#WeKnowCybersecurity

Cybersecurity Blog of Fraunhofer AISEC

Trusted Artificial Intelligence
Nicolas Müller

How to build suitable datasets for successful detection of audio deepfakes

Deepfakes are a significant threat to democracy as well as private individuals and companies. They make it possible to spread disinformation, to steal intellectual property and to commit fraud, to name but a few. While robust AI detection systems offer a possible solution, their effectiveness depends largely on the quality of the underlying data, simply put: »Garbage in, garbage out.« But how do you create a dataset that is well suited to identifying the ever-evolving deepfakes and enables robust detection? And what constitutes high-quality training data?

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Nicolas Müller 31. March 2025
Cybersecurity
Stefan Tatschner

Parsing X.509 Certificates: How Secure Are TLS Libraries?

Digital certificates like X.509 are essential for secure internet communication by enabling authentication and data integrity. However, differences in how they are parsed by various TLS libraries can introduce security risks. A recent study by Fraunhofer AISEC analyzed six widely used X.509 parsers with real-world certificates. The findings reveal inconsistencies that could impact security-critical applications. In this article, we summarize the key results and explain why companies need to scrutinize their cryptographic libraries.

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Stefan Tatschner 26. February 2025
Cryptography
Ivan Gavrilan

Fortifying Cryptography with Impeccable Circuits: Impeccable Keccak Explained

Cybersecurity threats are evolving, and cryptographic implementations face growing risks from fault injection attacks. Fraunhofer AISEC’s research introduces Impeccable Keccak, a new approach to secure SPHINCS+, a post-quantum cryptography digital signature scheme that has been standardized by NIST in 2024. By leveraging impeccable circuits and ensuring active security, this represents a new approach to fault-resilient cryptography.

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Ivan Gavrilan 13. January 2025
Quantum Computing
Maximilian Wendlinger

Quantum and Classical AI Security: How to Build Robust Models Against Adversarial Attacks

The rise of quantum machine learning (QML) brings exciting advancements such as higher levels of efficiency or the potential to solve problems intractable for classical computers. Yet how secure are quantum-based AI systems against adversarial attacks compared to classical AI? A study conducted by Fraunhofer AISEC explores this question by analyzing and comparing the robustness of quantum and classical machine learning models under attack. Our findings about adversarial vulnerabilities and robustness in machine learning models form the basis for practical methods to defend against these attacks, which are introduced in this article.

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Maximilian Wendlinger 13. December 2024
IoT Security
Felix Oberhansl

Fraunhofer AISEC commissioned by the German Federal Office for Information Security (BSI): New study on the synthesis of cryptographic hardware implementations

The study by Fraunhofer AISEC on the security of cryptographic hardware implementations focuses on physical attacks on hardware, such as side-channel attacks and fault attacks, as well as measures to defend against them. These protective mechanisms can potentially be compromised by optimizations in the chip design process. The study shows that protective measures should be integrated into complex design processes and taken into account in hardware design synthesis in order to be resilient to hardware attacks. The findings will help hardware designers to develop robust and secure chips.

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Felix Oberhansl 7. November 2024
Cybersecurity
Christian Banse

Faster detection and rectification of security vulnerabilities in software with CSAF

The Common Security Advisory Framework (CSAF) is a machine-readable format for security notices and plays a crucial role in implementing the security requirements of the Cyber Resilience Act (CRA): Security vulnerabilities can be detected and rectified faster by automatically creating and sharing security information. Fraunhofer AISEC has now published the software library »kotlin-csaf«, which implements the CSAF standard in the Kotlin programming language.

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Christian Banse 16. October 2024
Cybersecurity
Immanuel Kunz

Privacy By Design: Integrating Privacy into the Software Development Life Cycle

As data breaches and privacy violations continue to make headlines, it is evident that mere reactive measures are not enough to protect personal data. Therefore, behind every privacy-aware organization lies an established software engineering process that systematically includes privacy engineering activities. Such activities include the selection of privacy-enhancing technologies, the analysis of potential privacy threats, as well as the continuous re-evaluation of privacy risks at runtime.
In this blog post, we give an overview of some of these activities which help your organization to build and operate privacy-friendly software by design. In doing so, we focus on risk-based privacy engineering as the driver for »Privacy by Design«.

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Immanuel Kunz 4. June 2024
Headerbild zum Blogartikel "Neue Studie zu Laser-basiertem Fehlerangriff auf XMSS" im Cybersecurityblog des Fraunhofer AISEC
Cryptography
Silvan Streit

Fraunhofer AISEC commissioned by the German Federal Office for Information Security (BSI): new study of laser-based fault attacks on XMSS

To ensure the security of embedded systems, the integrity and authenticity of the software must be verified, for example through signatures. However, targeted hardware attacks enable malware to be used to take over the system. What risks are modern cryptographic implementations exposed to? What countermeasures need to be taken? To answer these questions, Fraunhofer AISEC was commissioned by the German Federal Office for Information Security (BSI) to carry out a study of laser-based fault attacks on XMSS. The focus is on a hash-based, quantum-secure scheme for creating and verifying signatures based on the Winternitz One-Time-Signature (WOTS) scheme.

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Silvan Streit 6. March 2024
Quantum Computing
Kilian Tscharke

Anomaly Detection with Quantum Machine Learning – Identifying Cybersecurity Issues in Datasets

Since the release of ChatGPT, the popularity of Machine Learning (ML) has grown immensely. Besides Natural Language Processing (NLP) anomaly detection is an important branch of data analysis whose goal is to identify observations or events that deviate from the rest of the data. At Fraunhofer AISEC, cybersecurity experts explore Quantum Machine Learning methods for anomaly detection. One approach is based on the classification of quantum matter while a second method uses a type of Quantum Support Vector Machine with a kernel that is calculated on a quantum computer. This blog post explains the fundamentals of anomaly detection and shows the two approaches being pursued by the Quantum Security Technologies group at Fraunhofer AISEC.

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Kilian Tscharke 30. January 2024
‚Industrial Security‘
Nico Haas

Towards Automated Cloud Security Certification

Obtaining a cloud security certification requires a lot of preparation time, which mainly involves manual processes that are prone to error. In other words, several employees cannot perform their usual duties during an audit preparation. Our Clouditor tool aims to improve this process by making audit preparations more systematic and automatable. This makes it possible to continuously monitor cloud services and check their compliance with a cloud security catalog such as BSI C5[1], EUCS[2], or the CCM[3].

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Nico Haas 6. December 2023

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