Efficient monitoring for intrusion detection in wireless sensor networks

Abstract

SummaryIn wireless sensor networks (WSN), Intrusion Detection through sensor monitoring enables the detection of intricate security attacks such as denial of service and routing attacks. However, the monitoring process, which observes sensor behaviour, can induce a large amount of energy and bandwidth overhead, thus reducing the system lifetime. Furthermore, monitors can be attacked and their observations corrupted, which breaks the system security. Therefore, our goal is the design of a reliable and energy‐efficient monitoring system that resists internal security attacks. We present DAMS (Distributed and Adaptable Monitoring System) that extends LEACH protocol with a trust‐based and energy‐efficient clustering protocols for both cluster heads and monitors election. Compared to other LEACH extensions, the obtained topology reduces monitoring energy overhead, improves the system lifetime, and increases the packet delivery ratio.

EE-ISAC—Practical Cybersecurity Solution for the Energy Sector

“…Collaborative Intrusion Detection (CIDS) is a prospective methodology for detecting modern cyberattacks that has been studied already for more than ten years [40]. As a result, a privacy-preserving machine-learning-based CIDS for vehicular ad hoc networks (VANETs) [41], a CIDS for smart grids [42], a trust-based clustering support for deploying CIDS in wireless sensor networks [43], and a CIDS for Advanced Metering Infrastructure (AMI) [44] were proposed. Regarding operational IS or SA architectures, commercial or community-driven platforms such as AlienVault Open Threat Exchange (OTX), the Malware Information Sharing Project (MISP), and ThreatView's Cyber Threat and Reputation Intelligence were introduced.…”

Threat intelligence platform for the energy sector

“…As a promising direction in detecting modern cyberattacks, collaborative intrusion detection system (CIDS) has been studied intensively already for more than a decade . Recent proposals include a privacy‐preserving machine‐learning–based CIDS for vehicular ad hoc networks, a CIDS designed specifically to protect the smart grid, a trust‐based clustering solution that supports deploying CIDS in wireless sensor networks or a CIDS for Advanced Metering Infrastructure …”

Developing novel solutions to realise the European Energy – Information Sharing & Analysis Centre

“…As a promising direction in detecting modern cyberattacks, collaborative intrusion detection (CIDS) has been studied intensively already for more than a decade Locasto et al (2005). Recent proposals include a privacy-preserving machine-learning based CIDS for vehicular ad hoc networks (VANETs) Zhang and Zhu (2018), a CIDS designed specifically to protect the smart grid Patel et al (2017), a trust-based clustering solution that supports deploying CIDS in wireless sensor networks (WSN) Abdellatif and Mosbah (2017) or a CIDS for Advanced Metering Infrastructure (AMI) Liu et al (2015). Several solutions that support situational awareness are described in the edited volume of Jajodia et al Jajodia et al (2010).…”