How digital forensics relates to computing

A lot of people are aware that there is some inherent connection between digital forensics and computing. I’m going to attempt to explain my understanding of how the two relate. However before we dive into digital forensics, we should clear up some misconceptions about what computing is (and perhaps what it is not).

Ask yourself the question “What is computing?” When I ask this question (or some related variant) to folks, I get different responses ranging from programming, to abstract definitions about Turing machines. Well, it turns out that in 1989 some folks over at the ACM came up with a definition that works out quite well. The final report titled “Computing as a Discipline” provides a short definition:

The discipline of computing is the systematic study of algorithmic processes that describe and transform information … The fundamental question underlying all of computing is, “What can be (efficiently) automated?”

This definition can be a bit abstract for those who aren’t already familiar with computing. In essence, the term “algorithmic processes” basically implies algorithms. That’s right, algorithms are at the heart of computing. A (well defined) algorithm is essentially a finite set of clearly articulated steps to accomplish some task. The task the algorithm is trying to accomplish, can vary. So computing is about algorithms whose tasks are to describe and transform information.

When we implement an algorithm on a computing device, we have a computer program. So a computer program is really just the implementation of some algorithm for a specific computing device. The computing device could be a physical machine (e.g. an Intel architecture) or an abstract model (e.g. Turing machine). When we implement an algorithm for a specific computing device, we’re really just translating the algorithm into a form the computing device can understand.Β  To help make this more concrete, take for example Microsoft Word. Microsoft Word is a computer program, it’s a slew of computer instructions encoded in a specific format. The computer instructions tell a computing device (e.g. the processor) what to do with information (the contents of the Word document). The computer instructions are a finite set of clearly articulated steps (described in a format the processor understands) to accomplish some task (editing the Word document).

There is one other concept to deal with before focusing on digital forensics, and that is how algorithms work with information. In order for an algorithm to transform and describe information, the information has to be encoded in some manner. For example, the letter “A” can be encoded (in ASCII) as the number 0x41 (65). The number 0x41 can then be represented in binary as 01000001. This binary number can then be encoded as the different positions of magnets and stored on a hard disk. Implicit in the structure of the algorithm, is how the algorithm decodes the representation of information. This means that given just raw the encoding of information (e.g. a stream of bits) we don’t know what information is represented, we still need to understand (to some degree) how the information is used by the algorithm. I blogged about this a bit in a previous post “Information Context (a.k.a. Code/Data Duality)“.

So how does this relate to digital forensics? Simple, digital forensics is the application of knowledge of various aspects of computing to answer legal questions. It’s been common (in practice) to extend the definition of digital forensics to answer certain types of non-legal questions (e.g. policy violations in a corporate setting).

Think for a moment about what we do in digital forensics:

  • Collection of digital evidence: We collect the representation of information from computing devices.
  • Preservation of digital evidence: We take steps to minimize the alteration of the information we collect from computing devices.
  • Analysis of digital evidence: We apply our understanding of computer programs (algorithmic processes) to interpret and understand the information we collected. We then use our interpretation and understanding of the information to arrive at conclusions, using deductive and inductive logic.
  • Reporting: We relate our findings of the analysis of information collected from computing devices, to others.

Metadata can also be explained in terms of computing. Looking back at the definition for the discipline of computing, realize there are two general categories of information:

  • information that gets described and transformed by the algorithm
  • auxiliary information used by the algorithm when the steps of the algorithm are carried out

The former (information that gets described and transformed) can be called “content”, while the latter (auxiliary information used by the algorithm when executed) can be called “metadata”. Viewed in this perspective, metadata is particular to a specific algorithm (computer program) and what is content to one algorithm could be metadata to another.Again, an example can help make this a bit clearer. Let’s go back to our Microsoft Word document. From the perspective of Microsoft Word, the content would be the text the user typed. The metadata would be the font information and attributes, revision history, etc. So, to Microsoft Word, the document contains both content and metadata. However, from the perspective of the file system, the Word document is the content, and things such as the location of the file, security attributes, etc. are all metadata. So what is considered by Microsoft Word to be metadata and content is just content to the file system.

Hopefully this helps explain what computing is, and how digital forensics relates.


  1. Hello,
    Thank you for another excellent post..very informative
    waiting for the next πŸ™‚

  2. Cool, thanks. I’m working on the next one, although not sure when it’s going to be done πŸ™‚

  3. Recently stumbled upon this site whilst writing a report for my computer forensic class and very pleased that I did. Really easy to understand and very informative. I have a lot of reading to get done πŸ™‚ Keep up the good work!

  4. Cool, let me know if you have any questions πŸ™‚

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