Provenance-enabled Packet Path Tracing in the RPL-based Internet of Things

The interconnection of resource-constrained and globally accessible things with untrusted and unreliable Internet make them vulnerable to attacks including data forging, false data injection, and packet drop that affects applications with critical decision-making processes. For data trustworthiness, reliance on provenance is considered to be an effective mechanism that tracks both data acquisition and data transmission. However, provenance management for sensor networks introduces several challenges, such as low energy, bandwidth consumption, and efficient storage. This paper attempts to identify packet drop (either maliciously or due to network disruptions) and detect faulty or misbehaving nodes in the Routing Protocol for Low-Power and Lossy Networks (RPL) by following a bi-fold provenance-enabled packed path tracing (PPPT) approach. Firstly, a system-level ordered-provenance information encapsulates the data generating nodes and the forwarding nodes in the data packet. Secondly, to closely monitor the dropped packets, a node-level provenance in the form of the packet sequence number is enclosed as a routing entry in the routing table of each participating node. Lossless in nature, both approaches conserve the provenance size satisfying processing and storage requirements of IoT devices. Finally, we evaluate the efficacy of the proposed scheme with respect to provenance size, provenance generation time, and energy consumption.Comment: 14 pages, 18 Figure

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

An enhanced AES-GCM based security protocol for securing the IoT communication

In the recent years, the devices in Internet of Things (IoT) are growing exponentially due to the emergence of many sophisticated applications. This tremendous growth leads to serious security challenges and the devices of Wireless Sensor Networks should be protected from various attacks. IoT can be configured dynamically without fixed infrastructure and the devices are communicated with one another in an Ad-hoc manner. The work presents the classification of various DDoS attacks in the IoT environment and provides a solution for replay attack. All variations of DDoS attacks are modeled using UML based activity modeling. This clearly understands the behavior of each version of attacks and their performance in the environment. The modeling also helps to construct a solution to prevent this attack from its execution. The work also proposed a trust based protocol for replay attacks which allows the attack inside the network and blocks it after identifying the attack based on its specific behavior. The network performance is improved after implementing this proposed protocol inside the network with help of simulation under realistic conditions. The performance metrics considered in the work are energy, packet loss, computational time and throughput. The paper compares the performance with the state-of-the-art schemes such as Efficient Distributed Deterministic Key and Hashbased Message Authentication Code. The experimental analysis proved that the proposed scheme outperforms the other state-of-the-works in terms of computational cost, throughput, and delay

Design of a Network with wireless sensor applied to data transmission based on IEEE 802.15.4 standard

The problem of data transmission in wireless sensor networks (WSN), with real time guarantees, is an issue that has important references in the international scientific community, but that still does not have a solution that can completely satisfy this requirement [1]. Therefore, real time data transmission with WSN is considered an open issue with many possibilities of improvement. In this sense, this document presents a new procedure to ensure this type of transmission with WSN, particularly from the planning of the resources available for data transmission in the network, taking as a reference the IEEE 802.15.4 standard

Markov decision processes with applications in wireless sensor networks: A survey

