Intermittent Network Connectivity Research Articles

B-SAFE: Blockchain-Enabled Security Architecture for Connected Vehicle Fog Environment.

Vehicles are no longer stand-alone mechanical entities due to the advancements in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication-centric Internet of Connected Vehicles (IoV) frameworks. However, the advancement in connected vehicles leads to another serious security threat, online vehicle hijacking, where the steering control of vehicles can be hacked online. The feasibility of traditional security solutions in IoV environments is very limited, considering the intermittent network connectivity to cloud servers and vehicle-centric computing capability constraints. In this context, this paper presents a Blockchain-enabled Security Architecture for a connected vehicular Fog networking Environment (B-SAFE). Firstly, blockchain security and vehicular fog networking are introduced as preliminaries of the framework. Secondly, a three-layer architecture of B-SAFE is presented, focusing on vehicular communication, blockchain at fog nodes, and the cloud as trust and reward management for vehicles. Thirdly, details of the blockchain implementation at fog nodes is presented, along with a flowchart and algorithm. The performance of the evaluation of the proposed framework B-SAFE attests to the benefits in terms of trust, reward points, and threshold calculation.

A Secure Opportunistic Network with Efficient Routing for Enhanced Efficiency and Sustainability

The intersection of cybersecurity and opportunistic networks has ushered in a new era of innovation in the realm of wireless communications. In an increasingly interconnected world, where seamless data exchange is pivotal for both individual users and organizations, the need for efficient, reliable, and sustainable networking solutions has never been more pressing. Opportunistic networks, characterized by intermittent connectivity and dynamic network conditions, present unique challenges that necessitate innovative approaches for optimal performance and sustainability. This paper introduces a groundbreaking paradigm that integrates the principles of cybersecurity with opportunistic networks. At its core, this study presents a novel routing protocol meticulously designed to significantly outperform existing solutions concerning key metrics such as delivery probability, overhead ratio, and communication delay. Leveraging cybersecurity’s inherent strengths, our protocol not only fortifies the network’s security posture but also provides a foundation for enhancing efficiency and sustainability in opportunistic networks. The overarching goal of this paper is to address the inherent limitations of conventional opportunistic network protocols. By proposing an innovative routing protocol, we aim to optimize data delivery, minimize overhead, and reduce communication latency. These objectives are crucial for ensuring seamless and timely information exchange, especially in scenarios where traditional networking infrastructures fall short. By large-scale simulations, the new model proves its effectiveness in the different scenarios, especially in terms of message delivery probability, while ensuring reasonable overhead and latency.

Partition-Tolerant and Byzantine-Tolerant Decision Making for Distributed Robotic Systems With IOTA and ROS2

With the increasing ubiquity of autonomous robotic solutions, the interest in their connectivity and in the cooperation within multi-robot systems is rising. Two aspects that are a matter of current research are robot security and secure multirobot collaboration robust to byzantine agents. Blockchain and other distributed ledger technologies (DLTs) have been proposed to address the challenges in both domains. Nonetheless, some key challenges include scalability and deployment within realworld networks. This paper presents an approach to integrating IOTA and ROS 2 for more scalable DLT-based robotic systems while allowing for network partition tolerance after deployment. This is, to the best of our knowledge, the first implementation of IOTA smart contracts for robotic systems, and the first integrated design with ROS 2. This is in comparison to the vast majority of the literature which relies on Ethereum. We present a general IOTA+ROS 2 architecture leading to partitiontolerant decision-making processes that also inherit byzantine tolerance properties from the embedded blockchain structures. We demonstrate the effectiveness of the proposed framework for a cooperative mapping application in a system with intermittent network connectivity. We show both superior performance with respect to Ethereum in the presence of network partitions, and a low impact in terms of computational resource utilization. These results open the path for wider integration of blockchain solutions in distributed robotic systems with less stringent connectivity and computational requirements.

