Lossy Networks Research Articles

A Gaming and Trust-Model-Based Countermeasure for DIS Attack on 6TiSCH IoT Networks

The 6TiSCH communication architecture provides delay-bounded packet delivery, energy-efficient and reliable data-delivering communication in mission-critical Internet of Things (IoT) applications. It uses IETF’s 6TiSCH minimal configuration (6TiSCH-MC) standard for resource allocation during network formation and routing using Routing Protocol for Low power and Lossy network (RPL) as routing protocol. In RPL, the DODAG Information Solicitation (DIS) control packet is used to solicit routing information from the existing networks. However, it is observed that malicious transmission of this DIS packet can severely affect the 6TiSCH networks in terms of nodes’ network joining time and energy consumption. Therefore, designing countermeasures of DIS attack in 6TiSCH network has become critically important. Additionally, the existing works neither considered all the possible parameters together for detecting DIS attack nor energy efficient, and create control packet overhead. In this work, we model non-cooperative gaming to determine the optimal probability of responding to a DIS packet. Subsequently, we design a trust model to detect malicious DIS transmission in 6TiSCH networks. Finally, we merge both the proposed gaming model and trust model to propose a scheme – Gaming and Trust based Counter Measure (GTCM) to reduce the effect of DIS attack in 6TiSCH networks. We implement the GTCM on Contiki-NG and validate it using open source FIT IoT-LAB testbed. Our experimental testbed results show that GTCM reduces the effect of DIS attack in terms of pledges’ (new nodes) joining time and energy consumption significantly.

Congestion and Energy Aware Multipath Load Balancing Routing for LLNs

The Internet of Things (IoT) is presently in its golden era with its current technological evolution towards digital transformation. Low-power and Lossy Networks (LLNs) form the groundwork for IoT, where the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is designated by Internet Engineering Task Force as the benchmark protocol for routing. Although RPL, with its unique capabilities, has addressed many IoT routing requirements, Load balancing and Congestion control are the outliers. This paper builds on the RPL protocol and proposes a multipath Congestion and Energy Aware RPL (CEARPL) that alleviates the load balancing and congestion concerns associated with RPL and improves the network performance. For congestion avoidance, a Congestion and Energy Aware Objective Function (CEA-OF) is suggested during parent selection that considers multiple metrics like Child Count metric, Estimated Lifetime metric, and Queue Occupancy metric, to equally distribute the traffic in LLNs. The Queue Occupancy metric is used to detect congestion in the network, and a Multipath routing strategy is utilized to mitigate the congestion in the network. A comparison of the performance of CEA-RPL was made against the existing Objective Functions of RPL, OFO, and MRHOF, as well as COM-OF, utilizing Contiki OS 3.0's Cooja emulator. CEA-RPL projected superior results with power consumption lowering by 33%, end-to-end delay decreasing by 30%, queue loss ratio reducing by 49%, and packet receiving rate and network lifetime improving by 7% and 49%, on an average, respectively.

Compatible Authentication and Key Agreement Protocol for Low Power and Lossy Network in Iot Environment.

Compatible Authentication and Key Agreement Protocol for Low Power and Lossy Network in Iot Environment.

A New Objective Function for RPL Based on Combined Metrics in Mobile IoT

To satisfy the quality of service requirements for some applications in the Internet of Things (IoT) network with mobile nodes, routing protocols must be adaptable to make better routing decisions. Routing Protocol for Lowpower and Lossy Networks (RPL) is one of the routing protocols that support metrics and constraints while building a Destination Oriented Directed Acyclic Graphs (DODAG) using a specific Objective Function (OF). However, RPL metrics that use standard OFs do not guarantee the performance criteria for a specific mobile IoT in terms of received and lost packets, overhead, throughput and power consumption. In this paper, we propose a new version of mrhof based on a combination of metrics such as total energy, the number of neighbors, and expected transmission count (ETX) to evaluate RPL performances in a mobile context. Then, we compare the assessment of this function to existing OFs based on various mobility models (Random Waypoint (RWP), Reference Point Group Mobility (RPGM), Nomadic) and node densities. The results show that this new function is more efficient than the standards OF in terms of packets received and packets lost with Random Way Point and RPGM models. Regardless of the number of nodes, it also reduces ETX and traffic overhead for all mobility models, as well as convergence time in the Random Waypoint environment. Furthermore, this new function contributes to the improvement of Rtmetric, the enhancement of throughput at low density only in favor of RWP and RPGM models, and an effective power consumption reduction through all densities and mobility models.

