Additive Manufacturing (AM) was originally invented to reduce the cost of the prototyping process. Over time, the technology evolved to be faster, more accurate, and affordable. These factors, in addition to the potential use of AM in parts production, have helped rapidly drive the growth of AM in both industrial and personal uses. Thus, there is an accompanying demand to understand the cybersecurity implications of such systems. In our research, we present an in-depth security review of Stratasys Dimension Elite and show how manufacturers of such high-end 3D printers failed to protect the confidentiality and integrity of the printed 3D models. Revealing the intricate dimensions of cyber threats within the realm of AM and laying the foundation for understanding the multifaceted nature of attacks, offering insights into vulnerabilities and potential consequences. Moreover, we demonstrate the massive impact network attacks can have on 3D printers’ communication channels. Our sniffing attack stole transmitted models with a minimal overhead of 0.015 seconds to evade detection. The developed replacement attack targeted and replaced specific models with offline-prepared models. Also, we automated a sabotaging attack to alter the interior model structure on the fly with minimal visual but significant strength differences. By revealing these attacks, this research not only improves the security posture of 3D printers but also enhances the understanding of security challenges in additive manufacturing as a whole.
Read the full article here: https://doi.org/10.1016/j.cose.2024.103810
]]>One major issue with using chatbots to solve homework assignments is that it takes away the opportunity for students to practice their problem-solving skills. Instead of trying different approaches and figuring out how to solve the problem independently, they can simply input their question into the chatbot and receive the answer without any effort. This can lead to a lack of understanding and ability to apply their knowledge in real-world situations.
Another problem with using chatbots to solve homework assignments is that it can lead to a lack of creativity and innovation. When students are given the answers without thinking for themselves, they may be unable to develop new and unique solutions to problems. This can limit their potential and hinder their growth as IT professionals.
One way to combat this problem is to ensure students understand the importance of learning through trial and error. By encouraging them to experiment and take risks, they will be more likely to develop their problem-solving skills and come up with creative solutions. Another solution is to ensure homework assignments are designed in a way that makes it difficult or impossible to use chatbots to solve them. For example, assignments could include open-ended questions or require students to develop original solutions.
In conclusion, using chatbots like ChatGPT to solve homework assignments can negatively impact the learning process of IT students. It takes away the opportunity for students to practice their problem-solving skills, limits their creativity and innovation, and hinders their growth as IT professionals. To combat this problem, it is essential to encourage students to learn through trial and error and to design homework assignments that chatbots cannot solve.
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