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Marco Pellinacci

dblp:05/799 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Cyber-physical and IoT security · 50% Network security · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network security › intrusion detection and prevention › intrusion detection › intrusion detection system
distributed intrusion detection
0.112008
Consensus-based distributed intrusion detection for multi-robot systems · ICRA 2008
Cyber-physical and IoT security › robot security
multi-robot system security
0.112008
Consensus-based distributed intrusion detection for multi-robot systems · ICRA 2008
Distributed systems
consensus
0.012008
Consensus-based distributed intrusion detection for multi-robot systems · ICRA 2008

Methods — techniques the papers use, named apart from their topics

simulation · 0.2consensus algorithm · 0.2
YearPublicationVenuePosition
2008 Consensus-based distributed intrusion detection for multi-robot systems
abstract
This paper addresses a security problem in robotic multi-agent systems, where agents are supposed to cooperate according to a shared protocol. A distributed Intrusion Detection System (IDS) is proposed here, that detects possible non-cooperative agents. Previous work by the authors showed how single monitors embedded on-board the agents can detect non- cooperative behavior, using only locally available information. In this paper, we allow such monitors to share the collected information in order to overcome their sensing limitation. In this perspective, we show how an agreement on the type of behavior of a target-robot may be reached by the monitors, through execution of a suitable consensus algorithm. After formulating a consensus problem over non-scalar quantities, and with a generic update function, we provide conditions for the consensus convergence and an upper bound to its transient duration. Effectiveness of the proposed solution is finally shown through simulation of a case study.
Adriano Fagiolini, Marco Pellinacci, Gianni Valenti, Gianluca Dini, Antonio Bicchi
ICRA2