Biblio

In this paper, we address the virtual network embedding (VNE) problem in non-terrestrial networks (NTNs) enabling dynamic changes in the virtual network function (VNF) deployment to maximize the service acceptance rate and service revenue. NTNs such as satellite networks involve highly dynamic topology and limited resources in terms of rate and power. VNE in NTNs is a challenge because a static strategy under-performs when new service requests arrive or the network topology changes unexpectedly due to failures or other events. Existing solutions do not consider the power constraint of satellites and rate limitation of inter-satellite links (ISLs) which are essential parameters for dynamic adjustment of existing VNE strategy in NTNs. In this work, we propose a dynamic VNE algorithm that selects a suitable VNE strategy for new and existing services considering the time-varying network topology. The proposed scheme, D-ViNE, increases the service acceptance ratio by 8.51% compared to the benchmark scheme TS-MAPSCH.

IoT connects a large number of physical objects with the Internet that capture and exchange real-time information for service provisioning. Traditional network management schemes face challenges to manage vast amounts of network traffic generated by IoT services. Software-defined networking (SDN) and information-centric networking (ICN) are two complementary technologies that could be integrated to solve the challenges of different aspects of IoT service provisioning. ICN offers a clean-slate design to accommodate continuously increasing network traffic by considering content as a network primitive. It provides a novel solution for information propagation and delivery for large-scale IoT services. On the other hand, SDN allocates overall network management responsibilities to a central controller, where network elements act merely as traffic forwarding components. An SDN-enabled network supports ICN without deploying ICN-capable hardware. Therefore, the integration of SDN and ICN provides benefits for large-scale IoT services. This article provides a comprehensive survey on software-defined information-centric Internet of Things (SDIC-IoT) for IoT service provisioning. We present critical enabling technologies of SDIC-IoT, discuss its architecture, and describe its benefits for IoT service provisioning. We elaborate on key IoT service provisioning requirements and discuss how SDIC-IoT supports different aspects of IoT services. We define different taxonomies of SDIC-IoT literature based on various performance parameters. Furthermore, we extensively discuss different use cases, synergies, and advances to realize the SDIC-IoT concept. Finally, we present current challenges and future research directions of IoT service provisioning using SDIC-IoT.

Software-Defined Networking (SDN) technique is presented in this paper to manage the Naval Supervisory Control and Data Acquisition (SCADA) network for equipping the network with the function of reconfiguration and scalability. The programmable nature of SDN enables a programmable Modular Topology Generator (MTG), which provides an extensive control over the network’s internal connectivity and traffic control. Specifically, two functions of MTG are developed and examined in this paper, namely linkHosts and linkSwitches. These functions are able to place the network into three different states, i.e., fully connected, fully disconnected, and partially connected. Therefore, it provides extensive security benefits and allows network administrators to dynamically reconfigure the network and adjust settings according to the network’s needs. Extensive tests on Mininet have demonstrated the effectiveness of SDN for enabling the reconfigurable and scalable Naval SCADA network. Therefore, it provides a potent tool to enhance the resiliency/survivability, scalability/compatibility, and security of naval SCADA networks.

Software-Defined Networking (SDN) has found applications in different domains, including wired- and wireless networks. The SDN controller has a global view of the network topology, which is vulnerable to topology poisoning attacks, e.g., link fabrication and host-location hijacking. The adversaries can leverage these attacks to monitor the flows or drop them. However, current defence systems such as TopoGuard and TopoGuard+ can detect such attacks. In this paper, we introduce the Link Latency Attack (LLA) that can successfully bypass the systems' defence mechanisms above. In LLA, the adversary can add a fake link into the network and corrupt the controller's view from the network topology. This can be accomplished by compromising the end hosts without the need to attack the SDN-enabled switches. We develop a Machine Learning-based Link Guard (MLLG) system to provide the required defence for LLA. We test the performance of our system using an emulated network on Mininet, and the obtained results show an accuracy of 98.22% in detecting the attack. Interestingly, MLLG improves 16% the accuracy of TopoGuard+.

The Internet, the de facto platform for large-scale content distribution, suffers from two issues that limit its manageability, efficiency, and evolution. First, the IP-based Internet is host-centric and agnostic to the content being delivered and, second, the tight coupling of the control and data planes restrict its manageability, and subsequently the possibility to create dynamic alternative paths for efficient content delivery. Here, we present the CURLING system that leverages the emerging Information-Centric Networking paradigm for enabling cost-efficient Internet-scale content delivery by exploiting multicasting and in-network caching. Following the software-defined networking concept that decouples the control and data planes, CURLING adopts an interdomain hop-by-hop content resolution mechanism that allows network operators to dynamically enforce/change their network policies in locating content sources and optimizing content delivery paths. Content publishers and consumers may also control content access according to their preferences. Based on both analytical modeling and simulations using real domain-level Internet subtopologies, we demonstrate how CURLING supports efficient Internet-scale content delivery without the necessity for radical changes to the current Internet.

The growing trend toward information technology increases the amount of data travelling over the network links. The problem of detecting anomalies in data streams has increased with the growth of internet connectivity. Software-Defined Networking (SDN) is a new concept of computer networking that can adapt and support these growing trends. However, the centralized nature of the SDN design is challenged by the need for an efficient method for traffic monitoring against traffic anomalies caused by misconfigured devices or ongoing attacks. In this paper, we propose a new model for traffic behavior monitoring that aims to ensure trusted communication links between the network devices. The main objective of this model is to confirm that the behavior of the traffic streams matches the instructions provided by the SDN controller, which can help to increase the trust between the SDN controller and its covered infrastructure components. According to our preliminary implementation, the behavior monitoring unit is able to read all traffic information and perform a validation process that reports any mismatching traffic to the controller.

