Search Results - "Rieck, Konrad"

Automatic Inference of Search Patterns for Taint-Style Vulnerabilities by Yamaguchi, Fabian, Maier, Alwin, Gascon, Hugo, Rieck, Konrad

“…Taint-style vulnerabilities are a persistent problem in software development, as the recently discovered "Heart bleed" vulnerability strikingly illustrates. In…”
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Modeling and Discovering Vulnerabilities with Code Property Graphs by Yamaguchi, Fabian, Golde, Nico, Arp, Daniel, Rieck, Konrad

“…The vast majority of security breaches encountered today are a direct result of insecure code. Consequently, the protection of computer systems critically…”
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Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection by Demontis, Ambra, Melis, Marco, Biggio, Battista, Maiorca, Davide, Arp, Daniel, Rieck, Konrad, Corona, Igino, Giacinto, Giorgio, Roli, Fabio

“…To cope with the increasing variability and sophistication of modern attacks, machine learning has been widely adopted as a statistically-sound tool for…”
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Toward Supervised Anomaly Detection by Goernitz, N., Kloft, M., Rieck, K., Brefeld, U.

“…Anomaly detection is being regarded as an unsupervised learning task as anomalies stem from adversarial or unlikely events with unknown distributions. However,…”
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ZOE: Content-Based Anomaly Detection for Industrial Control Systems by Wressnegger, Christian, Kellner, Ansgar, Rieck, Konrad

“…Due its complexity and a multitude of proprietary components, industrial control systems are an immanently difficult field of application for intrusion…”
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Similarity measures for sequential data by Rieck, Konrad

“…Expressive comparison of strings is a prerequisite for analysis of sequential data in many areas of computer science. However, comparing strings and assessing…”
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Backdooring and Poisoning Neural Networks with Image-Scaling Attacks by Quiring, Erwin, Rieck, Konrad

“…Backdoors and poisoning attacks are a major threat to the security of machine-learning and vision systems. Often, however, these attacks leave visible…”
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Evaluating Explanation Methods for Deep Learning in Security by Warnecke, Alexander, Arp, Daniel, Wressnegger, Christian, Rieck, Konrad

“…Deep learning is increasingly used as a building block of security systems. Unfortunately, neural networks are hard to interpret and typically opaque to the…”
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Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking by Quiring, Erwin, Arp, Daniel, Rieck, Konrad

“…Machine learning is increasingly used in securitycritical applications, such as autonomous driving, face recognition, and malware detection. Most learning…”
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Special issue on threat detection, analysis and defense by Li, Shujun, Rieck, Konrad, Woodward, Alan

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Monte Carlo Localization for path-based mobility in mobile wireless sensor networks by Hartung, Salke, Kellner, Ansgar, Rieck, Konrad, Hogrefe, Dieter

“…Localization is a mandatory requirement in Wireless Sensor Networks (WSNs). Many solutions focus on static networks and do not account for mobility. In this…”
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On the Detection of Image-Scaling Attacks in Machine Learning by Quiring, Erwin, Müller, Andreas, Rieck, Konrad

“…Image scaling is an integral part of machine learning and computer vision systems. Unfortunately, this preprocessing step is vulnerable to so-called…”
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Adversarial Machine Learning Against Digital Watermarking by Quiring, Erwin, Rieck, Konrad

“…Machine learning and digital watermarking are independent research areas. Their methods, however, are vulnerable to similar attacks if operated in an…”
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Backdooring and Poisoning Neural Networks with Image-Scaling Attacks by Quiring, Erwin, Rieck, Konrad

“…Backdoors and poisoning attacks are a major threat to the security of machine-learning and vision systems. Often, however, these attacks leave visible…”
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Efficient and Flexible Discovery of PHP Application Vulnerabilities by Backes, Michael, Rieck, Konrad, Skoruppa, Malte, Stock, Ben, Yamaguchi, Fabian

“…The Web today is a growing universe of pages and applications teeming with interactive content. The security of such applications is of the utmost importance,…”
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Privacy Threats through Ultrasonic Side Channels on Mobile Devices by Arp, Daniel, Quiring, Erwin, Wressnegger, Christian, Rieck, Konrad

“…Device tracking is a serious threat to the privacy of users, as it enables spying on their habits and activities. A recent practice embeds ultrasonic beacons…”
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Misleading Deep-Fake Detection with GAN Fingerprints by Wesselkamp, Vera, Rieck, Konrad, Arp, Daniel, Quiring, Erwin

“…Generative adversarial networks (GANs) have made remarkable progress in synthesizing realistic-looking images that effectively outsmart even humans. Although…”
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I still know it's you! On Challenges in Anonymizing Source Code by Horlboge, Micha, Quiring, Erwin, Meyer, Roland, Rieck, Konrad

“…The source code of a program not only defines its semantics but also contains subtle clues that can identify its author. Several studies have shown that these…”
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Misleading Deep-Fake Detection with GAN Fingerprints by Wesselkamp, Vera, Rieck, Konrad, Arp, Daniel, Quiring, Erwin

“…Generative adversarial networks (GANs) have made remarkable progress in synthesizing realistic-looking images that effectively outsmart even humans. Although…”
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Hunting for Truth: Analyzing Explanation Methods in Learning-based Vulnerability Discovery by Ganz, Tom, Rall, Philipp, Harterich, Martin, Rieck, Konrad

“…Recent research has developed a series of methods for finding vulnerabilities in software using machine learning. While the proposed methods provide a…”
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