deterministic hash function $h$, if byte sequences $x$ and $y$ satisfythen $x\ne y$. Identical inputs must produce identical outputs. The converse fails: $h(x)=h(y)$ does not logically prove $x=y$, since a fixed-length digest can have collisions. A well-chosen cryptographic hash function makes finding such collisions computationally difficult under its stated security assumptions.

Even exact byte equality is narrower than factual truth. Two identical copies of a log preserve the same recorded assertion, including any inaccurate clock value or fabricated entry already present. Interpretation must connect the artifact to independent context and identify uncertainty.

Karen Kent is the first-listed author of the 2006 Guide to Integrating Forensic Techniques into Incident Response by Karen Kent and others. The guide connects digital forensics to investigating computer security incidents and operational faults, separating collection, examination, analysis and reporting.^[ref]

A technical distinction in that workflow is preserving data integrity while separately evaluating what collected data establishes. The guide describes comparing message digests of original and copied data.^[ref]

For an original counterexample, suppose two computer files contain the same two bytes, with hexadecimal values $41$ and $42$, but their recorded paths and creation times differ. A deterministic cryptographic hash function applied only to those content bytes returns the same value for both. That comparison does not establish equality of their file metadata, identify who created either file, or prove when an event occurred. The input being hashed determines what the comparison can support.

Thus integrity checks support the analysis rather than replacing it. This example is about the logical scope of a content hash, not an incident or experimental result reported by Kent.

Malware is software or code intentionally used for an unauthorized harmful purpose, such as disclosing data, altering it or disrupting access to a computing system. Computer viruses and computer worms are types of malware, but self-replication is not required for every malicious program. The classification concerns purpose and behavior, not merely whether a computer program contains a bug.^[ref]

A useful distinction separates what a program does from how it spreads. Replication, unauthorized disclosure and destructive changes are different properties. A computer worm can disrupt a system through replication-related resource use; another malicious program might disclose data without producing copies of itself.

For an original classification example, suppose three hypothetical programs produce the same unexpected loss of a test file. One has an accidental defect, one implements an authorized deletion request, and one intentionally deletes data without authorization. The visible outcome alone does not establish that all three are malware. Intended function, authorization and behavior supply different evidence.

Likewise, finding a familiar byte sequence in a file is a detection clue rather than a complete behavioral explanation. Digital forensics connects observed artifacts with supported conclusions; a label by itself does not reconstruct an incident.

Simson Garfinkel researches computer security, privacy and digital forensics. With Abhi Shelat, he studied whether used hard disk drives retained readable information after disposal or resale. Their 2003 paper transformed a general concern about confidentiality into an investigation of actual storage devices.^[ref]

The researchers acquired 158 drives between November 2000 and August 2002, recorded their provenance and examined copied device contents. Some drives were damaged or unreadable; others retained recoverable data. The paper distinguishes ordinary access through a file system from information remaining outside its live names and records. It also cautions that the sample does not establish a population-wide prevalence.^[ref]

An original storage example makes the distinction concrete. Suppose a toy file system holds a document in four 512-byte file data blocks. Removing its name from a file-system directory and marking those blocks reusable can leave all $4\times 512=2048$ content bytes unchanged. The file deletion changed live bookkeeping, while this stipulated model performed zero overwrites of the document's contents. Other file systems can behave differently, but disappearing from a directory listing alone does not prove data sanitization.

The experiment motivates testing a storage claim at the level it concerns: absence of a live filename and absence of recoverable former content are different observations.