In recent years, many technologies were racing to deliver the best service for human being Emerging Internet of Things (IoT) technologies made birth to the notion of smart infrastructures such as smart grid, smart factories or smart hospitals These infrastructures rely on interconnected smart devices collecting real-time data in order to improve existing procedures and systems capabilities A critical issue in smart infrastructures is the information protection which may be more valuable than physical assets Therefore, it is extremely important to detect and deter any attacks or breath to the network system for information theft One of these attacks is the rank attack that is carried out by an intruder node in order to attract legitimate traffic to it, then steal personal data of different persons (both patients and staffs in hospitals) In this paper, we propose an anomaly based rank attack detection system against an IoT network using Support Vector Machines As a use case, we are interested in the healthcare sector and in particular in smart hospitals which are multifaceted with many challenges such as service resilience, assets interoperability and sensitive information protection The proposed intrusion detection system (IDS) is implemented and evaluated using Conticki Cooja simulator Results show a high detection accuracy and low false positive rates

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Machine Learning Based Rank Attack Detection for Smart Hospital Infrastructure

In critical Internet of Things (IoT) application domains, such as the Defense Industry and Healthcare, false alerts have many negative effects, such as fear, disruption of emergency services, and waste of resources. Therefore, an alert must only be sent if triggered by a correct event. Nevertheless, IoT networks are exposed to intrusions, which affects event detection accuracy. In this paper, an Anomaly Detection System (ADS) is proposed in a smart hospital IoT system for detecting events of interest about patients’ health and environment and, at the same time, for network intrusions. Providing a single system for network infrastructure supervision and e-health monitoring has been shown to optimize resources and enforce the system reliability. Consequently, decisions regarding patients’ care and their environments’ adaptation are more accurate. The low latency is ensured, thanks to a deployment on the edge to allow for a processing close to data sources. The proposed ADS is implemented and evaluated while using Contiki Cooja simulator and the e-health event detection is based on a realistic data-set analysis. The results show a high detection accuracy for both e-health related events and IoT network intrusions.

Efficient Anomaly Detection for Smart Hospital IoT Systems.

Wireless sensor networks consist of a large number of nodes deployed randomly in an area of interest. Theses nodes have sensing, computation, and wireless communications capabilities. In another hand nodes have energy constraints since they are equipped by non-rechargeable batteries. To handle this issue, routing protocols consist of designing the network in order to collect and transmit data with less energy consumption. In this paper we presented a new Hybrid Energy Efficient Static routing protocol (HEESR), combining between clustering and multi-hop routing techniques. HEESR is dividing the network into several levels. For each round, it creates clusters, route the collected data through gateways called Independent Nodes, elected using a new dynamic approach and introduces Dormant nodes. Finally, the proposed HEESR have improved network’s life time, throughput and other compared metrics, in both homogeneous and heterogeneous networks, and prolonged network’s stability zone up to 98.4% compared to LEACH, 98% compared to DEEC and up to 40.5% compared to SMR.

Hybrid energy efficient static routing protocol for homogeneous and heterogeneous large scale WSN

Faced to challenges of low power and lossy networks (LLN’s) as well as the nature of these networks without infrastructure, it remains the subject of several researches to deal with routing constraints and thus propose adapted routing protocols according to different applications. In this context, a protocol based on Ipv6 RPL has been standardized to meet the requirements of low power and lossy networks. RPL centralizes traffic to one or more nodes through the construction of a Destination Oriented Directed Acyclic Graph (DODAG) based on a specific objective function. Nevertheless, the objective function influences the behavior of the routing protocol, so that the design must follow the prerequisites of each application. The problem of standardized objective functions is found in their routing paths selection, they are not based on different criteria which leads to unoptimized choices of routes which affects the network quality of services . Thus, we propose in this paper a new objective function IRH-OF based on designed combined metric cmIRH for rank calculation. Our proposed method, injected on the core of Contiki Operating System, ensures a better quality of services compared to other objective functions. The results showed that the new objective function can maintain a packet delivery ratio higher than 98% regardless of density, decreases approximately with 45% the average power consumption of the network, achieves a less convergence time and latency.