Mail Man Ferry: A Novel Routing Protocol in Intermittently Connected Networks

As an important area for mobile wireless networks, Intermittently Connected Networks (ICNs) have received increasing attention in practice and research in recent years. The main goals of the ICN routing protocol are to maximize the delivery probability and to minimize the delivery delay. These challenges have been investigated in previously proposed protocols with an assumption of fully cooperating nodes. Node cooperation directly impacts ICN performance in terms of delivery probability and delay. However, node cooperation is not guaranteed because a cooperating node consumes its buffer size and energy, thereby highlighting the challenges of memory, computation, and energy efficiencies. This paper addresses the challenge of ensuring node cooperation by proposing a novel routing protocol called Mail Man Ferry (MMF). The new protocol includes a node credit mechanism that ensures the cooperation of the network nodes. Extensive simulations were executed to evaluate the proposed protocol. Varying values of node cooperation in ICNs were employed in the simulation tests. The evaluation shows exciting results in which Mail Man Ferry outperforms previously proposed ICN protocols.

FAPMIC: Fake Packet and Selective Packet Drops Attacks Mitigation by Merkle Hash Tree in Intermittently Connected Networks

Delay/Disruption Tolerant Networks (DTNs) are a special category of IntermittentlyConnectedNetworks (ICNs). It has features such as long-delay, frequent-disruption, asymmetrical-data-rates, and high-bundle-error-rates. DTNs have been mainly developed for planet-to-planet networks, commonly known as Inter-Planetary-Networks (IPNs). However, DTNs have shown undimmed potency in challenged communication networks, such as DakNet, ZebraNet, KioskNet and WiderNet. Due to unique characteristics (Intermittent-connectivity and long-delay) DTNs face tough/several challenges in various research areas i.e bundle-forwarding, key-distribution, privacy, bundle-fragmentation, and malicious/selfish nodes particularly. Malicious/selfish nodes launch various catastrophic attacks, this includes, fake packet attacks, selective packet drops attacks, and denial-of-service/flood attacks. These attacks inevitably consume limited resources (persistent-buffer and bandwidth) in DTNs. Fake-packet and selective-packet-drops attacks are top among the challenging attacks in ICNs. The focus of this article is on critical analyses of fake-packet and selective-packet-drops attacks. The panoramic view on misbehavior nodes mitigation algorithms are analyzed, and evaluated mathematically through several parameters for detection probability/accuracy. This article presents a novel algorithm to detects/mitigates fake-packet and selective-packet-drops attacks. The proposed algorithm uses Merkle-Hash-Tree to detects the aforementioned attacks. The proposed algorithm added root hash along with all packets, when the malicious nodes drop packets or inject fake packets, the algorithm detects malicious nodes. Moreover, trace-driven simulation results show the proposed algorithm of this article accurately (enhanced detection-accuracy, enhanced packet delivery/packet loss ratios, and reduces false-positive/false-negative rates) detects malicious nodes which launch fake-packet and selective-packet-drops attacks, unlike previously proposed algorithms which detect only one attack (fake-packet or packet-drops at a time) or detect only malicious path (do not exactly detect malicious nodes which launch attacks). Furthermore, this article mathematically analyzed various scenarios to track exactly/position of various vehicular nodes.

DewDrone: Dew Computing for Internet of Drone Things

Unstable internet connectivity in aerial interconnection is challenging for the Internet of drone Things. Introducing the low power edge device and caching methodology opens a new challenge to developing an independent computing and communication application for smart cities, the rural sector, industry, and society 4.0. This author proposes a dew-cloud computing framework amalgamated with the UAV networks known as “DewDrone.” We engineered an opportunistic communication framework for unreliable and intermittent network connectivity. We analyzed the dew message transfer response, and caching performance has been measured in a resource constrain hardware testbed. The results show the 91.4% message delivery ratio within a dew buffer size of 150 MB with a minimum latency of 20.04 ms.

A context-aware improved POR protocol for Delay Tolerant networks

ABSTRACT The intermittent network connectivity and unawareness of global network knowledge are remarkable challenges when designing efficient Position-based Opportunistic Routing (POR) for Delay Tolerant Networks (DTNs). The best progress set selection of POR effectively handles the intermittent connectivity issue and improves the reliable performance of DTNs. Hence, the optimal progress set selection and catching capacity decide the routing reliability of DTN-POR. This paper proposes a context-aware DTN-POR protocol STAP to ensure reliable DTN routing with minimum overhead STAP design is divided into three folds: application diversity and network failures, context-aware best progress set selection, and enhanced caching management. The application diversity and network failure switch the nodes in harsh environments to DTN mode for transmitting the data packets successfully to the destination. Selecting context-aware relay nodes ensures highly successful data transmissions in the absence of end-to-end connectivity. The probability estimation maximizes the data reachability by considering unique node and application-level context attributes in the best progressive set. Finally, the enhanced catching management strategy limits the number of data copies with effective catch invalidation, resulting in minimum overhead. The proposed STAP accomplishes better results in different scenarios and improves the packet delivery ratio with a minimum duplication rate.

ECMS: Energy-Efficient Collaborative Multi-UAV Surveillance System for Inaccessible Regions

The evolution and popular adaptation of drone technology in diverse applications has necessitated advancement of UAV communication framework. UAVs inherently support features like mobility, flexibility, adaptive altitude, which make them a preferable option for dynamic surveillance of remote locations. Multiple UAVs can cooperatively work to accomplish surveillance missions more efficiently. However, the intermittent network connectivity and the limited onboard energy storage impose a great challenge on UAV-assisted remote surveillance. This paper presents an Energy-efficient Collaborative Multi-UAV Surveillance (ECMS) system for surveillance of inaccessible regions. The system employs an optimal Multi-UAV Collaborative Monocular Vision (MCMV) topology to facilitate the surveillance with zero blind spot using minimum number of drones. We also propose an application-aware Multi-Path Weighted Load-balancing (MWL) routing protocol for handling congestion by distributing traffic among all available resources in UAV network and adaptively selecting the of source datarate (i.e. switching video resolution). The simulation results demonstrate that the proposed surveillance system achieves coverage with lesser number of UAVs compared to the existing systems. It also achieves higher throughput, higher packet-delivery ratio, higher residual energy of UAVs, and lower end-to-end delay.

A New Hybrid Online and Offline Multi-Factor Cross-Domain Authentication Method for IoT Applications in the Automotive Industry

Connected vehicles have emerged as the latest revolution in the automotive industry, utilizing the advent of the Internet of Things (IoT). However, most IoT-connected cars mechanisms currently depend on available network services and need continuous network connections to allow users to connect to their vehicles. Nevertheless, the connectivity availability shortcoming in remote or rural areas with no network coverage makes vehicle sharing or any IoT-connected device problematic and undesirable. Furthermore, IoT-connected cars are vulnerable to various passive and active attacks (e.g., replay attacks, MiTM attacks, impersonation attacks, and offline guessing attacks). Adversaries could all use these attacks to disrupt networks posing a threat to the entire automotive industry. Therefore, to overcome this issue, we propose a hybrid online and offline multi-factor authentication cross-domain authentication method for a connected car-sharing environment based on the user’s smartphone. The proposed scheme lets users book a vehicle using the online booking phase based on the secured and trusted Kerberos workflow. Furthermore, an offline authentication phase uses the OTP algorithm to authenticate registered users even if the connectivity services are unavailable. The proposed scheme uses the AES-ECC algorithm to provide secure communication and efficient key management. The formal SOV logic verification was used to demonstrate the security of the proposed scheme. Furthermore, the AVISPA tool has been used to check that the proposed scheme is secured against passive and active attacks. Compared to the previous works, the scheme requires less computation due to the lightweight cryptographic algorithms utilized. Finally, the results showed that the proposed system provides seamless, secure, and efficient authentication operation for the automotive industry, specifically car-sharing systems, making the proposed system suitable for applications in limited and intermittent network connections.

UAVs Trajectory Optimization for Data Pick Up and Delivery with Time Window

Unmanned Aerial Vehicles (UAVs), also known as drones, are a class of aircraft without the presence of pilots on board. UAVs have the ability to reduce the time and cost of deliveries and to respond to emergency situations. Currently, UAVs are extensively used for data delivery and/or collection to/from dangerous or inaccessible sites. However, trajectory planning is one of the major UAV issues that needs to be solved. To address this question, we focus in this paper on determining the optimized routes to be followed by the drones for data pickup and delivery with a time window with an intermittent connectivity network, while also having the possibility to recharge the drones’ batteries on the way to their destinations. To do so, we formulated the problem as a multi-objective optimization problem, and we showed how to use the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to solve this problem. Several experiments were conducted to validate the proposed algorithm by considering different scenarios.

