CISPA Startups
Since 2019, the CISPA startup incubator has mentored, supported and accompanied the journey of many spin-off projects and startups.
Technology
Many companies are unaware of the attack surface they present to cybercriminals. The St. Ingbert-based company AIS wants to change that and helps companies uncover digital vulnerabilities and take appropriate security measures. The CISPA spin-off has developed the Findalyze platform, which enables companies to continuously monitor their Internet-exposed IT infrastructure and thus proactively secure it. Through the "attacker's goggles," the software examines publicly available information from companies for potentially security-relevant aspects, evaluates them, and provides actionable insights to improve and maintain IT security posture.
Scientific Background
To determine and reduce the potential attack surface, Findalyze applies various security-related checks and testing procedures to enterprise IT assets, such as domains, email addresses, or externally visible technologies. Under the technical and conceptual leadership of Dr. Oliver Schranz and Dr. Milivoj Simeonovski, both of whom earned their doctorates at CISPA, a scanning and evaluation mechanism was developed that processes the results for companies and makes them available on a dashboard. Through permanent knowledge transfer, AIS ensures that the latest findings and attack vectors are also incorporated into the platform.
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Kertos is a no-code SaaS solution connecting an organization’s entire infrastructure to manage personal data and fully automate privacy processes. By executing workflows, handling data subject requests, and building self-maintaining records of processing activities, Kertos makes manual privacy (GDPR) compliance a thing of the past. The integration of external systems plays a central role in the automation of data privacy tasks. This requires corresponding API keys, access tokens or comparable access information. Kertos develops a hybrid zero-trust architecture to make sure data transfer takes place only between the (potentially on-premise) worker nodes and the integrated systems. Thus, the Kertos backend itself never comes into contact with costumers’ API keys or customer data.
Scientific Background
Kertos focuses on the automation of processes, the secure management of privacy requirements and the simplification of everyday workflows for all stakeholders involved. The founders Dr. Kilian Schmidt, Johannes Hussak and Alexander Prams combine relevant practical experience and professional knowledge, which they acquired at renowned universities such as the Technical University of Munich and the Humboldt University of Berlin. While Dr. Kilian Schmidt, with his background in law and first-hand experience with legal processes, takes on the role of "legal expert" in the founding team, Johannes Hussak contributes expertise in product development and innovation as CPO and COO. The team is completed by Alexander Prams, who is responsible for the technical implementation of the Kertos solution in his role as CTO and with his field of expertise, automation.
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Technology
NetBird is a next generation solution of network access and security that has been developed as open-source software since 2021. The platform combines Zero Trust principles with a highly scalable peer-to-peer network enabling organizations and teams to securely connect remote resources. It is based on Wireguard® and provides a fast and secure network for any use case, that verifies policies and client context at the edge, not at centralized gateways.
Scientific Background
NetBird has a team with over twenty years of experience in software and infrastructure engineering fields. They come from their countries' best information systems and computer networking universities with a focus on information security. They built their careers in data, automation, and security engineering, always providing the best user experience while keeping security a default option.
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Technology
Simplyblock is a clustered cloud storage solution that provides users with the ability to create virtual (logical) block storage devices, that scale arbitrarily in size and speed, yet work just as simple as a locally attached disk. Built upon the industry-standard, and fast NVMe over Fabrics protocol, simplyblock combines a multitude of backing storage technologies (local and remote block storage, as well as object storage) but provides a single, holistic view of the logical device. Furthermore, the solution enables automatic tiered storage (moving data between backend storages for price and performance reasons), as well as industry-expected features, such as compression, deduplication, encryption, and more.
In addition to that, features like immediate snapshots, remote backups, automatic self-healing, and our intelligent data balancing algorithms, as well as enhanced disaster recovery mechanisms help mitigate the dangers of ransomware attacks, or other types of security breaches that cause data loss, data encryption, or data corruption. Simplyblock integrates advanced cybersecurity features to recognize and stop new attack vectors and offer an immediate recovery in situations where data was already modified, aiming to bring a RPO (Recovery-Point-Objective) of 0, hence no data loss, to the world.
We want to democratize the ability to use cloud storage the way the user needs it, not the way it is offered by cloud providers.
