Biblio

Software-defined networking (SDN) has become a popular technology, being adopted in operational networks and being a hot research topic. Many network testbeds today are used to test new research solutions and would benefit from offering SDN experimentation capabilities to their users. Yet, exposing SDN to experimenters is challenging because experiments must be isolated from each other and limited switch resources must be shared fairly. We outline three different approaches for exposing SDN to experimenters while achieving isolation and fair sharing goals. These solutions use software implementation, shared hardware switches and smart network interface cards to implement SDN in testbeds. These approaches are under development on two operational SDN testbeds: the DeterLab at USC/ISI/Berkeley and the NCL testbed at the National University of Singapore.

Software Defined Networking (SDN) stands to transmute our modern networks and data centers, opening them up into highly agile frameworks that can be reconfigured depending on the requirement. Denial of Service (DoS) attacks are considered as one of the most destructive attacks. This paper, is about DoS attack detection and mitigation using SDN. DoS attack can minimize the bandwidth utilization, leaving the network unavailable for legitimate traffic. To provide a solution to the problem, concept of performance aware Software Defined Networking is used which involves real time network monitoring using sFlow as a visibility protocol. So, OpenFlow along with sFlow is used as an application to fight DoS attacks. Our analysis and results demonstrate that using this technique, DoS attacks are successfully defended implying that SDN has promising potential to detect and mitigate DoS attacks.

Destination IP prefix-based routing protocols are core to Internet routing today. Internet autonomous systems (AS) possess fixed IP prefixes, while packets carry the intended destination AS's prefix in their headers, in clear text. As a result, network communications can be easily identified using IP addresses and become targets of a wide variety of attacks, such as DNS/IP filtering, distributed Denial-of-Service (DDoS) attacks, man-in-the-middle (MITM) attacks, etc. In this work, we explore an alternative network architecture that fundamentally removes such vulnerabilities by disassociating the relationship between IP prefixes and destination networks, and by allowing any end-to-end communication session to have dynamic, short-lived, and pseudo-random IP addresses drawn from a range of IP prefixes rather than one. The concept is seemingly impossible to realize in todays Internet. We demonstrate how this is doable today with three different strategies using software defined networking (SDN), and how this can be done at scale to transform the Internet addressing and routing paradigms with the novel concept of a distributed software defined Internet exchange (SDX). The solution works with both IPv4 and IPv6, whereas the latter provides higher degrees of IP addressing freedom. Prototypes based on Open vSwitches (OVS) have been implemented for experimentation across the PEERING BGP testbed. The SDX solution not only provides a technically sustainable pathway towards large-scale traffic analysis resistant network (TARN) support, it also unveils a new business model for customer-driven, customizable and trustable end-to-end network services.

Vulnerabilities of controller that is caused by separation of control and forwarding lead to a threat which attacker can take remote access detection in SDN. The current work proposes a controller architecture called secure control plane (SCP) that enhances security and increase the difficulty of the attack through a rotation of heterogeneous and multiple controllers. Specifically, a dynamic-scheduling method based on Bayesian Stackelberg Games is put forward to maximize security reward of defender during each migration. Secondly, introducing a self-cleaning mechanism combined with game strategy aims at improving the secure level and form a closed-loop defense mechanism; Finally, the experiments described quantitatively defender will get more secure gain based on the game strategy compared with traditional strategy (pure and random strategies), and the self-cleaning mechanism can make the control plane to be in a higher level of security.

SDN is a new network framework which can be controlled and defined by software programming, and OpenFlow is the communication protocol between SDN controller plane and data plane. With centralized control of SDN, the network is more vulnerable encounter APT than traditional network. After deeply analyzing the process of APT at each stage in SDN, this paper proposes the APT detection method based on HMM, which can fully reflect the relationship between attack behavior and APT stage. Experiment shows that the method is more accurate to detect APT in SDN, and less overhead.

Trusted routing is a hot spot in network security. Lots of efforts have been made on trusted routing validation for Interior Gateway Protocols (IGP), e.g., using Public Key Infrastructure (PKI) to enhance the security of protocols, or routing monitoring systems. However, the former is limited by further deployment in the practical Internet, the latter depends on a complete, accurate, and fresh knowledge base-this is still a big challenge (Internet Service Providers (ISPs) are not willing to leak their routing policies). In this paper, inspired by the idea of centrally controlling in Software Defined Network (SDN), we propose a CENtrally Trusted Routing vAlidation framework, named CENTRA, which can automated collect routing information, centrally detect anomaly and deliver secure routing policy. We implement the proposed framework using NETCONF as the communication protocol and YANG as the data model. The experimental results reveal that CENTRA can detect and block anomalous routing in real time. Comparing to existing secure routing mechanism, CENTRA improves the detection efficiency and real-time significantly.