DTN-Balance: A Forwarding-Capacity and Forwarding-Queue Aware Routing for Self-organizing DTNs

In delay-tolerant networks (DTNs), intermittent network connectivity and lack of global system information pose serious challenges to achieve effective data forwarding. Most state-of-the-art DTN routing algorithms are based on hill-climbing heuristics in order to select the best available next hop to achieve satisfactory network throughput and routing efficiency. An adverse consequence of this approach is that a small subset of good users take on most of the forwarding tasks. This can quickly deplete scarce resources (e.g. storage, battery, etc.) in heavily utilized devices which degrades the network reliability. A system with a significant amount of traffic carried by a small number of users is not robust to denial of service attacks and random failures. To overcome these deficiencies, this paper proposes a new routing algorithm, DTN-Balance, that takes the forwarding capacity and forwarding queue of the relay nodes into account to achieve a better load distribution in the network. For this, we defined a new routing metric called message forwarding utility combining nodal available bandwidth and forwarding workload. Applying small world theory, we impose an upper bound on the end-to-end hop count that results in a sharp increase in routing efficiency. Queued messages in a forwarding node are arranged by DTN-Balance based on message dropping utility metric for a more intelligent decision in the case of a message drop. The performance of our method is compared with that of the existing algorithms by simulations on real DTN traces. The results show that our algorithm provides outstanding forward efficiency at the expense of a small drop in the throughput.

Cooperative Caching in Vehicular Content Centric Network Based on Social Attributes and Mobility

Communications in vehicular ad-hoc network (VANET) are subject to performance degradation as results of channel fading and intermittent network connectivity. The emerging Vehicular Content Centric Network (VCCN) is promising in supporting the needs of contents and alleviating the communication problems in VANET. Specifically, to improve the cache hit ratio and reduce the access delay of content retrieval, it helps to choose the appropriate vehicles to cache the frequently accessed data items. In this paper, we propose a Cooperative Caching scheme based on Social Attributes and Mobility Prediction (CCSAMP) for VCCN. CCSAMP is based on the observation that vehicles move around and are liable to contact each other according to drivers' common interests or social similarities. A caching node sharing more social attributes with the content requester is more likely to be interested in the same contents and distribute the contents to others with similar interests. Furthermore, a caching node that frequently meets other nodes is a better candidate to keep cache copies. To increase the network performance, CCSAMP also exploits the regularity of vehicle moving behaviors to predict the chance for a vehicle to reach hot zones based on Hidden Markov Model (HMM). We evaluate CCSAMP through the ONE simulator to demonstrate its higher cache hit ratio and lower content access delay compared to other state-of-the-art schemes.

Churn in the Bitcoin Network

Efficient and reliable propagation of blocks is vital to the scalability of the Bitcoin network. As a result, several schemes, such as the compact block protocol (BIP 152), have been proposed over the last few years to speed up the block propagation. Even so, we provide experimental evidence that (i) the vast majority (97%) of Bitcoin nodes exhibit only intermittent network connectivity ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , churn), and (ii) this churn results in significant number of unsuccessful compact blocks, roughly three times the statistic for continuously connected nodes. We conduct experiments on the Bitcoin network that show that churn results in a roughly five fold increase in block propagation time ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , 566.89 ms vs. 109.31 ms) on average. To effect our analysis, we develop a statistical model for churn, based on empirical network data, and use this model to actuate live test nodes on the Bitcoin network. The performance of the system is measured within a novel framework that we developed for logging the internal behavior of a Bitcoin node, and which we share for public use. Finally, to mitigate the problem of missing transactions in churning nodes, we propose and implement into Bitcoin Core a new synchronization protocol, dubbed MempoolSync. Our measurements show that churning nodes implementing MempoolSync experience significantly better performance than standard nodes not implementing MempoolSync, including average block propagation delay reduced by over 50%.