Novel Fuzzy-based Objective Function for routing protocol for low power and lossy networks

Novel Fuzzy-based Objective Function for routing protocol for low power and lossy networks

Multiagent Distributed Secondary Control for Energy Storage Systems With Lossy Communication Networks in DC Microgrid

For the energy storage system (ESS) with lossy communication networks of packet loss in DC microgrid, the multiagent distributed secondary control strategy is proposed to manage the ESS. The multiagent dynamic-tracking consensus protocol (DCP) based on the random packet loss model is constructed to estimate the global information for the dynamic network with lossy communication. Then the adaptive current sharing algorithm (ACSA) is designed to balance the state of charge (SoC) for ESSs with different capacities. Furthermore, the data-driven model-free adaptive control (MFAC) scheme is proposed for the single-input multiple-output (SIMO) nonlinear ESS to provide accurate voltage tracking and current sharing. Finally, the real-time simulation tests of different case studies are carried out through the OPAL-RT platform to verify the effectiveness of the designed control strategy. Simulation results can prove that the favorable capabilities of current sharing and voltage regulation as well as robustness to communication packet loss and communication faults can be achieved.

Blackhole attacks in internet of things networks: a review

The internet of things (IoT) is one of data revolution area and is the following extraordinary mechanical jump after the internet. In terms of IoT, it is expected that electronic gadgets that are used on a regular basis would be connected to the current of the internet. IPv6 over low-power wireless personal area networks (6LoWPAN) is a one of IPv6 header pressure technology, and accordingly, it is vulnerable to attack. The IoT is a combination of devices with restricted resource assets like memory, battery power, and computational capability. To solve this, RPL or routing protocol for low power Lossy network is deploy by utilizing a distance vector scheme. One of denial of service (Dos) attack to RPL network is blackhole attack in which the assailant endeavors to become a parent by drawing in a critical volume of traffic to it and drop all packets. In this paper, we discuss research on numerous attacks and current protection methods, focusing on the blackhole attack. There is also discussion of challenge, open research issues and future perspectives in RPL security. Furthermore, research on blackhole attacks and specific detection technique proposed in the literature is also been presented.

Optimal networked state estimation in the presence of multi-channel correlated packet losses

This paper studies the optimal estimation problem for linear time-invariant systems over lossy communication networks subject to multi-channel packet losses. In its full generality, we assume that the random packet losses are spatially correlated across different channels. The problem is addressed by employing a modified Kalman filter to estimate the system’s states, and the primary issue under study is the convergence of the state estimate under a mean-square criterion. This convergence is shown to be equivalent to the existence of a stabilizing solution to a modified algebraic Riccati equation. We provide a necessary and sufficient condition to characterize the existence of the stabilizing solution, and show that the solution can be computed by solving a set of linear matrix inequalities. Additionally, from a robust convergence perspective, we consider further packet losses whose probabilities are unknown and uncertain. We develop a matrix measure referred to as the critical matrix to characterize the maximal tolerance for the modified Kalman filter to converge. Specifically, we show that the mean-square estimation error is bounded if and only if the critical matrix satisfies a positive semi-definiteness condition.