Ministry of Education, Singapore under its Academic Research Funding Tier

A wireless sensor network system for border security and crossing detection

The protection of long stretches of countries’ borders has posed a number of challenges. Effective and continuous monitoring of a border requires the implementation of multi-surveillance technologies, such as Wireless Sensor Networks (WSN), that work as an integrated unit to meet the desired goals. The research presented in this thesis investigates the application of topologically Linear WSN (LWSNs) to international border monitoring and surveillance. The main research questions studied here are: What is the best form of node deployment and hierarchy? What is the minimum number of sensor nodes to achieve k− barrier coverage in a given belt region? iven an appropriate network density, how do we determine if a region is indeed k−barrier covered? What are the factors that affect barrier coverage? How to organise nodes into logical segments to perform in-network processing of data? How to transfer information from the networks to the end users while maintaining critical QoS measures such as timeliness and accuracy. To address these questions, we propose an architecture that specifies a mechanism to assign nodes to various network levels depending on their location. These levels are used by a cross-layer communication protocol to achieve data delivery at the lowest possible cost and minimal delivery delay. Building on this levelled architecture, we study the formation of weak and strong barriers and how they determine border crossing detection probability. We propose new method to calculate the required node density to provide higher intruder detection rate. Then, we study the effect of people movement models on the border crossing detection probability. At the data link layer, new energy balancing along with shifted MAC protocol are introduced to further increase the network lifetime and delivery speed. In addition, at network layer, a routing protocol called Level Division raph (LD ) is developed. LD utilises a complex link cost measurement to insure best QoS data delivery to the sink node at the lowest possible cost. The proposed system has the ability to work independently or cooperatively with other monitoring technologies, such as drowns and mobile monitoring stations. The performance of the proposed work is extensively evaluated analytically and in simulation using real-life conditions and parameters. The simulation results show significant performance gains when comparing LD to its best rivals in the literature Dynamic Source Routing. Compared to DSR, LD achieves higher performance in terms of average end-to-end delays by up to 95%, packet delivery ratio by up to 20%, and throughput by up to 60%, while maintaining similar performance in terms of normalised routing load and energy consumption

Wireless sensor networks

Wireless sensor networks promise an unprecedented fine-grained interface between the virtual and the physical world. They are one of the most rapidly developing new information technologies, with applications in a wide range of fields including industrial process control, security and surveillance, environmental sensing, and structural health monitoring. The subject of this project is motivated by the urgent need to provide a comprehensive and organized survey of the field. It shows how the core challenges of energy efficiency, robustness, and autonomy are addressed in these systems by networking techniques across multiple layers. The topics covered include network deployment, wireless characteristics, time synchronization, congestion and error control, medium access, standards, topology control, routing, security, data transfer, transport protocols and new technologies and materials in fabricating sensors

Trust-based energy efficient routing protocol for wireless sensor networks

Wireless Sensor Networks (WSNs) consist of a number of distributed sensor nodes that are connected within a specified area. Generally, WSN is used for monitoring purposes and can be applied in many fields including health, environmental and habitat monitoring, weather forecasting, home automation, and in the military. Similar, to traditional wired networks, WSNs require security measures to ensure a trustworthy environment for communication. However, due to deployment scenarios nodes are exposed to physical capture and inclusion of malicious node led to internal network attacks hence providing the reliable delivery of data and trustworthy communication environment is a real challenge. Also, malicious nodes intentionally dropping data packets, spreading false reporting, and degrading the network performance. Trust based security solutions are regarded as a significant measure to improve the sensor network security, integrity, and identification of malicious nodes. Another extremely important issue for WSNs is energy conversation and efficiency, as energy sources and battery capacity are often limited, meaning that the implementation of efficient, reliable data delivery is an equally important consideration that is made more challenging due to the unpredictable behaviour of sensor nodes. Thus, this research aims to develop a trust and energy efficient routing protocol that ensures a trustworthy environment for communication and reliable delivery of data. Firstly, a Belief based Trust Evaluation Scheme (BTES) is proposed that identifies malicious nodes and maintains a trustworthy environment among sensor nodes while reducing the impact of false reporting. Secondly, a State based Energy Calculation Scheme (SECS) is proposed which periodically evaluates node energy levels, leading to increased network lifetime. Finally, as an integrated outcome of these two schemes, a Trust and Energy Efficient Path Selection (TEEPS) protocol has been proposed. The proposed protocol is benchmarked with A Trust-based Neighbour selection system using activation function (AF-TNS), and with A Novel Trust of dynamic optimization (Trust-Doe). The experimental results show that the proposed protocol performs better as compared to existing schemes in terms of throughput (by 40.14%), packet delivery ratio (by 28.91%), and end-to-end delay (by 41.86%). In conclusion, the proposed routing protocol able to identify malicious nodes provides a trustworthy environment and improves network energy efficiency and lifetime