Rings for Privacy: An Architecture for Large Scale Privacy-Preserving Data Mining

This article proposes a new architecture for privacy-preserving data mining based on Multi Party Computation (MPC) and secure sums. While traditional MPC approaches rely on a small number of aggregation peers replacing a centralized trusted entity, the current study puts forth a distributed solution that involves all data sources in the aggregation process, with the help of a single server for storing intermediate results. A large-scale scenario is examined and the possibility that data become inaccessible during the aggregation process is considered, a possibility that traditional schemes often neglect. Here, it is explicitly examined, as it might be provoked by intermittent network connectivity or sudden user departures. For increasing system reliability, data sources are organized in multiple sets, called rings, which independently work on the aggregation process. Two different protocol schemes are proposed and their failure probability, i.e., the probability that the data mining output cannot guarantee the desired level of accuracy, is analytically modeled. The privacy degree, the communication cost and the computational complexity that the schemes exhibit are also characterized. Finally, the new protocols are applied to some specific use cases, demonstrating their feasibility and attractiveness.

Delay-Minimized Edge Caching in Heterogeneous Vehicular Networks: A Matching-Based Approach

To enable ever-increasing vehicular applications, heterogeneous vehicular networks (HetVNets) are recently emerged to provide enhanced and cost-effective wireless network access. Meanwhile, edge caching is imperative to future vehicular content delivery to reduce the delivery delay and alleviate the unprecedented backhaul pressure. This work investigates content caching in HetVNets where Wi-Fi roadside units (RSUs), TV white space (TVWS) stations, and cellular base stations are considered to cache contents and provide content delivery. Particularly, to characterize the intermittent network connection provided by Wi-Fi RSUs and TVWS stations, we establish an on-off model with service interruptions to describe the content delivery process. Content coding then is leveraged to resist the impact of unstable network connections with optimized coding parameters. By jointly considering file characteristics and network conditions, we minimize the average delivery delay by optimizing the content placement, which is formulated as an integer linear programming (ILP) problem. Adopting the idea of student admission model, the ILP problem is then transformed into a many-to-one matching problem and solved by our proposed stable-matching-based caching scheme. Simulation results demonstrate that the proposed scheme can achieve near-optimal performances in terms of delivery delay and offloading ratio with low complexity.

Security Properties of Light Clients on the Ethereum Blockchain

Ethereum is a decentralized blockchain, known as being the second most popular public blockchain after Bitcoin. Since Ethereum is decentralised the canonical state is determined by the Ethereum network participants via a consensus mechanism without a centralized coordinator. The network participants are required to evaluate every transaction starting from the genesis block, which requires a large amount of network, computing, and storage resources. This is impractical for many devices with either limited computing resources or intermittent network connectivity. To overcome this drawback Ethereum defines a light client protocol where the light client fetches the blockchain state from a node operating as a light protocol server. Light clients are unable to maintain blockchain state internally, and as a consequence can only perform partial validation on blocks. Thus they rely on the light server for full block validation and to provide the updated blockchain state. Light clients connect to multiple light servers to mitigate the risk of relying on a single potentially dishonest server. Ethereum light clients are known to suffer from a probabilistic security model, but they are widely assumed to be secure under normal operating conditions. In fact, the implicit security assumptions of light clients have not been formally characterised in the literature. We present and analyse the probabilistic security guarantees under three different adversarial scenarios. The results show that for any adversary that is able to manipulate the network, the security assurances provided by the light protocol are severely impacted, and in some cases entirely lost. These results clearly demonstrate that the assumption of normal operating conditions is insufficient to justify the security assumptions of light clients. Our work also provides insight to the security of light clients under different security parameters, allowing light client implementers to more accurately understand the potential security trade-offs.

A Trust Model for Security Against Black Hole Attack in Hierarchical Cluster Based Wireless Sensor Network

Wireless Sensor Network (WSN) is widely gaining fame since it has theoretically unavoidable unlimited applications. Security stays a significant challenge for WSN because for a few feeble substances like open remote medium, dynamic topology, absence of centralized infrastructure and intermittent network connectivity. Dark gap assault is a sort of Denial of Service (DoS) attack, which influences reliability of a system by diverting and dropping genuine packets in the system. Black hole attack ends up being progressively extraordinary when number of threatening nodes participate to show Black hole attack in the framework, which is named as a helpful black hole attack. In this paper, we showed an Enhanced Detection and Prevention Mechanism for Black hole Attack (EDPMBA) Trust Model to save the assurance from single and helpful black hole attack. EDPMBA additionally shows better execution as far delay and packet conveyance proportion.