RPL-Based IoT Networks under Simple and Complex Routing Security Attacks: An Experimental Study

Effective security support still remains a challenge even for a standardized Internet of Things network protocol such as the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). It provides limited protection against external security attacks but stays highly vulnerable to internal routing attacks. The inherent RPL design of RPL, particularly its topology establishment and maintenance mechanism, makes it easy to initiate such kinds of attacks which target overall network performance and topology stability. Establishing a firm and practical understanding of the impacts of these attacks on RPL networks is still critically needed for further investigation. This is more demanding when considering varying-scale RPL deployments targeted by complex attack scenarios. In this research work, an extensive experimental study of these critical RPL routing attacks considering simple-to-complex attack scenarios in varying-scale RPL network setups is presented. It provides a practical contribution toward experimentally understanding the effectiveness of internal routing attacks when targeting RPL-based IoT networks. The main objective is to provide future research works with a practical reference to the effectiveness of these security attacks and the overall performance of RPL networks under routing attacks. The results indicate the adverse impacts of routing attacks on the overall performance of RPL networks. Even in simple attack scenarios, it was found that the attacked networks experienced noticeable degradation in QoS performance and topology stability. In addition, the attacks incurred considerable increases in energy consumption and control traffic overhead. These were more evident in large-scale experimental setups and also under composite and hybrid routing attacks. QoS performance and topology stability degraded by more than 90% whereas energy consumption and network overhead increased by more than 200%.

DCS: Dilution-based Convergecast Scheduling in a TSCH network

We describe Dilution-based Convergecast Scheduling (DCS), an algorithm to compute a convergecast tree and a corresponding schedule to Timeslotted Channel Hopping (TSCH) networks. DCS works by dividing the plane into a grid and computing local trees inside each grid box. DCS uses the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) to assign specific labels to nodes (called ranks) and to connect the local trees into a single convergecast tree spanning the whole network. DCS creates schedules that are collision-free. Additionally, differently from existing related approaches, apart from the use of RPL, DCS is itself a collision-free algorithm, i.e., the convergecast tree and the schedules are computed without collision during message transmissions. DCS adapts and implements over contiki-ng and the Cooja simulator a previous scheduling algorithm designed for the Signal-to-Interference-plus-Noise Ratio (SINR) model. contiki-ng is an operating system for embedded devices that offers a reference implementation of TSCH. In this paper we describe how DCS builds and structures TSCH schedules over a real communication stack. In particular, beyond being collision-free, DCS can generate short schedules when compared to the number of nodes in the network. In DCS schedule sizes do not depend directly on the number of nodes. We present simulation results where DCS outperforms related approaches in terms of slotframe sizes, packet delivery ratio and end-to-end delays.

Weighted Sum Metrics – Based Load Balancing RPL Objective Function for IoT

The technological development of Internet of Things (IoT) applications is emerging and attracting the attention of the real world in the automated industry, agriculture, environment, and scientific community. In most scenarios, extending the network lifetime of an IoT network is highly challenging because of constrained nodes. The wireless sensor network (WSN) is the core component of IoT applications. In addition, the WSN nodes are required for the network processes, particularly routing, energy maintenance, load balance, congestion control, packet delivery, quick response, and more. The failure of any of the above network processes will affect the entire network operation. IPv6 Routing Protocol for Low-power and Lossy network (RPL) provides high routing solutions to IoT applications requirements. The load balance, congestion control, traffic load, and bottleneck problems are still open issues in the RPL. To resolve the load balance issue, we propose a weighted sum method objective function (WSM-OF), which provides the ability to select the alternative parent in routing by RPL metrics. WSM-OF adopts congestion control and load balancing to avoid heavy traffic and extend the network's node lifetime. The network parameters of control overhead, jitter, packet delivery ratio, parent switching, energy consumption, latency, and network lifetime are implemented and analyzed through the COOJA simulator. The result shows that the WSM-OF improves the network performance and significantly enhances the network lifetime by up to 7.8%.

TB-RPL: A Try-the-Best Fused Mode of Operation to Enhance Point-to-Point Communication Performance in RPL

RPL is the IPv6 routing protocol for low-power and lossy networks in the Internet of Things which supports point-to-point (P2P) communication. However, the partition of two modes of operations (MOPs) in downward routing complicates achieving high performance. In the non-storing mode, a downward route with the longest path length is often picked. In the storing mode, the downward routes to some child nodes cannot be stored by their parent because of the limitation of memory space, which makes some nodes unreachable. In addition, there are extra performance costs of mixing or switching the two modes in the existing hybrid-MOPs works. Therefore, this article proposes TB-RPL to achieve an enhancement of RPL with a better performance of P2P communication. It allows all nodes to behave in a single and uniformly fused MOP that solves the problems mentioned above. The proposed mode uses a modified routing header format and introduces a threshold to the number of route entries. We implemented and compared TB-RPL with related mechanisms in Cooja simulator based on the Contiki-NG operating system. Simulation results verify that TB-RPL eliminates the three identified problems. Consequently, it significantly improves the performance of P2P communication in LLN.

