Stefano Bennati

Stefano Bennati
ETH Zurich | ETH Zürich · Computational Social Science

MSc

About

18
Publications
13,685
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79
Citations
Introduction
Stefano Bennati currently works at the Computational Social Science, ETH Zurich. Stefano does research in Computational Social science, Artificial Neural Network and Agent-Based Modeling. Their most recent publication is 'How intelligence can change the course of evolution.'
Additional affiliations
July 2013 - July 2014
Carnegie Mellon University
Position
  • Research Programmer
March 2012 - April 2013
University of Freiburg
Position
  • Research Assistant

Publications

Publications (18)
Chapter
Malware reverse-engineering, specifically, identifying the tasks a given piece of malware was designed to perform (e.g., logging keystrokes, recording video, establishing remote access) is a largely human-driven process that is a difficult and time-consuming operation. In this chapter, we present an automated method to identify malware tasks using...
Article
Full-text available
The interaction between phenotypic plasticity, e.g. learning, and evolution is an important topic both in Evolutionary Biology and Machine Learning. The evolution of learning is commonly studied in Evolutionary Biology, while the use of an evolutionary process to improve learning is of interest to the field of Machine Learning. This paper takes a d...
Article
Full-text available
Collective sensing is an emergent phenomenon that enables individuals to estimate an invisible property of the environment through the observation of social interactions. It has been shown in Nature that individuals in animal groups develop the capacity to perceive this signal and the social interactions between them produce complex group behavior...
Article
Full-text available
Provision of smart city services often relies on users contribution, e.g., of data, which can be costly for the users in terms of privacy. Privacy risks, as well as unfair distribution of benefits to the users, should be minimized as they undermine user participation, which is crucial for the success of smart city applications. This paper investiga...
Preprint
Full-text available
Several smart city services rely on users contribution, e.g., data, which can be costly for the users in terms of privacy. High costs lead to reduced user participation, which undermine the success of smart city technologies. This work develops a scenario-independent design principle, based on public good theory, for resource management in smart ci...
Article
The effect of phenotypic plasticity on evolution, the so-called Baldwin effect, has been studied extensively for more than 100 years. Plasticity is known to influence the speed of evolution towards a specific genetic configuration, but whether it also influences what that genetic configuration is, is still an open question. This question is investi...
Article
Full-text available
This paper introduces PriMaL, a general PRIvacy-preserving MAchine-Learning method for reducing the privacy cost of information transmitted through a network. Distributed sensor networks are often used for automated classification and detection of abnormal events in high-stakes situations, e.g. fire in buildings, earthquakes, or crowd disasters. Su...
Article
Full-text available
Big data collection practices using Internet of Things (IoT) pervasive technologies are often privacy-intrusive and result in surveillance, profiling, and discriminatory actions over citizens that in turn undermine the participation of citizens to the development of sustainable smart cities. Nevertheless, real-time data analytics and aggregate info...
Article
Full-text available
Identifying the tasks a given piece of malware was designed to perform (e.g. logging keystrokes, recording video, establishing remote access, etc.) is a difficult and time-consuming operation that is largely human-driven in practice. In this paper, we present an automated method to identify malware tasks. Using two different malware collections, we...
Conference Paper
Full-text available
An important source of constraints on unified theories of cognition is their ability to perform complex tasks that are challenging for humans. Malware reverse-engineering is an important type of analysis in the domain of cyber-security. Rapidly identifying the tasks that a piece of malware is designed to perform is an important part of reverse engi...
Conference Paper
Full-text available
Malware reverse-engineering is an important type of analysis in cybersecurity. Rapidly identifying the tasks that a piece of malware is designed to perform is an important part of reverse engineering that is generally manually performed as it relies heavily on human intuition This paper describes how the use of cognitively-inspired inference can as...
Conference Paper
ACT-R is one of the most widely used cognitive architectures, and it has been used to model hundreds of phenomena described in the cognitive psychology literature. In spite of this, there are relatively few studies that have attempted to apply ACT-R to situations involving social interaction. This is an important omission since the social aspects o...
Conference Paper
Full-text available
This paper describes a general instance-based learning model of sensemaking in the context of geospatial intelligence tasks. Building upon a model previously described in Lebiere, Pirolli, Thomson et al. (2013), our model captures human performance across two tasks involving generating and updating likelihoods based on simulated geospatial intellig...
Conference Paper
Full-text available
In this paper, we describe a framework for processing big data that maximizing the efficiency of human data scientists by having them primarily operate over information that is best structured to human processing demands. We accomplish this through the use of cognitive models as an intermediary between machine learning algorithms and human data sci...
Article
Robotic swarms are nonlinear dynamical systems that benefit from the presence of human operators in realistic missions with changing goals and constraints. There has been recent interest in safe operations of robotic swarms under human control. Verification and validation techniques for these human-machine systems could be deployed to provide forma...

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Project (1)
Project
The project involves modeling and empirical analysis of the solar energy trading projects in rural context of developing countries. The aim is to understand the social (economical and institutional too) dynamics involved by providing: 1. Policy recommendations with empirical research on the various energy trading projects at micro/nano grid level and development of theoretical framework to incorporate the social factors. 2. Computer Science (agent based) model to understand the effects via agent based modelling and minimize the effects among of societal norms for energy trading.