arXiv subjects

Ilya Komarov

Publications and source records attributed to Ilya Komarov.

4 recordsLinked to original sources

arXiv2026

Cross-Layer Intrusion Detection in 5G O-RAN: Gains and Limits of Fusing Radio Telemetry with Network Flow Records

Open RAN disaggregation enables joint analysis of DU radio telemetry and CU-side network-flow records, motivating cross-layer intrusion detection. We evaluate whether fusing these two modalities improves over each individually across seven architectures, using run-disjoint splits over ten seeds on a live 5G O-RAN dataset. Radio features match or outperform network flows on ROC-AUC and run-level detection rate across all architectures. Fusion yields selective ROC-AUC gains but at a one-percent false-positive operating point improves detection rate only for GRU and Transformer, reducing it for the other five models. The benefit is confined to architectures where both single-modality detection rates fall below 0.75. A DoS-to-Benign confusion of 27 to 46 percent persists across all 42 tested configurations of architecture, modality, and window duration, pointing to a limitation in the tested windowed statistical aggregation rather than in model capacity. Code is publicly available.

cs.CR↗

arXiv2020

User documentation and training at Belle II

Belle II is a rapidly growing collaboration with members from one hundred and nineteen institutes spread around the globe. The software development team of the experiment, as well as the software users, are very much decentralised. Together with the active development of the software, such decentralisation makes the adoption of the latest software releases by users an essential, but quite challenging task. To ensure the relevance of the documentation, we adopted the policy of in-code documentation and configured a website that allows us to tie the documentation to given releases. To prevent tutorials from becoming outdated, we covered them by unit-tests. For the user support, we use a question and answer service that not only reduces repetition of the same questions but also turned out to be a place for discussions among the experts. A prototype of a metasearch engine for the different sources of documentation has been developed. For training of the new users, we organise centralised StarterKit workshops attached to the collaboration meetings. The materials of the workshops are later used for self-education and organisation of local training sessions.

cs.CY↗

arXiv2020

Fingerprinting Analog IoT Sensors for Secret-Free Authentication

Especially in context of critical urban infrastructures, trust in IoT data is of utmost importance. While most technology stacks provide means for authentication and encryption of device-to-cloud traffic, there are currently no mechanisms to rule out physical tampering with an IoT device's sensors. Addressing this gap, we introduce a new method for extracting a hardware fingerprint of an IoT sensor which can be used for secret-free authentication. By comparing the fingerprint against reference measurements recorded prior to deployment, we can tell whether the sensing hardware connected to the IoT device has been changed by environmental effects or with malicious intent. Our approach exploits the characteristic behavior of analog circuits, which is revealed by applying a fixed-frequency alternating current to the sensor, while recording its output voltage. To demonstrate the general feasibility of our method, we apply it to four commercially available temperature sensors using laboratory equipment and evaluate the accuracy. The results indicate that with a sensible configuration of the two hyperparameters we can identify individual sensors with high probability, using only a few recordings from the target device.

cs.CR↗

arXiv2019

The Full Event Interpretation -- An exclusive tagging algorithm for the Belle II experiment

The Full Event Interpretation is presented: a new exclusive tagging algorithm used by the high-energy physics experiment Belle II. The experimental setup of Belle II allows the precise measurement of otherwise inaccessible $B$ meson decay-modes. The Full Event Interpretation algorithm enables many of these measurements. The algorithm relies on machine learning to automatically identify plausible $B$ meson decay chains based on the data recorded by the detector. Compared to similar algorithms employed by previous experiments, the Full Event Interpretation provides a greater efficiency, yielding a larger effective sample size usable in the measurement.

hep-ex↗