Scientific Background
The simplyblock team combines decades of experience in different field, product-related fields, such as distributed systems, storage solutions, cloud infrastructures. Our technology is based on industry-proven components like SPDK (the Storage Performance Development Kit), a framework supported by industry giants such as Intel, and uses NVMe over TCP as the underlying transport protocol, providing an out of the box experience available in Linux and Windows. The combination of components provides an easy to use and high-performance solution to companies running IO-intensive workloads, such as databases, in the cloud.
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Codeshield has developed a security tool for integrated development environments, which allows to analyze the whole software supply chain in almost real time and with high precision. With the help of static code analysis, data flow analysis and fingerprinting vulnerabilities in your own code as well as in integrated third party libraries can be detected and fixed.
Scientific Background
Dr. Johannes Späth has developed new and efficient algorithms for static code analysis in the context of his excellent dissertation and has published on this topic at international congresses. Manuel Benz has a master's degree in both computer science and IT security and has been working on the combination of static and dynamic analysis at the University of Paderborn since 2016. Andreas Dann has a master's degree in computer science with a minor in economics and has been researching static code analysis in the field of IT security at the University of Paderborn since 2016.
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Technology
Sesame leverages modern Large Language Models (LLMs) to optimize knowledge management for clients. Based in Saarland, Germany, with additional presence in Hamburg and Bavaria, the team prioritizes maximizing LLM benefits while upholding top-notch security and privacy. Their commitment goes beyond interest; they utilize LLMs as invaluable assets for clients through innovative software solutions. Collaborating closely with customers, they merge their ideas with cutting-edge technologies, delivering bespoke solutions tailored to unique business needs. This proactive approach to security enables businesses to optimize operations using advanced LLMs all while safeguarding the privacy of their data.
Scientific Background
Collaborating with esteemed research affiliations like Helmholtz (CISPA), contexxt.ai – the company behind Sesame – demonstrates its dedication to pioneering innovation, with security and data privacy ingrained in every aspect of its approach. Security and data privacy are fundamental pillars of the strategy, deeply integrated into the recommended architectures and methodologies. The team actively explores the security readiness of vector databases, recognizing their potential as optimal primary data sources for language models, especially in terms of data security entry points.
In the ongoing research, the company investigates how vector databases can facilitate tenant separation by integrating knowledge elements with unique TenantIDs. This involves integrating TenantIDs within the vector database, implementing data partitioning techniques, and applying tenant-specific filters. These efforts are aimed at enhancing privacy and security in shared language models, leading to benefits such as heightened data confidentiality, adherence to regulatory frameworks, and bolstered customer trust. By prioritizing security in this manner, contexxt.ai upholds its commitment to ensuring the utmost care in handling data and maintaining trust.
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The Cybervize platform is designed for organizations of all sizes to strengthen their cybersecurity. This solution includes an AI-based SaaS component that identifies risks, recommends cybersecurity measures, and assists with implementation. As an integral part of Cybervize, a moderated user forum promotes knowledge sharing and provides practical guidance. Human advisors provide targeted expert assessments to assist with implementation and conduct periodic reviews upon request.
Scientific Background
Cybervize's technology is based on the application of AI technologies and SaaS solutions to automate cybersecurity processes. The solution draws on proven cybersecurity practices and processes, as well as information security and risk management best practices, to provide a comprehensive and cost-effective cybersecurity solution specifically for small and medium-sized businesses.
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fuse.space is the first secure data and collaboration space that records and protects the complex and collaborative process of creative work, to protect its intellectual property. Our vision is to connect the world in creativity. A world where all people and entities can work together easily and securely, without having to know or trust each other. To do this, we are creating a space that supports, transparently documents, immutably secures, and verifiably protects the collaborative process of creative work. We address music creators, architects or scientists, anyone who shares and collaborates on their sensitive and unprotected intangible assets, such as ideas, concepts, and inventions. With the support of CISPA, fuse.space is further developing its solution to enable a secure collaboration space.
Scientific Background
With the help of over 1,000 creators and institutions in the creative industries, we are working together to create a solution that covers and secures the most important work processes and integrates them into their workflows. We ourselves come from the music industry and know the problem and its potential very well. Andre Angkasa has been building digital media services, products, and brands for over 18 years. Alexander Wittkowski, as a music producer and composer, knows the problem from his own experience. He had two of his songs stolen and published under a different name by a very famous pop star. Unfortunately, he lacks any proof of the collaboration process and his IP.
