MARINE: Man-in-the-middle attack resistant trust model IN connEcted vehicles

Vehicular Ad-hoc NETwork (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as Man-in-the-Middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper, we propose a novel trust model, namely, Man-in-the-middle Attack Resistance trust model IN connEcted vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the bench-marked trust model. Simulation results show that for a network containing 35% MiTM attackers, MARINE outperforms the state of the art trust model by 15%, 18%, and 17% improvements in precision, recall and F-score, respectively.N/A

From Sensor to Observation Web with Environmental Enablers in the Future Internet

This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities’ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term ?envirofied? Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management)

Resilient networking in wireless sensor networks

This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR)

Views from the coalface: chemo-sensors, sensor networks and the semantic sensor web

Currently millions of sensors are being deployed in sensor networks across the world. These networks generate vast quantities of heterogeneous data across various levels of spatial and temporal granularity. Sensors range from single-point in situ sensors to remote satellite sensors which can cover the globe. The semantic sensor web in principle should allow for the unification of the web with the real-word. In this position paper, we discuss the major challenges to this unification from the perspective of sensor developers (especially chemo-sensors) and integrating sensors data in real-world deployments. These challenges include: (1) identifying the quality of the data; (2) heterogeneity of data sources and data transport methods; (3) integrating data streams from different sources and modalities (esp. contextual information), and (4) pushing intelligence to the sensor level

A Smart Modular Wireless System for Condition Monitoring Data Acquisition

Smart sensors, big data, the cloud and distributed data processing are some of the most interning changes in the way we collect, manage and treat data in recent years. These changes have not significantly influenced the common practices in condition monitoring for shipping. In part this is due to the reduced trust in data security, data ownership issues, lack of technological integration and obscurity of direct benefit. This paper presents a method of incorporating smart sensor techniques and distributed processing in data acquisition for condition monitoring to assist decision support for maintenance actions addressing these inhibitors

An objective based classification of aggregation techniques for wireless sensor networks

Wireless Sensor Networks have gained immense popularity in recent years due to their ever increasing capabilities and wide range of critical applications. A huge body of research efforts has been dedicated to find ways to utilize limited resources of these sensor nodes in an efficient manner. One of the common ways to minimize energy consumption has been aggregation of input data. We note that every aggregation technique has an improvement objective to achieve with respect to the output it produces. Each technique is designed to achieve some target e.g. reduce data size, minimize transmission energy, enhance accuracy etc. This paper presents a comprehensive survey of aggregation techniques that can be used in distributed manner to improve lifetime and energy conservation of wireless sensor networks. Main contribution of this work is proposal of a novel classification of such techniques based on the type of improvement they offer when applied to WSNs. Due to the existence of a myriad of definitions of aggregation, we first review the meaning of term aggregation that can be applied to WSN. The concept is then associated with the proposed classes. Each class of techniques is divided into a number of subclasses and a brief literature review of related work in WSN for each of these is also presented

Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks

Emerging six generation (6G) is the integration of heterogeneous wireless networks, which can seamlessly support anywhere and anytime networking. But high Quality-of-Trust should be offered by 6G to meet mobile user expectations. Artificial intelligence (AI) is considered as one of the most important components in 6G. Then AI-based trust management is a promising paradigm to provide trusted and reliable services. In this article, a generative adversarial learning-enabled trust management method is presented for 6G wireless networks. Some typical AI-based trust management schemes are first reviewed, and then a potential heterogeneous and intelligent 6G architecture is introduced. Next, the integration of AI and trust management is developed to optimize the intelligence and security. Finally, the presented AI-based trust management method is applied to secure clustering to achieve reliable and real-time communications. Simulation results have demonstrated its excellent performance in guaranteeing network security and service quality

Trust model genetic node recovery based on cloud theory for underwater acoustic sensor network

Underwater Acoustic Sensor Networks [UASNs] are becoming a very growing research topic in the field of WSNs. UASNs are harmful by many attacks such as Jamming attacks at the physical layer, Collision attacks at the data link layer and Dos attacks at the network layer. UASNs has a unique characteristic such as unreliable communication, mobility, and computation of underwater sensor network. Because of this the traditional security mechanism, e.g. cryptographic, encryption, authorization and authentications are not suitable for UASNs. Many trust mechanisms of TWSNs [Terrestrial Wireless Sensor Networks] had proposed to UASNs and failed to provide security for UASNs environment, due to dynamic network structure and weak link connection between sensors. In this paper, a novel Trust Model Genetic Algorithm based on Cloud Theory [TMC] for UASNs has been proposed. The TMC-GA suggested a genetic node recovery algorithm to improve the TMC network in terms of better network lifetime, residual energy and total energy consumption. Also ensures that sensor nodes are participating in the rerouting in the routing discovery and performs well in terms of successful packet delivery. Simulation result provides that the proposed TMC-Genetic node recovery algorithm outperforms compared to other related works in terms of the number of hops, end-to-end delay, total energy consumption, residual energy, routing overhead, throughput and network lifetime

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems