Contiki Operating System Research Articles

CERP: Cooperative and Efficient Routing Protocol for Wireless Sensor Networks.

Wireless sensor networks (WSNs), constrained by limited resources, demand routing strategies that prioritize energy efficiency. The tactic of cooperative routing, which leverages the broadcast nature of wireless channels, has garnered attention for its capability to amplify routing efficacy. This manuscript introduces a power-conscious routing approach, tailored for resource-restricted WSNs. By exploiting cooperative communications, we introduce an innovative relay node selection technique within clustered networks, aiming to curtail energy usage while safeguarding data dependability. This inventive methodology has been amalgamated into the Routing Protocol for Low-Power and Lossy Networks (RPL), giving rise to the cooperative and efficient routing protocol (CERP). The devised CERP protocol pinpoints and selects the most efficacious relay node, ensuring that packet transmission is both energy-minimal and reliable. Performance evaluations were executed to substantiate the proposed strategy, and its practicality was examined using an Arduino-based sensor node and the Contiki operating system in real-world scenarios. The outcomes affirm the efficacy of the proposed strategy, outshining the standard RPL concerning reliability and energy conservation, enhancing RPL reliability by 10% and energy savings by 18%. This paper is posited to contribute to the evolution of power-conscious routing strategies for WSNs, crucial for prolonging sensor node battery longevity while sustaining dependable communication.

A novel scheme based on coarse‐grained localization and fine‐grained isolation for defending against Sybil attack in low power and lossy networks

AbstractDue to the lack of security mechanisms and sensor resources, the IPv6 Routing Protocol for Low power and Lossy networks (RPL) is vulnerable to various attacks, among which Sybil attack has received a lot of attention. This paper proposes a novel scheme based on coarse‐grained localization and fine‐grained isolation (CLFI) for defending Sybil attack. In CLFI, normal neighbor nodes are identified based on received signal strength indicator (RSSI). To further identify Sybil nodes, a physical address identifier called is defined, which is calculated as the difference of RSSI at two different receivers when they are receiving the same packet. In order to facilitate the calculation of , a set of anchor nodes are deployed to broadcast the received RPL control packets. Then Sybil behaviors can be detected by comparing the physical address identifier with the logical address embedded in the received packets. The proposed CLFI scheme has been completely implemented in the Contiki operating system. The extensive evaluation in comparison with the state‐of‐the‐art scheme indicates that CLFI can quickly localize and isolate Sybil nodes.

Efficient Secure Routing Mechanisms for the Low-Powered IoT Network: A Literature Review

The Wireless Sensor Network in the Internet of Things (WSN-IoT) has been flourishing as another global breakthrough over the past few years. The WSN-IoT is reforming the way we live today by spreading through all areas of life, including the dangerous demographic aging crisis and the subsequent decline of jobs. For a company to increase revenues and cost-effectiveness growth should be customer-centered and agile within an organization. WSN-IoT networks have simultaneously faced threats, such as sniffing, spoofing, and intruders. However, WSN-IoT networks are often made up of multiple embedded devices (sensors and actuators) with limited resources that are joined via various connections in a low-power and lossy manner. However, to our knowledge, no research has yet been conducted into the security methods. Recently, a Contiki operating system’s partial implementation of Routing Protocol for Low Power & Lossy Network RPL’s security mechanisms was published, allowing us to evaluate RPL’s security methods. This paper presents a critical analysis of security issues in the WSN-IoT and applications of WSN-IoT, along with network management details using machine learning. The paper gives insights into the Internet of Things in Low Power Networks (IoT-LPN) architecture, research challenges of the Internet of Things in Low Power Networks, network attacks in WSN-IoT infrastructures, and the significant WSN-IoT objectives that need to be accompanied by current WSN-IoT frameworks. Several applied WSN-IoT security mechanisms and recent contributions have been considered, and their boundaries have been stated to be a significant research area in the future. Moreover, various low-powered IoT protocols have been further discussed and evaluated, along with their limitations. Finally, a comparative analysis is performed to assess the proposed work’s performance. The study shows that the proposed work covers a wide range of factors, whereas the rest of the research in the literature is limited.