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Hyde is a platform for consumers to monetize their data in a privacy-preserving manner, and for businesses to understand their customers better in a compliant way. Built on a state-of-the-art privacy foundation, Hyde provides transparency, control and data sovereignty for consumers, while allowing businesses to expand their customer data beyond their own premises. The vision of Hyde is to equip consumers with data agency and to equalize business data moats.
Scientific Background
Hyde builds on recent progress in Trusted Execution Environments (TEE). This technology allows to compute on data without exposing it to third parties. Beyond that, Hyde is heavily using Machine Learning Embedding technology to convey consumer taste like music, movies, or shopping. Hyde is led by Dr. Uwe Stoll with a PhD in Semantic Web and Machine Learning, and a long track record in applied AI. CTO Kyohei Hamaguchi (JP) has about ten years of experience in designing complex software systems with an emphasis on information security.
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Two-factor authentication has become the standard for logging in to most web services. To ensure that logging in is not only fast, but also secure, Deepsign has developed a technology for companies and their employees that turns the individual behavior of users into a second factor. Using artificial intelligence techniques, DeepSign creates a model of how users interact with their mouse and keyboard. This unique interaction pattern can then replace cumbersome authentication via other devices or repeated password entries when logging into a computer. Unlike other biometric features such as a face or fingerprint, interaction patterns cannot be easily copied undetected or accidentally passed on like a password. In addition, the login process remains fast.
Scientific Background
DeepSign puts behavior-based security at the forefront. The founders Jannis Froese and Nils Vossebein studied at Saarland University and combine knowledge about IT security from academia and industry. While Jannis Froese is particularly knowledgeable in the field of machine learning, Nils Vossebein's specialty is the acquisition, processing and storage of data. He is also in charge of sales at DeepSign.
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LUBIS EDA has developed a software tool for the verification of digital integrated circuits (IC) which are part of a lot of semiconductors. With this tool, LUBIS EDA can automatically generate the Verification Intellectual Property (VIP). This VIP can then be used to ensure that there are no functional flaws and bugs within the IC. Functional bugs can not only lead to a malfunctioning semiconductor but can also be an entry point for security issues. The verification methodology is based on the so called “Formal Verification” technique for semiconductors.
Scientific background
Dr. Tobias Ludwig has developed a new and efficient methodology for the generation of the VIP within his time as a researcher at the TU Kaiserslautern. His dissertation resulted in a software prototype that implements this methodology. Dr. Michael Schwarz has done his dissertation at the same chair as Dr. Tobias Ludwig and is an expert in Formal Verification as well as Hardware-Software-Interfaces. Dr. Max Birtel holds a degree in business engineering and was a researcher at the German Research Centre for Artificial Intelligence (DFKI) and the SmartFactory Kaiserslautern in the field of Industrie 4.0 .
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Technology
Complex AI systems are inherently black-boxes with minimal insight into their internal functionality. This bears the danger of decisions that are not justifiable, legitimate, robust against external manipulations or that simply cannot be understood by stakeholders with different backgrounds. To help organizations meet this challenge, QuantPi developed an innovative framework which systematically matches questions about the functionality of AI systems with appropriate algorithms to produce relevant explanations. Furthermore, it allows users to understand how the latter algorithms work and to evaluate risks when interpreting their output.
Scientific Background
QuantPi is a spin-off of the prestigious Helmholtz Center for Information Security (CISPA), located in Germany. We develop automated and scalable solutions for explainability and robustness auditing of AI models. The QuantPi team is made up of leading researchers, engineers and business minds from premier universities around the world. Our customers include well-established companies of various industries and fastly-growing AI startups.
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Technology
At the heart of the Xpect approach to modeling safe processes is a representation formalism that not only maps temporal sequences of actions, but also captures their semantics by linking them to existing knowledge. In this way, it becomes possible to prove central properties of abstract processes and concrete sequences and to correct them if necessary. By monitoring the current execution of a process, the violation of central security or compliance rules can be detected in advance and the occurrence of a critical state can be avoided.
Scientific Background
Most of Xpect's employees have many years of experience in artificial intelligence research. For example, many of them were employees at DFKI, with which there is still close cooperation. In addition, they have gained relevant experience in management consultancies or companies in large-scale industry, which pays off in particular when it comes to identifying relevant issues and assessing the weaknesses of current solutions.
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