**3. Discussion**

We live in the age of modern information technology. Therefore, it should be fully assumed that we will work with accurate, correct, up-to-date data, which is stored


*Impact of Digital Vehicle Identification Errors on Critical Information Systems DOI: http://dx.doi.org/10.5772/intechopen.107888*

#### **Table 1.**

*Summary of basic VIN statuses identified during the correctness analysis.*

in information systems for various purposes—production, administrative, control, public transparency and efficiency, health and property protection, security, etc. It should also be assumed that data processing, including its acquisition (primary entry) into information systems in the public administration, will be supported by automated processes and modern technological means, which are already in common use in our everyday practice.

However, this is not the case in practice in the performance of state agencies (registers) working mainly with motor vehicles. There are objective and subjective reasons for this. The issue of vehicle registration as such is very specific in that there are a number of diverse manufacturers creating completely new products and global standardization in some areas (also related to registration practice) is not sufficiently flexible and at the same time not consistently observed. On the one hand, there is technological, major globalization in terms of technical or consumer aspects; on the other hand, the relevant legislation or standardization is also intended to be global (or at least pan-European), but its implementation is delayed by many years due to the adoption and implementation of European directives and regulations in national legislation.

In practice, the basic purposes of any systematic creation of various records and registers are often forgotten. In the past, every object entered into information systems was usually physically checked to ensure the quality of the information, especially key identifiers and other important characteristics.

The current registration processes, specifically in the case of motor vehicles, are only a "paper" matter as they are formally separated from each other. Vehicle registration is based only on the documents submitted, and there is a relatively large margin for error or even deliberate manipulation. In other words, one cannot, for example, technologically read the VIN by optically scanning its physical stamping from the vehicle body, read the VIN digitally from the vehicle control units, or scan the barcode. In the registration process, the vehicle is not physically present at the place of registration. This issue can theoretically be solved by carrying out quality technical inspections and vehicle originality checks that physically take place elsewhere and at different times. Unfortunately, even here the potential of optoelectronic or electronic (digital) technologies that are naturally available cannot be effectively used, because there is no standardized support for the uniform use of barcode or other technologies for recording VINs on vehicles, reading digital VINs from vehicles by manufacturers [31]. Not everyone uses barcodes or QR codes. There is no uniform device for reading (extracting) digital VINs from vehicle control units today that is capable of reading these values in general from all models that are at least simultaneously produced. For every manufacturer (manufacturing concern), it is necessary to have its proprietary technology available, which is not possible in independent inspection practice.

The basic research results obtained, presented in **Tables 1**–**3**, correspond to the practice of manual data acquisition and, at the same time, the lack of understanding of the seriousness of the vehicle identification issue in the design of the information system. The analysis shows that within the VIN item, 8.79 % percent of records do not


#### **Table 2.**

*Overview of error types in the VIN identifier. Decoded – the VIN identifier is error-free (91.21 % overall); Err – 8.79 % of VINs in the database are erroneous. Err – decoding errors.*

*Impact of Digital Vehicle Identification Errors on Critical Information Systems DOI: http://dx.doi.org/10.5772/intechopen.107888*


#### **Table 3.**

*Example of typical erroneous VIN entries. Users either write completely different information values into the database, unrelated to the VIN, or they copy only the first or last parts of the VIN.*

correspond to ISO standards imposed on this identifier. In other words, the error rate for the key identifier VIN is almost 9 %; i.e., one in 11 vehicles is problematic in terms of its unambiguous identification.

A closer analysis reveals that 5.48 % (4.15 + 0.04 + 1.29; see **Table 3**) of all the VINs are incorrect. This is due to the incorrect identifier length (different from the 17 standard characters) and the use of prohibited characters O, Q, and I. These characters must not be used in the VIN structure in order to avoid optical confusion of character pairs such as 0-O, 0-Q, I-J, and I-1, because then the object of interest cannot be found correctly in the search. The analysis also shows (see **Table 3**) that, in practice, data is entered in the VIN entry, items which have a completely different predictive value and certainly do not belong in the VIN entry. Clerks enter various official numbers and file marks. In numerous cases, this includes shortening (front or back) the VIN, usually to only 6–8 positions, because the official thinks that this sequence (reminiscent of the pre-1986 body serial number entries) is sufficient to identify a vehicle. This issue is trivially solvable at the level of information system design because it is sufficient to check the length of the VIN identifier for 17 positions and for the forbidden characters O, Q, and J. Records that do not meet these criteria must be brought to the attention of the information system operator, and such records must not normally be entered into the computer database. This type of error is of an objective nature (incorrect design of the functionality of the information system) and can be corrected retrospectively at minimal cost so that further errors do not occur.

The analysis also shows that an additional 3.31 % of all the VINs are erroneous, and the errors are due to human factors [32–34], in particular fatigue, inattention of an unintentional nature and possible fraudulent behavior [35] to change the vehicle identity [36]. A single character of the 17-digit VIN can be mistyped or misspelled, and a new "artificial" or fictitious VIN is created, which either does not formally exist or belongs to a completely different vehicle. These errors can only be eliminated by using the check digit mechanism in the VIN and/or by checking the inserted VIN

using so-called VINdecoders which check the VIN structure. As such, the VIN check digit mechanism only works in full if vehicle manufacturers in a given country are legally obliged to have this mechanism built into the vehicles they sell. An example is the USA. In Europe and other continents, there it is then necessary to use suitable VINdecoders that operate in real time.