Development of a Crop Spectral Reflectance Sensor

In this study, a low-cost, self-balancing crop spectral reflectance sensor (CSRS) was designed for real-time, nondestructive monitoring of the spectral reflectance and vegetation index of crops such as tomato and rapeseed. The sensor had a field of view of 30°, and a narrow-band filter was used for light splitting. The filter’s full width at half-maximum was 10 nm, and the spectral bands were 710 nm and 870 nm. The sensor was powered by a battery and used WiFi for communication. Its software was based on the Contiki operating system. To make the sensor work in different light intensity conditions, the photoelectric conversion automatic gain circuit had a total of 255 combinations of amplification. The gimbal of the sensor was mainly composed of an inner ring and an outer ring. Under the gravity of the sensor, the central axis of the sensor remained vertical, such that the up-facing and down-facing photosensitive units stayed in the horizontal position. The mechanical components of the sensor were designed symmetrically to facilitate equal mass distribution and to meet the needs of automatic balancing. Based on the optical signal transmission process of the sensor and the dark-current characteristics of the photodetector, a calibration method was theoretically deduced, which improved the accuracy and stability of the sensor under different ambient light intensities. The calibration method is also applicable for the calibration of other crop growth information sensors. Next, the standard reflectance gray scale was taken as the measurement variable to test the accuracy of the sensor, and the results showed that the root mean square error of the reflectance measured by the sensor at 710 nm and 870 nm was 1.10% and 1.27%, respectively; the mean absolute error was 0.95% and 0.89%, respectively; the relative error was below 4% and 3%, respectively; and the coefficient of variation was between 1.0% and 2.5%. The reflectance data measured by the sensor under different ambient light intensities suggested that the absolute error of the sensor was within ±0.5%, and the coefficients of variation at the two spectral bands were 1.04% and 0.39%, respectively. With tomato and rapeseed as the monitoring targets, the proposed CSRS and a commercial spectroradiometer were used to measure at the same time. The results showed that the reflectance measured by the two devices was very close, and there was a linear relationship between the normalized difference vegetation index of the CSRS and that of the commercial spectroradiometer. The coefficient of determination (R2) for tomato and rapeseed were 0.9540 and 0.9110, respectively.

Implementation of Elliptical Curve Cryptography Based Diffie-Hellman Key Exchange Mechanism in Contiki Operating System for Internet of Things

Wireless Sensor Networks have gradually upgraded to Internet of Things (IoT) of embedded devices wherein the constrained devices have been connected directly onto the Internet. This transformation has not only facilitated the expansion in connectivity and accessibility of the sensor network but has also enabled one sensor network to interact with other through Internet. Security of IoT devices has been researched extensively. The challenge to transform the complex cryptographic algorithms into lighter and faster has kept researchers on their toes. Contiki-OS is one of the purest implementations of 6LoWPAN and IEEE 802.15.4. That makes Contiki-OS lightest and therefore preferred OS for implementation on ultra-low power sensor nodes. Elliptical Cryptography has proved to be the choice of most of the security researchers for constrained devices. However, there is very limited literature available on implementation of Elliptical Cryptography on Contiki-OS. The open-source libraries available for security implementation have not found to be supporting Cooja simulator of Contiki-OS. In this research work we demonstrate improved results in processing the Elliptical Cryptography Based implementation of Diffie-Hellman Key exchange mechanism in Contiki-OS using Cooja simulator. SECP160K1 curve has been implemented and the results in terms of ECDH computational time have been compared with previously published research works. This research demonstrates improved results in Cooja simulator than previous known results on hardware providing a leap ahead in efficiency of implementation.

MMEDD: Multithreading Model for an Efficient Data Delivery in wireless sensor networks

Nowadays, the use of Wireless Sensor Networks (WSNs) is increasingly growing as they allow a large number of applications. In a large scale sensor network, communication among sensors is achieved by using a multihop communication. However, since the sensor is limited by its resources, sensors' operating systems are developed in order to optimize the management of these resources, especially the power consumption. Therefore, the hybrid operating system Contiki uses a low consumption layer called Rime which allows sensors to perform multihop sending with a low energy cost. This is favored by the implementation of lightweight processes called protothreads. These processes have a good efficiency/consumption ratio for monolithic tasks, but the management of several tasks remains a problem. In order to enable multitasking, Contiki provides to users a preemptive multithreading module that allows the management of multiple threads. However, it usually causes greater energy wastage. To improve multithreading in sensor networks, a Multithreading Model for an Efficient Data Delivery (MMEDD) using protothreads is proposed in this paper. Intensive experiments have been conducted on COOJA simulator that is integrated in Contiki. The results show that MMEDD provides better ratio message reception rate/energy consumption than other architectures.

