Forensic evidence is useful in helping solve the most violent and brutal of cases, as well as completely nonviolent cases related to crimes such as fraud and hacking. Investigators use forensic toxicology to determine whether a driver was impaired at the time they were involved in an accident.

Computer forensics is also important because it can save your organization money. From a technical standpoint, the main goal of computer forensics is to identify, collect, preserve, and analyze data in a way that preserves the integrity of the evidence collected so it can be used effectively in a legal case.

It is important to secure the crime scene because anyone that isn’t a trained professional can possibly contaminate or even destroy the evidence. Usually when investigators secure the area, it is made larger than the crime scene to make sure they did not miss any sort of evidence.

It provides a permanent record of the crime scene as it was when it was discovered and thus helps remind officers and witnesses of important details that would otherwise be forgotten. Documentation such as this also records evidence that might later be lost, stolen, or destroyed during recovery or transportation.

That all depends. The general rule is that if it can become dislodged, blown away, lost or destroyed from whatever it is attached to, it’s better to collect and seal it in a separate and correctly labeled evidence envelope or container.

Internal investigations – the three C’s – confidence. credibility. cost.

There are four phases involved in the initial handling of digital evidence: identification, collection, acquisition, and preservation ( ISO/IEC 27037 ; see Cybercrime Module 4 on Introduction to Digital Forensics).

In order to ensure the authenticity of electronic evidence, four issues should be paid attention to in the collection of electronic evidence in cybercrime: collect strictly according to law, collect electronic evidence comprehensively, invite electronic experts to participate, and ensure the privacy rights of the …

Additional digital evidence can be extracted by analyzing the content of computer’s RAM, the PC’s volatile operating memory. Generally speaking, the PC should be powered on in order to perform Live RAM analysis.

A complete examination of a 100 GB of data on a hard drive can have over 10,000,000 pages of electronic information and may take between 15 to 35 hours or more to examine, depending on the size and types of media.

The first step in any forensic process is the validation of all hardware and software, to ensure that they work properly.

The first digital forensic process model proposed contains four steps: Acquisition, Identification, Evaluation and Admission. Since then, numerous process models have been proposed to explain the steps of identifying, acquiring, analysing, storage, and reporting on the evidence obtained from various digital devices.

• Identification. First, find the evidence, noting where it is stored.
• Preservation. Next, isolate, secure, and preserve the data.
• Analysis. Next, reconstruct fragments of data and draw conclusions based on the evidence found.
• Documentation.
• Presentation.

Forensic investigation is the gathering and analysis of all crime-related physical evidence in order to come to a conclusion about a suspect. Investigators will look at blood, fluid, or fingerprints, residue, hard drives, computers, or other technology to establish how a crime took place.

If the domain of computer forensic functions is known and the domain of expected results (i.e. requirements of each function) are known, that is, the range and specification of the results, then the process of validating any tool can be as simple as providing a set of references with known results.

Common types of data validation checks include:

• Data Type Check. A data type check confirms that the data entered has the correct data type.
• Code Check. A code check ensures that a field is selected from a valid list of values or follows certain formatting rules.
• Range Check.
• Format Check.
• Consistency Check.
• Uniqueness Check.

Different categories of the data validation methods. As depicted in Figure 2, the faulty data detection methods, used to detect failures on the sensors’ signal, may include ANNs, dimensional reduction methods, instance based methods, probabilistic and statistical methods, and Bayesian methods.