Software-defined networking (SDN) is a recently developed approach to computer networking that brings a centralized orientation to network control, thereby improving network architecture and management. However, as with any communication environment that involves message transmission among users, SDN is confronted by the ongoing challenge of protecting user privacy. In this “Work in Progress (WIP)” research, we propose an SDN security model that applies the moving target defense (MTD) technique to protect communication links from sensitive data leakages. MTD is a security solution aimed at increasing complexity and uncertainty for attackers by concealing sensitive information that may serve as a gateway from which to launch different types of attacks. The proposed MTD-based security model is intended to protect user identities contained in transmitted messages in a way that prevents network intruders from identifying the real identities of senders and receivers. According to the results from preliminary experiments, the proposed MTD model has potential to protect the identities contained in transmitted messages within communication links. This work will be extended to protect sensitive data if an attacker gets access to the network device.

Many of the emerging wide-area monitoring protection and control (WAMPAC) applications in modern electrical grids rely heavily on the availability and integrity of widespread phasor measurement unit (PMU) data. Therefore, it is critical to protect PMU networks against growing cyber-attacks and system faults. In this paper, we present a self-healing PMU network design that considers both power system observability and communication network characteristics. Our design utilizes centralized network control, such as the emerging software-defined networking (SDN) technology, to design resilient network self-healing algorithms against cyber-attacks. Upon detection of a cyber-attack, the PMU network can reconfigure itself to isolate compromised devices and re-route measurement
data with the goal of preserving the power system observability. We have developed a proof-of-concept system in a container-based network testbed using integer linear programming to solve a graphbased PMU system model.We also evaluate the system performance regarding the self-healing plan generation and installation using the IEEE 30-bus system.
 

The unauthorized access or theft of sensitive, personal information is becoming a weekly news item. The illegal dissemination of proprietary information to media outlets or competitors costs industry untold millions in remediation costs and losses every year. The 2013 data breach at Target, Inc. that impacted 70 million customers is estimated to cost upwards of 1 billion dollars. Stolen information is also being used to damage political figures and adversely influence foreign and domestic policy. In this paper, we offer some techniques for better understanding the health and security of our networks. This understanding will help professionals to identify network behavior, anomalies and other latent, systematic issues in their networks. Software-Defined Networks (SDN) enable the collection of network operation and configuration metrics that are not readily available, if available at all, in traditional networks. SDN also enables the development of software protocols and tools that increases visibility into the network. By accumulating and analyzing a time series data repository (TSDR) of SDN and traditional metrics along with data gathered from our tools we can establish behavior and security patterns for SDN and SDN hybrid networks. Our research helps provide a framework for a range of techniques for administrators and automated system protection services that give insight into the health and security of the network. To narrow the scope of our research, this paper focuses on a subset of those techniques as they apply to the confidence analysis of a specific network path at the time of use or inspection. This confidence analysis allows users, administrators and autonomous systems to decide whether a network path is secure enough for sending their sensitive information. Our testing shows that malicious activity can be identified quickly as a single metric indicator and consistently within a multi-factor indicator analysis. Our research includes the implementation of - hese techniques in a network path confidence analysis service, called Confidence Assessment as a Service. Using our behavior and security patterns, this service evaluates a specific network path and provides a confidence score for that path before, during and after the transmission of sensitive data. Our research and tools give administrators and autonomous systems a much better understanding of the internal operation and configuration of their networks. Our framework will also provide other services that will focus on detecting latent, systemic network problems. By providing a better understanding of network configuration and operation our research enables a more secure and dependable network and helps prevent the theft of information by malicious actors.

As today's networks become larger and more complex, the Distributed Denial of Service (DDoS) flooding attack threats may not only come from the outside of networks but also from inside, such as cloud computing network where exists multiple tenants possibly containing malicious tenants. So, the need of source-based defense mechanism against such attacks is pressing. In this paper, we mainly focus on the source-based defense mechanism against Botnet-based DDoS flooding attack through combining the power of Software-Defined Networking (SDN) and sample flow (sFlow) technology. Firstly, we defined a metric to measure the essential features of this kind attack which means distribution and collaboration. Then we designed a simple detection algorithm based on statistical inference model and response scheme through the abilities of SDN. Finally, we developed an application to realize our idea and also tested its effect on emulation network with real network traffic. The result shows that our mechanism could effectively detect DDoS flooding attack originated in SDN environment and identify attack flows for avoiding the harm of attack spreading to target or outside. We advocate the advantages of SDN in the area of defending DDoS attacks, because it is difficult and laborious to organize selfish and undisciplined traditional distributed network to confront well collaborative DDoS flooding attacks.

The Internet of Things (IoT) architecture is expected to evolve into a model containing various open systems, integrated environments, and platforms, which can be programmed and can provide secure services on demand. However, not much effort has been devoted towards the security of such an IoT architecture. In this paper, we present an IoT architecture that supports deploying dynamic security policies for IoT services. In this approach, IoT devices, gateways, and data are open and programmable to IoT application developers and service operators. Fine-grained security policies can be programmed and dynamically adjusted according to users' requirements, devices' capabilities and networking environments. The implementation and test results show that new security policies can be created and deployed rapidly and demonstrate the feasibility of the architecture.