Design Prototype and Security Analysis of a Lightweight Joint Compression and Encryption Scheme for Resource-Constrained IoT Devices

Compressive sensing (CS) can provide joint compression and encryption, which is promising to address the challenges of massive sensor data and data security in the Internet of Things (IoT). However, as IoT devices have constrained memory, computing power, and energy, in practice the CS-based computationally secure scheme is shown to be vulnerable to ciphertext-only attack for short-signal length. Although the CS-based perfectly secure scheme has no such vulnerabilities, its practical realization is challenging. In this article, we propose an energy concealment (EC) encryption scheme, a practical realization of the perfectly secure scheme by concealing energy, thereby removing the requirement of an additional secure channel. We propose three different methods to generate sensing matrix to improve energy efficiency using linear feedback shift registers and lagged Fibonacci sequences. Leveraging the signal’s maximum energy in the EC scheme, we design a new measure to evaluate reconstructed signal quality without the knowledge of the original signal. Furthermore, a new CS decoding algorithm is designed by incorporating the knowledge of maximum energy at the decoder, which improves the signal reconstruction quality while reducing the number of measurements. Additionally, our comprehensive security analysis shows that the EC scheme is secure against various cryptographic attacks. We implement the EC scheme using the three different ways of generating the sensing matrix in the resource-constrained TelosB mote using the Contiki operating system. The experimental results demonstrate that the EC scheme outperforms advanced encryption standard in terms of code memory footprint and total energy consumption.

Radio Wave Attenuation Measurement System Based on RSSI for Precision Agriculture: Application to Tomato Greenhouses

Precision agriculture and smart farming are concepts that are acquiring an important boom due to their relationship with the Internet of Things (IoT), especially in the search for new mechanisms and procedures that allow for sustainable and efficient agriculture to meet future demand from an increasing population. Both concepts require the deployment of sensor networks that monitor agricultural variables for the integration of spatial and temporal agricultural data. This paper presents a system that has been developed to measure the attenuation of radio waves in the 2.4 GHz free band (ISM- Industrial, Scientific and Medical) when propagating inside a tomato greenhouse based on the received signal strength indicator (RSSI), and a procedure for using the system to measure RSSI at different distances and heights. The system is based on Zolertia Re-Mote nodes with the Contiki operating system and a Raspberry Pi to record the data obtained. The receiver node records the RSSI at different locations in the greenhouse with the transmitter node and at different heights. In addition, a study of the radio wave attenuation was measured in a tomato greenhouse, and we publish the corresponding obtained dataset in order to share with the research community.

Coffee forensics — Reconstructing data in IoT devices running Contiki OS

The ability to examine evidence and reconstruct files from novel IoT operating systems, such as Contiki with its Coffee File System, is becoming vital in digital forensic investigations. Two main challenges for an investigator facing such devices are that (i) the forensic artifacts of the file system are not well documented, and (ii) there is a lack of available forensic tools. To meet these challenges, we use code review and an emulator to gain insight into the Coffee file system, including its functionality, and implement reconstruction of deleted and modified data from extracted flash memory in software. We have integrated this into a forensic tool, COFFOR, and analyzed the Coffee File System to reconstruct deleted and modified files. This paper presents an overview of the artifacts in the file system and implements methods for the chronological ordering of the deleted file versions, and discusses these methods’ limitations. Our results demonstrate that forensic acquisition and analysis of devices running the Contiki operating system can reveal live and deleted files, as well as file version history. In some cases, a complete, chronological ordering of the version history can be reconstructed.