IoT-Enabled Precision Agriculture: Developing an Ecosystem for Optimized Crop Management

The Internet of Things (IoT) has the potential to revolutionize agriculture by providing real-time data on crop and livestock conditions. This study aims to evaluate the performance scalability of wireless sensor networks (WSNs) in agriculture, specifically in two scenarios: monitoring olive tree farms and stables for horse training. The study proposes a new classification approach of IoT in agriculture based on several factors and introduces performance assessment metrics for stationary and mobile scenarios in 6LowPAN networks. The study utilizes COOJA, a realistic WSN simulator, to model and simulate the performance of the 6LowPAN and Routing protocol for low-power and lossy networks (RPL) in the two farming scenarios. The simulation settings for both fixed and mobile nodes are shared, with the main difference being node mobility. The study characterizes different aspects of the performance requirements in the two farming scenarios by comparing the average power consumption, radio duty cycle, and sensor network graph connectivity degrees. A new approach is proposed to model and simulate moving animals within the COOJA simulator, adopting the random waypoint model (RWP) to represent horse movements. The results show the advantages of using the RPL protocol for routing in mobile and fixed sensor networks, which supports dynamic topologies and improves the overall network performance. The proposed framework is experimentally validated and tested through simulation, demonstrating the suitability of the proposed framework for both fixed and mobile scenarios, providing efficient communication performance and low latency. The results have several practical implications for precision agriculture by providing an efficient monitoring and management solution for agricultural and livestock farms. Overall, this study provides a comprehensive evaluation of the performance scalability of WSNs in the agriculture sector, offering a new classification approach and performance assessment metrics for stationary and mobile scenarios in 6LowPAN networks. The results demonstrate the suitability of the proposed framework for precision agriculture, providing efficient communication performance and low latency.

RPLAD3: anomaly detection of blackhole, grayhole, and selective forwarding attacks in wireless sensor network-based Internet of Things.

Routing protocols transmit vast amounts of sensor data between the Wireless Sensor Network (WSN) and the Internet of Things (IoT) gateway. One of these routing protocols is Routing Protocol for Low Power and Lossy Networks (RPL). The Internet Engineering Task Force (IETF) defined RPL in March 2012 as a de facto distance-vector routing protocol for wireless communications with lower energy. Although RPL messages use a cryptographic algorithm for security protection, it does not help prevent internal attacks. These attacks drop some or all packets, such as blackhole or selective forwarding attacks, or change data packets, like grayhole attacks. The RPL protocol needs to be strengthened to address such an issue, as only a limited number of studies have been conducted on detecting internal attacks. Moreover, earlier research should have considered the mobility framework, a vital feature of the IoT. This article presents a novel lightweight system for anomaly detection of grayhole, blackhole, and selective forwarding attacks. The study aims to use a trust model in the RPL protocol, considering attack detection under mobility frameworks. The proposed system, anomaly detection of three RPL attacks (RPLAD3), is designed in four layers and starts operating immediately after the initial state of the network. The experiments demonstrated that RPLAD3 outperforms the RPL protocol when defeating attacks with high accuracy and a true positive ratio while lowering power and energy consumption. In addition, it significantly improves the packet delivery ratio and decreases the false positive ratio to zero.

