# Investigation of Smart Machines with DNAs in SpiderNet
## 3 Methodology and Material
### The Network Structure & DNA  
IoT devices come in a wide variety of forms, with diverse hardware configurations, software systems, designs, and functions, ranging from mobile phones to robots. Each device includes distinct physical identifiers such as manufacturer details, model numbers, serial numbers, SIM card data, and more. In the SpiderNet framework, these identifying features are referred to as \"genes\", with the complete set of these genes called DNA. Figure 2 illustrates the structure of a typical DNA, as adapted from [11; 29]. \(n\)DNA, or nested DNA (shown in Figure 2), refers to DNA structures within a parent device DNA. A primary DNA may contain one or more \(n\)DNAs, indicating devices connected to it. The \(n\)DNA structure resembles that of the parent DNA. For example, a wheelchair or Bluetooth device like speakers might be linked to a Smart IoT machine that manages these \"extra devices\". The \(n\)DNA would indicate that such a connection has been established. This will provide a thorough investigation when several devices have been used in the same colony. This concept can also apply to an investigation within an organisation. A company's network server could serve as the primary DNA, while connected devices such as computers, phones, and other employee devices would be part of the \(n\)DNAs. The  
Figure 2: DNA structure for IoT devices and users. network structure would link to employees and their specific device DNA within the organisation's network. A device DNA can be classified into two types of genes--immutable or permanent genes (_i_Dna), which do not change and include attributes like serial numbers, model numbers, or vehicle identification numbers, and mutable or temporary genes (_m_Dna), which relate to the current owner, user, or operator of the device. For instance, when a car is transferred to a new owner, the mutable genes update to reflect the new user's information. Country servers managing the DNAs of various devices use alert flags to indicate the status of each DNA. These alert flags grouped within a scoreboard (sB) are mutable and convey essential information, such as whether a DNA has reached its end of life and should be deleted, whether it contains illegal content requiring law enforcement action, if it has been duplicated by hackers, if it is set up for preventive forensic investigations (indicating if immediate police involvement is necessary), and if a court order is required for jurisdictional rules. A simplified version of DNA and its associated scoreboard (sB) is outlined below using the formal specification language [30]--refer to the syntax in Appendix A. The device DNA and its associated scoreboard data structure are formatted as dictionaries, with keys representing mutable and immutable genes, while the keys of the scoreboard refer to the alert flags. \[\begin{split} Dna=&\text{\text{\text{\text{\text{ \text{\text{\text{\text{\text{\text{\text{\  
and spatial DNA (sDNA), representing the location and physical parameters where the device is situated. The user DNA is modelled as a dictionary of nested DNAs.  
\[u\text{Dna}=<\!\!\text{$p$Dna}=<\!\!\text{fp:}\ldots\!>,b\text{Dna}=<\!\!\text{ks: }\ldots\!>,\text{sDna}=<\!\!\text{loc:}\ldots,\text{ip:}\ldots\!> \tag{2}\]  
Physiological biometrics are generally more reliable and stable than behavioural biometrics; however, they may also change due to factors like injury or surgery. This framework suggests that fingerprints, facial recognition, iris, and retina scans be integrated into the physiological authentication for SpiderNet. Fingerprints, widely used in everyday devices, provide secure identification, with further potential for incorporating ear or palm print recognition as unique authentication factors. Facial recognition offers additional security by distinctly identifying users and saving images of individuals accessing the system.