Modified CSMA/CA protocol for real-time data fusion applications based on clustered WSN

The large amount of data generated by the Internet of Things (IoT) is exploited by the data fusion process to improve the quality of services (QoS) requested by the user. Data fusion systems typically collect and fuse data from various sensor nodes to achieve better data quality (more precision, accuracy, or global view) on the field of interest. For the specific case of the wireless sensor network (WSN) based on cluster-tree topology, the data transmission between nodes and the intermediate data fusion node (DFN) depends primarily on the channel access often managed by the Carrier-Sens Multiple Access with Collision Avoidance (CSMA/CA) protocol. In this article, a modified CSMA/CA is proposed to meet the requirements of the WSN real-time data fusion applications and, in particular, to ensure better management of the transmission channel. It takes into account a transmission time-delay, schedules the retransmission dynamically, and eliminates data packets scheduled beyond the predefined time-delay, thereby releasing the channel to the benefit of other nodes. Moreover, before proceeding with the fusion at the DFN level, it optimizes the probability of receiving data from each node in the specified time-delay. The proposed solution is implemented under the Contiki operating system; it aims to collect data from all nodes within a given time-delay. The results of simulations and experiments show increasing in the data received within time-delay, collisions reduction, and saving energy in the WSN. Moreover, two real-time data fusion applications, namely mobile localization and majority decision-making, are also simulated to support the found results. Compared to the use of CSMA/CA as implemented in Contiki, using the proposed modified CSMA/CA in both data fusion applications improves QoS.

A hybrid objective function with empirical stability aware to improve RPL for IoT applications

The diverse applications of the internet of things (IoT) require adaptable routing protocol able to cope with several constraints. Thus, RPL protocol was designed to meet the needs for IoT networks categorized as low power and lossy networks (LLN). RPL uses an objective function based on specific metrics for preferred parents selection through these packets are sent to root. The single routing metric issue generally doesn’t satisfy all routing performance requirements, whereas some are improved others are degraded. In that purpose, we propose a hybrid objective function with empirical stability aware (HOFESA), implemented in the network layer of the embedded operating system CONTIKI, which combines linearly three weighty metrics namely hop count, RSSI and node energy consumption. Also, To remedy to frequent preferred parents changes problems caused by taking into account more than one metric, our proposal relies on static and empirical thresholds. The designed HOFESA, evaluated under COOJA emulator against Standard-RPL and EC-OF, showed a packet delivery ratio improvement, a decrease in the power consumption, the convergence time and DIO control messages as well as it gives network stability through an adequate churn.

Scalability Analysis of Privacy Enabled IPv6 Addressing Protocol for Duty Cycled 6LoWPAN

Background: The privacy enabled IPv6 addressing mechanism ensures the privacy of the node's identification in the communication messages. It makes it difficult for adversaries to track nodes and link any activities with the node's IP or the MAC address. Scalability of the privacy enabled IPv6 addressing scheme for 6LoWPAN may be affected due to underlying MAC layer mechanisms. Objective: Hence, this study aims to explore such an impact. Methods: Addressing scheme is implemented in the Contiki operating system which uses duty cycling at the MAC layer along with the CSMA channel access mechanism. ContikiMAC and CXMAC are widely used duty cycling protocols in Contiki. An analytical study is presented in this paper, which analyses the IPv6 address configuration delay with ContikiMAC and CXMAC. Simulation is performed to corroborate the presented analytical model. The address configuration latency limits the scalability of the network. Hence, this paper studies the impact of duty cycling of the nodes on the address configuration latency and estimates the size of a single hop PAN. Results & Conclusion: It is observed that the ContikiMAC duty cycling protocol can achieve better performance compared to the CXMAC protocol in terms of address configuration latency. In order to make up for the delay due to duty cycling, the network can be divided into multiple PANs of smaller sizes where the addressing process runs simultaneously.

AIEMLA: artificial intelligence enabled machine learning approach for routing attacks on internet of things

The Internet of things (IoT) is emerging as a prime area of research in the modern era. The significance of IoT in the daily life is increasing due to the increase in objects or things connected to the internet. In this paper, routing protocol for low power and lossy networks (RPL) is examined on the Contiki operating system. This paper used RPL attack framework to simulate three RPL attacks, namely hello-flood, decreased-rank and increased-version. These attacks are simulated in a separate and simultaneous manner. The focus remained on the detection of these attacks through artificial neural network (ANN)-based supervised machine learning approach. The accurate detection of the malicious nodes prevents the network from the severe effects of the attack. The accuracy of the proposed model is computed with hold-out approach and tenfold cross-validation technique. The hyperparameters have been optimized through parameter tuning. The model presented in this paper detected the aforesaid attacks simultaneously as well as individually with 100% accuracy. This work also investigated other performance measures like precision, recall, F1-score and Mathews correlation coefficient (MCC).

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

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.

Enhancing Routing Security in IoT: Performance Evaluation of RPL’s Secure Mode Under Attacks

As the Routing Protocol for Low Power and Lossy Networks (RPL) became the standard for routing in the Internet of Things (IoT) networks, many researchers had investigated the security aspects of this protocol. However, no work (to the best of our knowledge) has investigated the use of the security mechanisms included in RPL standard, mainly because there was no implementation for these features in any IoT operating systems yet. A partial implementation of RPL security mechanisms was presented recently for the Contiki operating system (by Perazzo et al.), which provided us with an opportunity to examine RPL security mechanisms. In this paper, we investigate the effects and challenges of using RPL security mechanisms under common routing attacks. First, a comparison of RPL performance, with and without its security mechanisms, under four routing attacks (Blackhole, Selective-Forward, Neighbor, and Wormhole attacks) is conducted using several metrics (e.g., average data packet delivery rate, average data packet delay, average power consumption, etc.). This comparison is performed using two commonly used Radio Duty-Cycle protocols. Secondly, and based on the observations from this comparison, we propose two techniques that could reduce the effects of such attacks, without having added security mechanisms for RPL. An evaluation of these techniques shows improved performance of RPL under the investigated attacks, except for the Wormhole attack.

RPL routing protocol performance under sinkhole and selective forwarding attack: experimental and simulated evaluation

To make possible dream of connecting 30 billion smart devices assessable from anywhere, anytime and to fuel the engine growth of Internet of things (IoT) both in terms of physical and virtual things, Internet Engineering Task Force (IETF) came up with a concept of 6LoWPAN possessing characteristics like low power, bandwidth and cost. To bridge the routing gap and to collaborate between low power private area network and the outside world, IETF ROLL group proposed IPv6 based lightweight standard RPL (Routing protocol for low power and lossy networks). Due to large chunks of random data generated on daily basis security either externally or internally always remain bigger threat which may lead to devastation and eventually degrades the quality of service parameters affecting network resources. This paper evaluates and compare the effect of internal attacks like sinkhole and selective forwarding attacks on routing protocol for low power and lossy network topology. Widely known IoT operating system Contiki and Cooja as the simulator are used to analyse different consequences on low power and lossy network.

Design and analysis of RPL objective functions using variant routing metrics for IoT applications

The main objective of Internet of Things (IoT) is to connect almost all the devices anywhere and everywhere in the world. IoT network is heterogeneous in nature, hence routing the data packets in this network is a big challenge. Routing Protocol for Low Power Lossy Network (RPL), has been designed by Internet Engineering Task Force (IETF) for such type of network. The existing design of RPL Objective Function (OF) is insufficient to cover all the issues of IoT applications. In this paper, the proposed OFs designs using various routing metrics are used to enhance the performance of the IoT applications. The analysis for various scenarios for these designs shows that only traditional hop and Expected Transmission Count (ETX) routing parameters will not fit for the smart applications need. The routing metric selection according to the application requirement is the principal idea of the proposed design. Three metrics ETX, Content and Energy, single and combination with each other are used to enhance the design of objective function of RPL for IoT applications. The enhanced triggering technique is added in these designs for the improvement of RPL. This technique will eliminate the cumulative effect of the short-listen problem of default trickle timer. The result analysis done using Cooja simulator along with Contiki Operating System (OS) states that, all the designs are performing well in one or other manner than the traditional OF. Energy combined with Content (EC) and aggregation with Enhanced timer (EC_En_Timer) design gives better result for Packet Delivery Ratio (PDR) and Latency Delay (LD) as compared to default OF design. Residual Energy (RE) combined with ETX (EE) and conjunction with Enhanced timer (EE_En_Timer) design works well for energy consumption. Overhead is very less in RE and ETX design. Conversion time is reduced by almost 50% in an En_Timer design. Higher PDR and low delay values of EC and EC_En_Timer design encourages its use in health monitoring application where reliability is essential. Low energy consumption results of RE, EE and EE_En_Timer designs are comfortable for forest monitoring application, as energy is a crucial aspect. This comparative result outcome will help to fulfill the IoT application requirements.