Delay-Constrained Routing via Heterogeneous Vehicular Communications in Software Defined BusNet

As a critical part of public transportation systems, buses driving routinely in urban areas naturally form a bus ad-hoc network (BusNet). Different from conventional vehicular ad-hoc networks, the sparse distribution of buses magnifies the problem of intermittent network connectivity, making it more challenging for real-time routing. In this paper, we first present a novel architecture called software-defined BusNet, where the distributed controllers (i.e., base stations) collect traffic information and real-time requests from buses via vehicle-to-cellular communication. The collected information enables the logically centralized controller to make routing decisions with global traffic information. Then, the routing decisions are returned to roadside units (RSUs) and buses, which will instruct the data broadcast from RSUs to buses via vehicle-to-roadside (V2R) communication, and data forwarding among the buses through vehicle-to-vehicle (V2V) communication. On this basis, we formulate the problem of delay-constrained routing for BusNet (DCRB) which aims to maximize both the delivery ratio and the bandwidth efficiency. We build a probabilistic model to analyze the encounter probability and encounter delay between the relay buses based on the predicable bus traces. Further, we derive the expected reachability and expected delivery delay of the multi-hop routing path. The routing graph is constructed for searching the feasible routing paths via the modified Dijkstra algorithm. Four routing selection strategies are proposed based on different metrics: HRF (highest reachability first), SDF (shortest delivery delay first), MHF (minimum number of hops first), and RDH (combination of reachability, delay, and hop). Finally, we build the simulation model and implement the proposed routing algorithms for performance evaluation. The comprehensive simulation results demonstrate that RDH achieves the best overall performance on improving system delivery ratio and enhancing bandwidth efficiency.

FRID: Flood Attack Mitigation Using Resources Efficient Intrusion Detection Techniques in Delay Tolerant Networks

Delay tolerant networks (DTNs) are a special type of intermittently connected networks (ICN) featured by variable delay, frequent disruption, asymmetric data rates, and high-error rates. The DTNs have been primarily developed for interplanetary networks (IPNs), however, it shows applicability to challenged networks. Thus, solutions devised for security and routing for traditional networks do not apply to DTNs due to its unique nature. Moreover, this paper shows less attention particularly in security and its related strings. In DTNs, malicious nodes launch various attacks that include packet drop, a fake packet, and flood attack. These attacks inevitably overuse scarce resources (bandwidth, buffer, and energy) in DTNs, which leads to low packet delivery ratio and high packet loss ratio. Flood attack is listed in top among the challenging attacks in DTNs. The existing techniques to confront flood attack suffered from high-detection time and low-detection accuracy. This paper proposed novel resources efficient (distributed and intrusion detection system-based) algorithms to mitigate flood attack. The simulation results show considerable improvement in detection time, detection accuracy, and resource consumption, and also show enhanced packet delivery ratio and reduced packet loss ratio.

Location-assistant content distribution scheme for emergency rescue

In order to optimize the timeliness and pertinence of message delivery in emergency rescue scenarios and improve the service performance of emergency communications network, we propose a location-assistant content distribution scheme based on delay tolerant network. First of all, considering that the movement patterns of rescue teams tend to follow a predetermined course of action, we design a location-based group mobility model. Due to the intermittent network connectivity and variety of emergency service, a content-classification-based publish/subscribe architecture and a GenericSpray routing algorithm based on the prediction of overlap opportunity in spatio-temporal positions are proposed. Furthermore, we also give a cache management strategy based on the content significance. Since location-assistant content distribution scheme can predict the overlap of activity between rescue teams through the course of action, not only can the number of copy forwarding and message delivery delays be significantly reduced but also the priority delivery of important messages can be ensured by message classification. Simulation experiments show that compared with the traditional delay tolerant network routing algorithm and the classic first-in-first-out caching strategy, location-assistant content distribution scheme improves the performance of message delivery rate, transmission delay, and control overhead significantly.