HPI-MIT design research collaboration creates powerful teams

The recent ransomware attack on ChangeHealthcare, which severed the network connecting health care providers, pharmacies, and hospitals with medical insurance corporations, demonstrates just how disruptive supply chain attacks could be. On this case, it hindered the power of those providing medical services to submit insurance claims and receive payments.

This form of attack and other forms of information theft have gotten increasingly common and sometimes goal large, multinational corporations through the small and mid-sized vendors of their corporate supply chains, enabling breaks in these enormous systems of interwoven corporations.

Cybersecurity researchers at MIT and the Hasso Plattner Institute (HPI) in Potsdam, Germany, are focused on the several organizational security cultures that exist inside large corporations and their vendors since it’s that difference that creates vulnerabilities, often on account of the dearth of emphasis on cybersecurity by the senior leadership in these small to medium-sized enterprises (SMEs).

Keri Pearlson, executive director of Cybersecurity at MIT Sloan (CAMS); Jillian Kwong, a research scientist at CAMS; and Christian Doerr, a professor of cybersecurity and enterprise security at HPI, are co-principal investigators (PIs) on the research project, “Culture and the Supply Chain: Transmitting Shared Values, Attitudes and Beliefs across Cybersecurity Supply Chains.”

Their project was chosen within the 2023 inaugural round of grants from the HPI-MIT Designing for Sustainability program, a multiyear partnership funded by HPI and administered by the MIT Morningside Academy for Design (MAD). This system awards about 10 grants annually of as much as $200,000 each to multidisciplinary teams with divergent backgrounds in computer science, artificial intelligence, machine learning, engineering, design, architecture, the natural sciences, humanities, and business and management. The 2024 Call for Applications is open through June 3.

Designing for Sustainability grants support scientific research that promotes the United Nations’ Sustainable Development Goals (SDGs) on topics involving sustainable design, innovation, and digital technologies, with teams made up of PIs from each institutions. The PIs on these projects, who’ve common interests but different strengths, create more powerful teams by working together.

Transmitting shared values, attitudes, and beliefs to enhance cybersecurity across supply chains

The MIT and HPI cybersecurity researchers say that almost all ransomware attacks aren’t reported. Smaller corporations hit with ransomware attacks just shut down, because they’ll’t afford the payment to retrieve their data. This makes it difficult to know just what number of attacks and data breaches occur. “As more data and processes move online and into the cloud, it becomes much more vital to deal with securing supply chains,” Kwong says. “Investing in cybersecurity allows information to be exchanged freely while keeping data secure. Without it, any progress towards sustainability is stalled.”

One in all the primary large data breaches in america to be widely publicized provides a transparent example of how an SME cybersecurity can leave a multinational corporation vulnerable to attack. In 2013, hackers entered the Goal Corporation’s own network by obtaining the credentials of a small vendor in its supply chain: a Pennsylvania HVAC company. Through that breach, thieves were capable of install malware that stole the financial and private information of 110 million Goal customers, which they sold to card shops on the black market.

To stop such attacks, SME vendors in a big corporation’s supply chain are required to conform to follow certain security measures, however the SMEs often don’t have the expertise or training to make good on these cybersecurity guarantees, leaving their very own systems, and due to this fact any connected to them, vulnerable to attack.

“Immediately, organizations are connected economically, but not aligned when it comes to organizational culture, values, beliefs, and practices around cybersecurity,” explains Kwong. “Mainly, the massive corporations are realizing the smaller ones aren’t capable of implement all of the cybersecurity requirements. We’ve seen some larger corporations address this by reducing requirements or making the method shorter. Nevertheless, this doesn’t mean corporations are safer; it just lowers the bar for the smaller suppliers to clear it.”

Pearlson emphasizes the importance of board members and senior management taking responsibility for cybersecurity to be able to change the culture at SMEs, quite than pushing that all the way down to a single department, IT office, or in some cases, one IT worker.

The research team is using case studies based on interviews, field studies, focus groups, and direct commentary of individuals of their natural work environments to learn the way corporations engage with vendors, and the precise ways cybersecurity is implemented, or not, in on a regular basis operations. The goal is to create a shared culture around cybersecurity that could be adopted accurately by all vendors in a supply chain.

This approach is according to the goals of the Charter of Trust Initiative, a partnership of huge, multinational corporations formed to determine a greater technique of implementing cybersecurity in the availability chain network. The HPI-MIT team worked with corporations from the Charter of Trust and others last yr to know the impacts of cybersecurity regulation on SME participation in supply chains and develop a conceptual framework to implement changes for stabilizing supply chains.

Cybersecurity is a prerequisite needed to realize any of the United Nations’ SDGs, explains Kwong. Without secure supply chains, access to key resources and institutions could be abruptly cut off. This might include food, clean water and sanitation, renewable energy, financial systems, health care, education, and resilient infrastructure. Securing supply chains helps enable progress on all SDGs, and the HPI-MIT project specifically supports SMEs, that are a pillar of the U.S. and European economies.

Personalizing product designs while minimizing material waste

In a vastly different Designing for Sustainability joint research project that employs AI with engineering, “Personalizing Product Designs While Minimizing Material Waste” will use AI design software to put out multiple parts of a pattern on a sheet of plywood, acrylic, or other material, in order that they could be laser cut to create recent products in real time without wasting material.