RIoT: A Routing Protocol for the Internet of Things†

AbstractThe routing protocol for low-power and lossy networks (RPL) is a standard routing framework for Internet of Things (IoT). It supports multipoint-to-point (MP-to-P), point-to-point (P-to-P) and point-to-multipoint (P-to-MP) communications. It is known that RPL’s control overhead can result in the protocol’s poor performance in P-to-P and P-to-MP communications especially in its non-storing mode of operation. Here, we present a routing protocol for the Internet of Things (RIoT) that supports MP-to-P, P-to-P and P-to-MP communications. The protocol can construct P-to-P and P-to-MP routes with relatively lower control overhead. Another salient feature of RIoT is that it supports multiple gateways in the same network with an aim to reduce memory requirement for storing a forwarding table. Furthermore, RIoT is also capable of handling mobility-based IoT use cases. To facilitate communication among nodes connected to different gateways in the same network, here we also present an inter-gateway communication mechanism. We implemented RIoT in the Contiki operating system, and it is extensively evaluated using emulation and real testbed-based experiments. We analyzed the impact of the number of gateways, radio duty cycling (RDC) and mobility on the routing protocols’ performance. Our results demonstrate that either with or without RDC RIoT demonstrates statistically significantly better packet delivery ratio, per-packet end-to-end delay and control overhead compared to the RPL-based protocol. RIoT’s multi-gateway communication architecture substantially reduces the memory requirement to store a forwarding table. Our results also demonstrate that multiple gateways in a network reduce the network partitioning problem in mobile scenarios. Hence, RIoT also demonstrates better performance in mobile scenarios compared to the RPL-based protocol.

Routing protocol for Low-Power and Lossy Networks for heterogeneous traffic network

In a real network deployment, the diverse sensor applications generate a heterogeneous traffic pattern which may include basic sensing measurements such as temperature readings or high-volume multimedia traffic. In a heterogeneous traffic network, the two standardized objective functions (OFs), i.e., objective function zero (OF0) and the Minimum Rank with Hysteresis Objective Function (MRHOF) for routing protocol for Low-Power and Lossy Networks (RPL) perform poor routing decisions by selecting an already congested parent node and cause more re-transmissions across the network. Therefore, careful consideration is required in designing a new OF for heterogeneous traffic scenarios. In this study, we examine the RPL protocol under a heterogeneous traffic pattern and proposed a new protocol based on queue and workload-based condition (QWL-RPL). The aim of the proposed protocol is to achieve a reliable path with better overall performance. The proposed OF model considers the link workload in addition to mapping the congestion status of the node using the packet queue. We implement the proposed routing model in the Contiki operating system (OS) Cooja environment to compare with the existing technique. The simulation results show that QWL-RPL can improve the performance of a heterogeneous traffic network as compared with both OF0 and MRHOF, specifically in terms of the amount of overhead, packets reception ratio (PRR), average delay, and jitter. Final results indicate that on average, there is a 5%–30% improvement in PRR, 25%–45% reduction in overheads, 12%–30% reduction in average delay, and 20%–40% reduction in jitter.

An intrusion detection framework for energy constrained IoT devices

• We present a novel intrusion detection framework for industrial IoT applications. • We investigate intrusion detection via collaboration between device and edge IoT. • A formal evaluation for security capabilities of proposed framework is presented. • Rigorous evaluation of proposed framework demonstrates its performance efficiency. Industrial Internet of Things (IIoT) exemplifies IoT with applications in manufacturing, surveillance, automotive, smart buildings, homes and transport. It leverages sensor technology, cutting edge communication and data analytics technologies and the open Internet to consolidate IT and operational technology (OT) aiming to achieve cost and performance benefits. However, the underlying resource constraints and ad hoc nature of such systems have significant implications especially in achieving effective intrusion detection. Consequently, contemporary solutions requiring a stable infrastructure and extensive computational resources are inadequate to fulfill these characteristics of an IIoT system. In this paper, we propose an intrusion detection framework for the energy-constrained IoT devices which form the foundation of an IIoT ecosystem. In view of the ad hoc nature of such systems as well as emerging complex threats such as botnets, we assess the feasibility of collaboration between the host (IoT devices) and the edge devices for effective intrusion detection whilst minimizing energy consumption and communication overhead. We implemented the proposed framework with Contiki operating system and conducted rigorous evaluation to identify potential performance trade-offs. The evaluation results demonstrate that the proposed framework can minimize energy and communication overheads whilst achieving an effective collaborative intrusion detection for IIoT systems.