arXiv subjects

Federica Bianchi

Publications and source records attributed to Federica Bianchi.

4 recordsLinked to original sources

arXiv2025

Generalized Encrypted Traffic Classification Using Inter-Flow Signals

In this paper, we present a novel encrypted traffic classification model that operates directly on raw PCAP data without requiring prior assumptions about traffic type. Unlike existing methods, it is generalizable across multiple classification tasks and leverages inter-flow signals - an innovative representation that captures temporal correlations and packet volume distributions across flows. Experimental results show that our model outperforms well-established methods in nearly every classification task and across most datasets, achieving up to 99% accuracy in some cases, demonstrating its robustness and adaptability.

cs.CR↗

arXiv2023

Scalable and automated Evaluation of Blue Team cyber posture in Cyber Ranges

Cyber ranges are virtual training ranges that have emerged as indispensable environments for conducting secure exercises and simulating real or hypothetical scenarios. These complex computational infrastructures enable the simulation of attacks, facilitating the evaluation of defense tools and methodologies and developing novel countermeasures against threats. One of the main challenges of cyber range scalability is the exercise evaluation that often requires the manual intervention of human operators, the White team. This paper proposes a novel approach that uses Blue and Red team reports and well-known databases to automate the evaluation and assessment of the exercise outcomes, overcoming the limitations of existing assessment models. Our proposal encompasses evaluating various aspects and metrics, explicitly emphasizing Blue Teams' actions and strategies and allowing the automated generation of their cyber posture.

cs.CR↗

arXiv2023

Relational Event Modeling

Advances in information technology have increased the availability of time-stamped relational data such as those produced by email exchanges or interaction through social media. Whereas the associated information flows could be aggregated into cross-sectional panels, the temporal ordering of the events frequently contains information that requires new models for the analysis of continuous-time interactions, subject to both endogenous and exogenous influences. The introduction of the Relational Event Model (REM) has been a major development that has led to further methodological improvements stimulated by new questions that REMs made possible. In this review, we track the intellectual history of the REM, define its core properties, and discuss why and how it has been considered useful in empirical research. We describe how the demands of novel applications have stimulated methodological, computational, and inferential advancements.

stat.AP↗

arXiv2023

Drivers of the decrease of patent similarities from 1976 to 2021

The citation network of patents citing prior art arises from the legal obligation of patent applicants to properly disclose their invention. One way to study the relationship between current patents and their antecedents is by analyzing the similarity between the textual elements of patents. Many patent similarity indicators have shown a constant decrease since the mid-70s. Although several explanations have been proposed, more comprehensive analyses of this phenomenon have been rare. In this paper, we use a computationally efficient measure of patent similarity scores that leverages state-of-the-art Natural Language Processing tools, to investigate potential drivers of this apparent similarity decrease. This is achieved by modeling patent similarity scores by means of generalized additive models. We found that non-linear modeling specifications are able to distinguish between distinct, temporally varying drivers of the patent similarity levels that explain more variation in the data ($R^2\sim 18\%$) compared to previous methods. Moreover, the model reveals an underlying trend in similarity scores that is fundamentally different from the one presented previously.

stat.AP↗