39 citations · 114 across the 13 of their papers we have counts for
14 papers
False Prophets: On the Security of World Models in Agentic Systems
Erik Imgrund, Anna Wimbauer, Klim Kireev +1
Large language models now power autonomous agents capable of complex, multi-step tasks in different environments. Accurate and reliable execution of these tasks requires the agent…
When a Zero-Shooter Cheats: Improving Age Estimation via Activation Steering
Erik Imgrund, Pia Hanfeld, Klim Kireev +1
Different age-related regulations have been proposed to protect minors from harmful content and interactions online. Automated age estimation is central to enforcing such regulatio…
Toward Securing AI Agents Like Operating Systems
Lukas Pirch, Micha Horlboge, Patrick Großmann +4
Autonomous agents based on large language models (LLMs) are rapidly emerging as a general-purpose technology, with recent systems such as OpenClaw extending their capabilities thro…
Evaluating Concept Filtering Defenses against Child Sexual Abuse Material Generation by Text-to-Image Models
Ana-Maria Cretu, Klim Kireev, Amro Abdalla +5
We evaluate the effectiveness of filtering child images from training datasets of text-to-image models to prevent model misuse to create child sexual abuse material (CSAM). First,…
A Manually Annotated Image-Caption Dataset for Detecting Children in the Wild
Klim Kireev, Ana-Maria Creţu, Raphael Meier +3
Platforms and the law regulate digital content depicting minors (defined as individuals under 18 years of age) differently from other types of content. Given the sheer amount of co…
Inverting Black-Box Face Recognition Systems via Zero-Order Optimization in Eigenface Space
Anton Razzhigaev, Matvey Mikhalchuk, Klim Kireev +3
Reconstructing facial images from black-box recognition models poses a significant privacy threat. While many methods require access to embeddings, we address the more challenging…
Characterizing and Detecting Propaganda-Spreading Accounts on Telegram
Klim Kireev, Yevhen Mykhno, Carmela Troncoso +1
Information-based attacks on social media, such as disinformation campaigns and propaganda, are emerging cybersecurity threats. The security community has focused on countering the…
Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings
Klim Kireev, Maksym Andriushchenko, Carmela Troncoso +1
Research on adversarial robustness is primarily focused on image and text data. Yet, many scenarios in which lack of robustness can result in serious risks, such as fraud detection…
Adversarial Robustness for Tabular Data through Cost and Utility Awareness
Klim Kireev, Bogdan Kulynych, Carmela Troncoso
Many safety-critical applications of machine learning, such as fraud or abuse detection, use data in tabular domains. Adversarial examples can be particularly damaging for these ap…
Darker than Black-Box: Face Reconstruction from Similarity Queries
Anton Razzhigaev, Klim Kireev, Igor Udovichenko +1
Several methods for inversion of face recognition models were recently presented, attempting to reconstruct a face from deep templates. Although some of these approaches work in a…
On the effectiveness of adversarial training against common corruptions
Klim Kireev, Maksym Andriushchenko, Nicolas Flammarion
The literature on robustness towards common corruptions shows no consensus on whether adversarial training can improve the performance in this setting. First, we show that, when us…
Black-Box Face Recovery from Identity Features
Anton Razzhigaev, Klim Kireev, Edgar Kaziakhmedov +2
In this work, we present a novel algorithm based on an it-erative sampling of random Gaussian blobs for black-box face recovery, given only an output feature vector of deep face re…
On adversarial patches: real-world attack on ArcFace-100 face recognition system
Mikhail Pautov, Grigorii Melnikov, Edgar Kaziakhmedov +2
Recent works showed the vulnerability of image classifiers to adversarial attacks in the digital domain. However, the majority of attacks involve adding small perturbation to an im…
Real-world adversarial attack on MTCNN face detection system
Edgar Kaziakhmedov, Klim Kireev, Grigorii Melnikov +2
Recent studies proved that deep learning approaches achieve remarkable results on face detection task. On the other hand, the advances gave rise to a new problem associated with th…