102 citations · 216 across the 20 of their papers we have counts for
22 papers
PRISM: Predictive Runtime In-place Scaling and Model Selection for Edge Microservices
Uwe Gropengießer, Thomas Reuter, Dominik Schön +3
Latency-sensitive edge AI services must balance strict deadlines, output quality, and limited compute and energy budgets. However, static CPU provisioning wastes resources because…
PRICE: Pricing-based Resource Incentives for Quality-of-Result-aware Computing at the Edge
Uwe Gropengießer, Sebastian Frenz, Max Mühlhäuser
Edge nodes are capacity-constrained by design, yet many edge workloads can trade result quality for resource efficiency at runtime. Existing edge pricing mechanisms largely treat r…
The End of the Canonical IoT Botnet: A Measurement Study of Mirai's Descendants
Leon Böck, Valentin Sundermann, Isabella Fusari +3
Since the burgeoning days of IoT, Mirai has been established as the canonical IoT botnet. Not long after the public release of its code, researchers found many Mirai variants compe…
Mitigating Intersection Attacks in Anonymous Microblogging
Sarah Abdelwahab Gaballah, Thanh Hoang Long Nguyen, Lamya Abdullah +2
Anonymous microblogging systems are known to be vulnerable to intersection attacks due to network churn. An adversary that monitors all communications can leverage the churn to lea…
Unsupervised Driving Event Discovery Based on Vehicle CAN-data
Thomas Kreutz, Ousama Esbel, Max Mühlhäuser +1
The data collected from a vehicle's Controller Area Network (CAN) can quickly exceed human analysis or annotation capabilities when considering fleets of vehicles, which stresses t…
Unsupervised 4D LiDAR Moving Object Segmentation in Stationary Settings with Multivariate Occupancy Time Series
Thomas Kreutz, Max Mühlhäuser, Alejandro Sanchez Guinea
In this work, we address the problem of unsupervised moving object segmentation (MOS) in 4D LiDAR data recorded from a stationary sensor, where no ground truth annotations are invo…
Malware Sight-Seeing: Accelerating Reverse-Engineering via Point-of-Interest-Beacons
August See, Maximilian Gehring, Max Mühlhäuser +2
New types of malware are emerging at concerning rates. However, analyzing malware via reverse engineering is still a time-consuming and mostly manual task. For this reason, it is n…
2PPS -- Publish/Subscribe with Provable Privacy
Sarah Abdelwahab Gaballah, Christoph Coijanovic, Thorsten Strufe +1
Publish/Subscribe systems like Twitter and Reddit let users communicate with many recipients without requiring prior personal connections. The content that participants of these sy…
User-Level Label Leakage from Gradients in Federated Learning
Aidmar Wainakh, Fabrizio Ventola, Till Müßig +6
Federated learning enables multiple users to build a joint model by sharing their model updates (gradients), while their raw data remains local on their devices. In contrast to the…
Enhancing Privacy via Hierarchical Federated Learning
Aidmar Wainakh, Alejandro Sanchez Guinea, Tim Grube +1
Federated learning suffers from several privacy-related issues that expose the participants to various threats. A number of these issues are aggravated by the centralized architect…
DeepAlign: Alignment-based Process Anomaly Correction using Recurrent Neural Networks
Timo Nolle, Alexander Seeliger, Nils Thoma +1
In this paper, we propose DeepAlign, a novel approach to multi-perspective process anomaly correction, based on recurrent neural networks and bidirectional beam search. At the core…
TRIDEnT: Building Decentralized Incentives for Collaborative Security
Nikolaos Alexopoulos, Emmanouil Vasilomanolakis, Stephane Le Roux +2
Sophisticated mass attacks, especially when exploiting zero-day vulnerabilities, have the potential to cause destructive damage to organizations and critical infrastructure. To tim…
On generating network traffic datasets with synthetic attacks for intrusion detection
Carlos Garcia Cordero, Emmanouil Vasilomanolakis, Aidmar Wainakh +2
Most research in the area of intrusion detection requires datasets to develop, evaluate or compare systems in one way or another. In this field, however, finding suitable datasets…
BINet: Multi-perspective Business Process Anomaly Classification
Timo Nolle, Stefan Luettgen, Alexander Seeliger +1
In this paper, we introduce BINet, a neural network architecture for real-time multi-perspective anomaly detection in business process event logs. BINet is designed to handle both…
A Systematic Approach to Constructing Families of Incremental Topology Control Algorithms Using Graph Transformation
Roland Kluge, Michael Stein, Gergely Varró +3
In the communication systems domain, constructing and maintaining network topologies via topology control (TC) algorithms is an important cross-cutting research area. Network topol…
A Systematic Approach to Constructing Incremental Topology Control Algorithms Using Graph Transformation
Roland Kluge, Michael Stein, Gergely Varró +3
Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication ne…
Analyzing Business Process Anomalies Using Autoencoders
Timo Nolle, Stefan Luettgen, Alexander Seeliger +1
Businesses are naturally interested in detecting anomalies in their internal processes, because these can be indicators for fraud and inefficiencies. Within the domain of business…
PABO: Mitigating Congestion via Packet Bounce in Data Center Networks
Xiang Shi, Lin Wang, Fa Zhang +3
In today's data center, a diverse mix of throughput-sensitive long flows and delay-sensitive short flows are commonly presented in shallow-buffered switches. Long flows could poten…
M-STAR: A Modular, Evidence-based Software Trustworthiness Framework
Nikolaos Alexopoulos, Sheikh Mahbub Habib, Steffen Schulz +1
Despite years of intensive research in the field of software vulnerabilities discovery, exploits are becoming ever more common. Consequently, it is more necessary than ever to choo…
I Trust my Zombies: A Trust-enabled Botnet
Emmanouil Vasilomanolakis, Jan Helge Wolf, Leon Böck +2
Defending against botnets has always been a cat and mouse game. Cyber-security researchers and government agencies attempt to detect and take down botnets by playing the role of th…
Beyond the Hype: On Using Blockchains in Trust Management for Authentication
Nikolaos Alexopoulos, Jörg Daubert, Max Mühlhäuser +1
Trust Management (TM) systems for authentication are vital to the security of online interactions, which are ubiquitous in our everyday lives. Various systems, like the Web PKI (X.…
Optimally Efficient Prefix Search and Multicast in Structured P2P Networks
Dirk Bradler, Jussi Kangasharju, Max Muehlhaeuser
Searching in P2P networks is fundamental to all overlay networks. P2P networks based on Distributed Hash Tables (DHT) are optimized for single key lookups, whereas unstructured net…