Multi-Modal Industrial IoT Networks: Recent Advances and Future Challenges

AbstractWhile the ongoing fourth industrial revolution continues to be a major driver behind wireless communication technologies, some environments are so prohibitive that even state-of-the-art solutions can barely achieve ubiquitous wireless connectivity (if at all). For example, in industrial sites with large metal constructions (such as petrochemical plants), highly localized and time-varying changes in wireless link quality are quite common. Oddly enough, much of the capabilities needed to deal with such effects are already present at the physical layer (PHY), but remain largely unexploited by higher protocol layers. In fact, little Industrial Internet of Things (IoT) (IIoT) research has considered harnessing the full multi-modal capabilities of modern multi-PHY/multi-band IoT hardware in general. As such, in this vision paper, we: (1) analyze recent advances towards enabling multi-modal IIoT through link- and routing layer operations; and (2) describe challenges and opportunities for future IIoT deployments, based on the design choices that emerged from said analysis. In summary, we identify a combination of a modified/extended Time-Slotted Channel Hopping (TSCH) link layer, using either fixed or variable duration timeslots, together with a Parent-Oriented (PO) Routing Protocol for Low-Power and Lossy Networks (LLNs) (RPL) approach to be the most promising way forward.

LDES: detector design for version number attack detection using linear temporal logic based on discrete event system

The Internet Engineering Task Force (IETF) has defined routing protocols for low power and lossy networks (RPL) for constrained devices. RPL constructs DODAGs (destination oriented directed acyclic graphs), to optimize routing. RPL ensures acyclic topology with the DODAG version number. However, the control message’s DODAG version number is not authenticated. So, RPL is vulnerable to network resource attack known as DODAG Version Number (DVN) attack. DVN attack creates a packet delay, packet loss, cyclic topology, etc., in the network. This paper proposes a method for detecting DODAG version number attacks. Several existing schemes to defend against the DVN, such as cryptographic techniques, trust-based, threshold-based and mitigation are computationally intensive or require protocol modification. DVN does not change the packet format or sequence of packets, but can still perform attacks and hence fall under the category of stealthy attacks, which are difficult to detect using traditional intrusion detection system’s (IDS). Discrete-event system (DES) based IDS have been applied in the literature for stealthy attacks that achieve low overhead, low false alarm rate, etc. However, the construction of DES-based IDS for network protocol may lead to errors, as modelling is manual. The resulting IDS, therefore, is unable to guarantee its correctness. This paper proposes linear temporal logic (LTL) based DES paradigm to detect DVN. LTL-based paradigm facilitates formal verification of the DES-based IDS, and hence the correctness of the scheme is ascertained. The proposed technique is simulated using the Contiki cooja simulator. When the percentage of spiteful nodes in the network increases, the true positive rate, and packet delivery rate drops, while the false positive rate and control message overhead increase. The memory requirement for sending the packets and verifying the nodes is minimal. The LTL-based IDS has been formally verified using NuSMV to ensure the correctness of the framework.

Routing Attacks Detection in 6LoWPAN-Based Internet of Things

The Internet of Things (IoT) has become increasingly popular, and opened new possibilities for applications in various domains. However, the IoT also poses security challenges due to the limited resources of the devices and its dynamic network topology. Routing attacks on 6LoWPAN-based IoT devices can be particularly challenging to detect because of its unique characteristics of the network. In recent years, several techniques have been proposed for detecting routing attacks, including anomaly detection. These techniques leverage different features of network traffic to identify and classify routing attacks. This paper focuses on routing attacks that target the Routing Protocol for Low-Power and Lossy Networks (RPL), which are widely used in 6LoWPAN-based IoT systems. The attacks discussed in this paper can be categorized as either inherited from Wireless Sensor Networks or exploiting vulnerabilities unique to RPL (known as RPL-specific attacks). The paper describes various RPL attacks, including Flood Attacks, Data-DoS/DDoS Attacks, Wormhole Attacks, RPL Rank Attacks, Blackhole Attacks, Version Attacks, and Sinkhole Attacks. In this paper, a novel Hybrid Intrusion Detection System (HIDS) that combines a decision tree classifier and a one-class Support Vector Machine classifier is proposed to detect routing attacks. The HIDS draws on the strengths of both a Signature Intrusion Detection System (SIDS) and an Anomaly-based Intrusion Detection System (AIDS) to identify routing attacks with a high degree of accuracy and a low false alarm rate. The routing dataset, which features genuine IoT network traffic and various kinds of routing attacks, was used to test the proposed HIDS. According to the findings, the hybrid IDS proposed in this study outperforms SIDS and AIDS approaches, with higher detection rates and lower false positive rates.

