Social Area Framework for Early Security Triggers – SAFEST

Social Area Framework for Early Security Triggers

Public spaces such as airports, railway stations or stadiums bring together large numbers of people to use a security-sensitive infrastructure. Electronic security systems help providing better, faster public security, and safety, allowing for instance intrusion detection and monitoring of large crowds in order to provide guidance in case of unexpected events. SAFEST aim to leverage sensors, in-network computation and Internet of Things to achieve light-weight electronic security systems.

Leveraging sensors, image processing, in-network computation, Internet of Things, and social science to achieve light-weight electronic security systems

Current security systems are typically expensive, non-trivial to deploy, difficult to operate and maintain, prone to malfunction due to individual component failures, and generally lack citizen privacy-friendliness. SAFEST is a project that aims at providing a better system, aiming to be both more distributed, based on sensor networking, and more citizen-friendly, using in-network computation techniques, and the results of social science analysis. The system will be demonstrated at the Berlin ariport at the end of the project.

- Social Science
- Energy Efficient & Rugged Hardware Design
- Energy Efficient Embedded Software Design
- Internet of Things Interoperability
- Network Protocol Design
- Online Image Processing
- Knowledge Fusion

Novel Analysis of Acceptability, Privacy, Legal and Social Impacts:
Design of a theoretical model of subjective perception & acceptance of electronic security systems. Development & pretest of a quantitative survey study based on this model (for airport passengers & personal).

Innovative Hardware:
Design & development of
-SAGEM SmartNode multi-sensor hub and its software, allowing advanced energy consumption management,
-SAGEM compact uncooled IR camera allowing energy efficient high frame-rate infra-red video capture & meta-data exchange for optimized image processing.

Innovative Open-source Software:
Design & development of RIOT, a compact, real-time, energy-efficient operating system for the Internet of Things. Enables app development in standard C or C++, provides unified APIs (including POSIX), for 8-bit, 16-bit or 32-bit platforms, while requiring as low as 1,5kB of RAM and 5kB of ROM. On-going development of RIOT network stacks (IPv6 and CCN) connecting apps to one another & to the Internet.

New Network Protocols & Distributed Computation Mechanisms:
Design & development of a novel embedded distributed cooperation mechanism (new open source C++ library CAF available) based on the actor programming model. Design of novel network protocols for reliability, security, & self-protection, including
- routing protocol enabling low-power, reactive multi-path discovery (RPL-P2P, RFC6997)
- routing topology authentication mechanisms protecting against insider attacks (TRAIL).

Innovative Image Processing Techniques:
Design of Daviko video triggers, based on novel online crowd detection algorithms. Implementation, pretest & demo using live data from SAGEM IR camera & Microsoft Kinect.

Innovative Knowledge Fusion Framework:
Design of a novel modular architecture for knowledge fusion & processing for complex distributed event detection. Implementation applied to crowd monitoring. Demo with simple (threshold-based) rules, focusing on crowd-density & crowd-size.

Some software components of SAFEST, released as open source, including RIOT (www.riot-os.org) and CAF (www.actor-framework.org), are gaining momentum in the community, and being reused in a variety of other research domains, and are currently tested in the industry.

The work accomplished in SAFEST yielded dozens of publications co-authored by project partners in international conferences, journals (IEEE, ACM ...) in the relevant scientific domains. Project partners have also co-organized several workshops in the context of SAFEST scientific activities.

The prototype of the SAFEST system, or components of the SAFEST system were presented in various world-class venues, including CeBIT 2014.

A significant part of the software produced in SAFEST is released as open source, including RIOT and CAF, which are both gaining momentum in the community, and being reused in a variety of other research domains.

Public spaces, such as airports, railway stations, or stadiums bring together large numbers of people on limited space to use security-sensitive infrastructure. These spaces pose two distinct challenges to public security: (a) detecting unauthorized intrusions and (b) monitoring large crowds in order to provide guidance in case of unexpected events (e.g., a mass panic). To ensure the safety of the general public as well as individuals, we thus require a flexible and intelligent method for area surveillance. One example in which current monitoring systems proved to be dangerously inefficient is the Love Parade music festival in Duisburg, Germany, July 2010. Crowd control failed to provide guidance to a large crowd, resulting in a mass panic with 21 deaths and several hundred injured. In this particular case, overloaded communication infrastructure led to a lack of information about the density and the movement of the crowd, which in turn resulted in misjudgments on appropriate strategies to resolve the situation. This incident highlights the need for more sophisticated and reliable methods for area surveillance.
The SAFEST project, as presented in this text, aims at analyzing the social context of area surveillance and developing a system that can fulfill this task, both in terms of technology as well as acceptance by the general public. Said system is envisioned to be easy to deploy, inexpensive, resilient against malfunctions of individual components, and to respect the privacy of citizens. The system will operate in distributed way, collect anonymized data, securely transfer this data to a central location for evaluation, and – if necessary – notify the operator and/or issue alerts directly to the general public. Work on the technical aspects of the system is accompanied by social studies investigating the individual perception of risk and the methods for reaching public acceptance of technical solutions.
The consortium for the SAFEST project consists of eight partners, comprises a national coordi- nator for security-related research, universities, national institutes for applied research, and industry partners (including one operator of security-critical infrastructures). Within the consortium, Sagem D ´efense S ´ecurit ´e (SAGEM) will adapt its sensing platform to monitor human movement; the Institut National de Recherche en Informatique et en Automatique (INRIA) will provide a reliable communi- cation mechanism that is capable of covering large areas; and Hamburg University of Applied Sciences (HAW) will establish the end-to-end security between devices. Based upon this platform, Freie Uni- versita ¨t Berlin (FU) will detect security-relevant situations; Fraunhofer Institute for Software and Systems Engineering (ISST) will aggregate the information and alert affected individuals; and daviko GmbH (DAV) will contribute video support for the system. The Forschungsforum O ¨ffentliche Sicher- heit (FO ¨ S) will investigate privacy and acceptance issues related this approach and provide guidance with regard to legal and social implications. To ensure the real-world applicability of the project re- sults, a demonstrator of the system will be evaluated at Berlin Brandenburg International airport, which is currently being constructed by Flughafen Berlin Scho ¨nefeld GmbH (FBS).
The SAFEST project addresses the following topics relevant to the call: It proposes a solution for crisis management, addressing social, technical, and economic issues; it enhances the protection of the population against risks and dangers, including the evaluation of acceptance of said solution; and it addresses the protection of critical infrastructures by the means of a comprehensive technical solution. Furthermore, the bi-national structure of the French/German project consortium enables the pursuit of these goals while sharing of knowledge and expertise for the mutual benefit of the partners.

Project coordinator

Monsieur Emmanuel BACCELLI (Institut National de Recherche en Informatique et en Automatique - centre de recherche INRIA Saclay - Île-de-France / EPI HIPERCOM) – emmanuel.baccelli@inria.fr

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.


FBS Flughafen Berlin Schönefeld GmbH
FÖS Forschungsforum Öffentliche Sicherheit
Daviko Daviko GmbH
HAW Hochschule für Angewandte Wissenschaften Hamburg
Fraunhofer Fraunhofer Instituts für Software und Systemtechnik (ISST)
FUB Freie Universität Berlin
INRIA-Saclay-Ile-de-France / EPI HIPERCOM Institut National de Recherche en Informatique et en Automatique - centre de recherche INRIA Saclay - Île-de-France / EPI HIPERCOM

Help of the ANR 609,467 euros
Beginning and duration of the scientific project: March 2012 - 36 Months

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