Stefanie Mueller, the TIBCO Profession Development Associate Professor within the MIT Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory, and Patrick Baudisch, a professor of computer science and chair of the Human Computer Interaction Lab at HPI, are co-PIs on the project. The 2 have worked together for years; Baudisch was Mueller’s PhD research advisor at HPI.

Baudisch’s lab developed a web based design teaching system called Kyub that lets students design 3D objects in pieces which are laser cut from sheets of wood and assembled to turn out to be chairs, speaker boxes, radio-controlled aircraft, and even functional musical instruments. As an example, each leg of a chair would consist of 4 an identical vertical pieces attached at the sides to create a hollow-centered column, 4 of which can provide stability to the chair, though the fabric could be very lightweight.

“By designing and constructing such furniture, students learn not only design, but additionally structural engineering,” Baudisch says. “Similarly, by designing and constructing musical instruments, they find out about structural engineering, in addition to resonance, sorts of musical tuning, etc.”

Mueller was at HPI when Baudisch developed the Kyub software, allowing her to look at “how they were developing and making all of the design decisions,” she says. “They built a extremely neat piece for people to quickly design some of these 3D objects.” Nevertheless, using Kyub for material-efficient design just isn’t fast; to be able to fabricate a model, the software has to interrupt the 3D models down into 2D parts and lay these out on sheets of fabric. This takes time, and makes it difficult to see the impact of design decisions on material use in real-time.

Mueller’s lab at MIT developed software based on a layout algorithm that uses AI to put out pieces on sheets of fabric in real time. This enables AI to explore multiple potential layouts while the user remains to be editing, and thus provide ongoing feedback. “Because the user develops their design, Fabricaide decides good placements of parts onto the user’s available materials, provides warnings if the user doesn’t have enough material for a design, and makes suggestions for the way the user can resolve insufficient material cases,” in accordance with the project website.

The joint MIT-HPI project integrates Mueller’s AI software with Baudisch’s Kyub software and adds machine learning to coach the AI to supply higher design suggestions that save material while adhering to the user’s design intent.

“The project is all about minimizing the waste on these materials sheets,” Mueller says. She already envisions the subsequent step on this AI design process: determining how one can integrate the laws of physics into the AI’s knowledge base to make sure the structural integrity and stability of objects it designs.

AI-powered startup design for the Anthropocene: Providing guidance for novel enterprises

Through her work with the teams of MITdesignX and its international programs, Svafa Grönfeldt, faculty director of MITdesignX and professor of the practice in MIT MAD, has helped scores of individuals in startup corporations use the tools and methods of design to be sure that the answer a startup proposes actually suits the issue it seeks to resolve. This is usually called the problem-solution fit.

Grönfeldt and MIT postdoc Norhan Bayomi are actually extending this work to include AI into the method, in collaboration with MIT Professor John Fernández and graduate student Tyler Kim. The HPI team includes Professor Gerard de Melo; HPI School of Entrepreneurship Director Frank Pawlitschek; and doctoral student Michael Mansfeld.

“The startup ecosystem is characterised by uncertainty and volatility compounded by growing uncertainties in climate and planetary systems,” Grönfeldt says. “Due to this fact, there’s an urgent need for a strong model that may objectively predict startup success and guide design for the Anthropocene.”

While startup-success forecasting is gaining popularity, it currently focuses on aiding enterprise capitalists in choosing corporations to fund, quite than guiding the startups within the design of their products, services and business plans.

“The coupling of climate and environmental priorities with startup agendas requires deeper analytics for effective enterprise design,” Grönfeldt says. The project goals to explore whether AI-augmented decision-support systems can enhance startup-success forecasting.

“We’re attempting to develop a machine learning approach that may give a forecasting of probability of success based on quite a few parameters, including the variety of business model proposed, how the team got here together, the team members’ backgrounds and skill sets, the market and industry sector they’re working in and the problem-solution fit,” says Bayomi, who works with Fernández within the MIT Environmental Solutions Initiative. The 2 are co-founders of the startup Lamarr.AI, which employs robotics and AI to assist reduce the carbon dioxide impact of the built environment.

The team is studying “how company founders make decisions across 4 key areas, ranging from the chance recognition, how they’re choosing the team members, how they’re choosing the business model, identifying essentially the most automatic strategy, during the product market fit to achieve an understanding of the important thing governing parameters in each of those areas,” explains Bayomi.

The team is “also developing a big language model that may guide the choice of the business model by utilizing large datasets from different corporations in Germany and the U.S. We train the model based on the precise industry sector, resembling a technology solution or an information solution, to search out what could be essentially the most suitable business model that might increase the success probability of an organization,” she says.

The project falls under several of the United Nations’ Sustainable Development Goals, including economic growth, innovation and infrastructure, sustainable cities and communities, and climate motion.

Furthering the goals of the HPI-MIT Joint Research Program

These three diverse projects all advance the mission of the HPI-MIT collaboration. MIT MAD goals to make use of design to remodel learning, catalyze innovation, and empower society by inspiring people from all disciplines to interweave design into problem-solving. HPI uses digital engineering focused on the event and research of user-oriented innovations for all areas of life.

Interdisciplinary teams with members from each institutions are encouraged to develop and submit proposals for ambitious, sustainable projects that use design strategically to generate measurable, impactful solutions to the world’s problems.