Hybrid Deep Learning-Based Intrusion Detection System for RPL IoT Networks

Internet of things (IoT) has become an emerging technology transforming everyday physical objects to be smarter by using underlying technologies such as sensor networks. The routing protocol for low-power and lossy networks (RPL) is considered one of the promising protocols designed for the IoT networks. However, due to the constrained nature of the IoT devices in terms of memory, processing power, and network capabilities, they are exposed to many security attacks. Unfortunately, the existing Intrusion Detection System (IDS) approaches using machine learning that have been proposed to detect and mitigate security attacks in internet networks are not suitable for analyzing IoT traffics. This paper proposed an IDS system using the hybridization of supervised and semi-supervised deep learning for network traffic classification for known and unknown abnormal behaviors in the IoT environment. In addition, we have developed a new IoT specialized dataset named IoTR-DS, using the RPL protocol. IoTR-DS is used as a use case to classify three known security attacks (DIS, Rank, and Wormhole). The proposed Hybrid DL-Based IDS is evaluated and compared to some existing ones, and the results are promising. The evaluation results show an accuracy detection rate of 98% and 92% in f1-score for multi-class attacks when using pre-trained attacks (known traffic) and an average accuracy of 95% and 87% in f1-score when predicting untrained attacks for two attack behaviors (unknown traffic).

Performance evaluation of AMQP over QUIC in the internet-of-thing networks

In today’s world, the use of IoT devices is growing every day. For connecting IoT devices from various vendors and supporting a variety of IoT use cases, an interoperable protocol like AMQP is necessary. Researchers are striving to minimize delay because many IoT applications are sensitive to it. The transport layer protocol that is used underneath, such as TCP or UDP, is one of the main causes of the delay. Although TCP is slower than UDP because to the three-way handshake and the usage of TLS for security, it is more reliable than UDP. The Internet Engineering Task Force has introduced a new transport layer protocol called QUIC that combines the best features of UDP and TCP to offer quick and reliable communication. In this study, we integrated QUIC and AMQP1.0 using the Go programming language. The Docker tool was used to containerize the AMQP1.0 Broker, Sender, and Receiver implementations. The performance of AMQP1.0 over TCP and AMQP1.0 over QUIC was benchmarked in the NS3 simulator over various wireless networks including WiFi, 4G/LTE, and satellite. QUIC showed considerable improvement over lossy networks. The results showed that switching from TCP to QUIC at the transport level lowered Communication Time by 8.57% over Satellite network. Although Round Trip Time was almost same yet Start up Latency showed improvement of 52%, 38% and 34% in case of WiFi, 4G/LTE and Satellite respectively. In addition, the performance of AMQP1.0 over TCP and AMQP1.0 over QUIC has been evaluated over different Packet Loss values, the results show that AMQP1.0 over QUIC outperforms AMQP1.0 over TCP in all the cases. The testing results revealed that TCP performance was degraded by 20%, 16%, and 36% over WiFi, 4G/LTE, and satellite, respectively at Packet loss of 15%, while QUIC performance was only degraded by 4%, 8%, and 9% in each of these cases.

Optimal Sensor Scheduling Under Intermittent Observations Subject to Network Dynamics

Motivated by various distributed control applications, we consider a linear system with Gaussian noise observed by multiple sensors which transmit measurements over a dynamic lossy network. We characterize the stationary optimal sensor scheduling policy for the finite horizon, discounted, and long-term average cost problems and show that the value iteration algorithm converges to a solution of the average cost problem. We further show that the suboptimal policies provided by the rolling horizon truncation of the value iteration also guarantee stability and provide near-optimal average cost. Lastly, we provide qualitative characterizations of the multidimensional set of measurement loss rates for which the system is stabilizable for a static network, thus extending earlier results on intermittent observations.