IRH-OF: A New Objective Function for RPL Routing Protocol in IoT Applications

The rise of the Internet of Things (IoT) and the diversity of its applications make the need for a flexible routing protocol able to face several constraints very essential. In this context, the RPL protocol was designed to meet the need for IoT classified as low power and lossy networks (LLN's). RPL relies on an objective function that takes into account a metric to implement its routing strategy in the network. On the other hand, the problem consists of a single routing metric that sometimes leads to the selection of non-optimized or static routes in the network. As a consequence, two main problems emerge, the first is the congestion created in the nodes due to the high number of packets to be relayed which leads to their loss, the second is the greedy energy consumption by these nodes which can conduct to quickly degrade their batteries, thus losing and causing loss the connectivity of several nodes in the network. To remedy this problem, a novel objective function for RPL FTC-OF has been implemented in the core of the embedded operating system CONTIKI, which combines three different routing metrics, aiming to create a balanced network while considering the quality of link on a short path, namely hop count, RSSI and a newly designed metric called Forwarded Traffic Metric (FTM). The proposed method, considered as a new balancing strategy, evaluated under the COOJA emulator, outperforms ETX and Energy based RPL protocols. It shows that it increases the rate of packet delivery, considerably reduces the power consumption of the network as well as an almost perfect balance of traffic managed by the relay nodes.

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FTC-OF: Forwarding Traffic Consciousness Objective Function for RPL Routing Protocol

6LowPAN is an implementation of wireless sensor networks that using IPv6 to address sensors in the network. It’s classified as a new technology that still in development. Therefore, IETF has proposed an IPv6 based routing protocol with low cost and power constraints. This routing protocol for Low power and lossy networks (RPL) selects the ideal routes from a source to a destination node based on certain metric injected into the objective functions (OF). This paper an assessment of Minimum Rank with Hysteresis Objective Function (MRHOF) and Objective Function Zero (OFO) in a different areas under a large scenarios and two realistic topologies considering the reliability in term of the Packet Delivery Ratio, the power consumption, the average end to end delay and the percentage of radio activity. For this, COOJA is used as a wireless sensor network simulator that emulat software and hardware levels of embedded nodes using contiki OS as a embedded operating system. Based on results of our simulations, we concluded that the choice of given objective function have affect the PDR and E2Edelay and can achieve saved energy levels. In conclusion, we propose to develop as a future work an objective function with hybridization more than one metric in order to deal with the compromise between PDR and energy consumption.

Assessment of a proactive routing protocol RPL in Ipv6 based wireless sensor networks

Since its development by IETF, the IPv6 routing protocol for low power and lossy networks (RPL) remains the subject of several researches. RPL is based on objective function as a mechanism selection of paths in the network. However, the default objective functions standardized selects the routes according to a single routing metric that leads to an unoptimized path selection and a lot of parent changes. Thus, we propose in this paper weighted combined metrics objective function (WCM-OF) and non-weighted combined metrics objective function (NWCM-OF) that are based both on additive link quality and energy metrics with equal weights or not to achieve a tradeoff between reliability and saved energy levels. The proposed objective functions were implemented in the core of Contiki operating system and evaluated with Cooja emulator. Results show that the proposed objective functions improved the network performances compared to default objective functions.

https://www.ijcnis.org/index.php/ijcnis/article/download/4446/379

A New Objective Function Based on Additive Combination of Node and Link Metrics as a Mechanism Path Selection for RPL Protocol

With the arrival of the internet of things concept, a new vision of wireless sensor networks has been adopted allowing them to be addressed with ipv6 addresses, thus forming 6LowPAN networks. It is categorized as a new technology being developed and improved. This causes issues about the networks performance to create the communication path and collecting data. Therefore, IETF has proposed an IPv6 based routing protocol with low cost and power constraints RPL that builds a Destination Oriented Directed Acyclic Graph (DODAG) based on a set of metrics and constraints via a specific Objective Functions (OFs). This objective function selects the best parents and construct the routes. Our research is focus on performance analysis of two objective functions that are Minimum Rank with Hysteresis Objective Function (MRHOF) and Objective Function Zero (OFO) in a small area under a large scenarios and topologies. This comparison is focused on energy consumption of the network in the given scenrios to distinguish which objective function is the most optimal to guarantee long life expectancy of the sensor networks especially in static environment.

https://hal.archives-ouvertes.fr/hal-02298879/document

Abdelhadi Eloudrhiri Hassani

Papers

Assessment of a proactive routing protocol RPL in Ipv6 based wireless sensor networks

A New Objective Function Based on Additive Combination of Node and Link Metrics as a Mechanism Path Selection for RPL Protocol

Impact of RPL objective functions on energy consumption in Ipv6 based wireless sensor networks

IRH-OF: A New Objective Function for RPL Routing Protocol in IoT Applications

FTC-OF: Forwarding Traffic Consciousness Objective Function for RPL Routing Protocol