# Investigation of Smart Machines with DNAs in SpiderNet
## 3 Methodology and Material
### SpiderNet, Legislation and the Future  
The case studies discussed above highlight instances wherein machine system errors endangered human lives, making it challenging to determine fault. While the driver in Section 4.3 pleaded guilty, it could be argued that the user relied on a self-driving car system that was expected to function properly. The other two cases have not provided significant information regarding the malfunctions beyond device inspections, raising questions about who should be held accountable when smart machines cause harm, whether accidentally or as tools of malicious intent.  
In 2020, the European Parliament passed a legislative resolution focused on establishing a liability regime for high-risk AI systems. This led to the European Commission's 2022 proposal for the AI Liability Directive, which includes rules aimed at protecting humans in the event of damages caused by AI systems, while easing the burden of proof for victims. Additionally, the Commission proposed the Product Liability Directive, which deals with no-fault liability for producers and manufacturers [39]. In the UK, Lord Chancellor [PERSON] signed an international treaty on AI risks, agreed upon by the Council of Europe, which outlines measures to manage AI products and prevent their misuse in order to protect society [40].  
These proposals and treaties underscore the need for AI systems and connected smart machines to be monitored through a unified framework like SpiderNet, which enables preventative forensics before harm is caused to humans or society.  
This research aims to develop a forensic framework that will transform how smart machines are investigated, providing protection against tampering and ensuring the reliability of digital evidence by analysing the behaviour, positions, and objectives of these machines. With the increasing prevalence of smart devices, there is a growing need for secure networks such as SpiderNet to continually evolve, preventing crime and improving forensic  
Figure 6: Storage evolution for 5 devices with a random radius between 10 and 100 m.  
investigations. Smart machines can be exploited for malicious purposes, including altering timing, deleting evidence, or committing crimes remotely--such as detonating bombs. Traditional forensic methods, relying on tools like network monitoring or cloud-based logs, are susceptible to tampering, as evidence can be altered or deleted by unauthorized access.  
The proposed SpiderNet framework addresses these vulnerabilities by ensuring that evidence and timestamps cannot be accessed or deleted by unauthorized users. Only registered law enforcement agencies would have read-only access to this data, preventing contamination and preserving the integrity of collected evidence. This framework supports evolving policies, manufacturing standards, and development strategies for smart machines.  
Furthermore, SpiderNet includes a proactive mechanism capable of detecting potential crimes in advance through technological intelligence, alerting authorities, and potentially deactivating compromised devices. By requiring a constant internet connection for syncing and data updates, this system serves as a foundational platform for future research, offering a new approach to investigating crimes involving smart machines that could be manipulated by malicious actors.  
For future research, integrating machine learning (ML) and artificial intelligence (AI) into the SpiderNet would enhance the system's ability to detect and prevent criminal activities. Developing appropriate software and understanding preventative forensic programming will improve the detection capabilities of the server and the connected devices. Current forensic methods are often insufficient because they rely on classical tools that do not account for the dynamic and interconnected nature of IoT devices. SpiderNet overcomes these limitations by providing a secure, hierarchical infrastructure that serves as a comprehensive forensic platform for the future of internet-connected smart machine investigations.