The majority of business activity of our integrated and connected world takes place in networks based on cloud computing infrastructure that cross national, geographic and jurisdictional boundaries. Such an efficient entity interconnection is made possible through an emerging networking paradigm, Software Defined Networking (SDN) that intends to vastly simplify policy enforcement and network reconfiguration in a dynamic manner. However, despite the obvious advantages this novel networking paradigm introduces, its increased attack surface compared to traditional networking deployments proved to be a thorny issue that creates skepticism when safety-critical applications are considered. Especially when SDN is used to support Internet-of-Things (IoT)-related networking elements, additional security concerns rise, due to the elevated vulnerability of such deployments to specific types of attacks and the necessity of inter-cloud communication any IoT application would require. The overall number of connected nodes makes the efficient monitoring of all entities a real challenge, that must be tackled to prevent system degradation and service outage. This position paper provides an overview of common security issues of SDN when linked to IoT clouds, describes the design principals of the recently introduced Blockchain paradigm and advocates the reasons that render Blockchain as a significant security factor for solutions where SDN and IoT are involved.

The majority of business activity of our integrated and connected world takes place in networks based on cloud computing infrastructure that cross national, geographic and jurisdictional boundaries. Such an efficient entity interconnection is made possible through an emerging networking paradigm, Software Defined Networking (SDN) that intends to vastly simplify policy enforcement and network reconfiguration in a dynamic manner. However, despite the obvious advantages this novel networking paradigm introduces, its increased attack surface compared to traditional networking deployments proved to be a thorny issue that creates skepticism when safety-critical applications are considered. Especially when SDN is used to support Internet-of-Things (IoT)-related networking elements, additional security concerns rise, due to the elevated vulnerability of such deployments to specific types of attacks and the necessity of inter-cloud communication any IoT application would require. The overall number of connected nodes makes the efficient monitoring of all entities a real challenge, that must be tackled to prevent system degradation and service outage. This position paper provides an overview of common security issues of SDN when linked to IoT clouds, describes the design principals of the recently introduced Blockchain paradigm and advocates the reasons that render Blockchain as a significant security factor for solutions where SDN and IoT are involved.

Software Defined Networks (SDNs) is a new networking paradigm that has gained a lot of attention in recent years especially in implementing data center networks and in providing efficient security solutions. The popularity of SDN and its attractive security features suggest that it can be used in the context of smart grid systems to address many of the vulnerabilities and security problems facing such critical infrastructure systems. This paper studies the impact of different cyber attacks that can target smart grid communication network which is implemented as a software defined network on the operation of the smart grid system in general. In particular, we perform different attack scenarios including DDoS attacks, location highjacking and link overloading against SDN networks of different controller types that include POX, Floodlight and RYU. Our experiments were carried out using the mininet simulator. The experiments show that SDN-enabled smartgrid systems are vulnerable to different types of attacks.

In recent years, cyber security oriented research is paying much close attention on Vehicular Adhoc NETworks (VANETs). However, existing vehicular networks do not meet current security requirements. Typically for dynamic networks, maximal decentralization and rapidly changing topology of moving hosts form a number of security issues associated with ensuring access control of hosts, security policy enforcement, and resistance of the routing methods. To solve these problems generally, the paper reviews SDN (software defined networks) based network security architectures of VANET. The following tasks are solved in our work: composing of network security architectures for SDN-VANET (architecture with the central control and shared security servers, decentralized (zoned) architecture, hierarchical architecture); implementation of these architectures in virtual modeling environment; and experimental study of effectiveness of the suggested architectures. With large-scale vehicular networks, architectures with multiple SDN controllers are most effective. In small networks, the architecture with the central control also significantly outperforms the traditional VANET architecture. For the suggested architectures, three control modes are discussed in the paper: central, distributed and hybrid modes. Unlike common architectures, all of the proposed security architectures allow us to establish a security policy in m2m-networks and increase resistance capabilities of self-organizing networks.

The IoT (Internet of Things) is one of the primary reasons for the massive growth in the number of connected devices to the Internet, thus leading to an increased volume of traffic in the core network. Fog and edge computing are becoming a solution to handle IoT traffic by moving timesensitive processing to the edge of the network, while using the conventional cloud for historical analysis and long-term storage. Providing processing, storage, and network communication at the edge network are the aim of fog computing to reduce delay, network traffic, and decentralise computing. In this paper, we define a framework that realises fog computing that can be extended to install any service of choice. Our framework utilises fog nodes as an extension of the traditional switch to include processing, networking, and storage. The fog nodes act as local decision-making elements that interface with software-defined networking (SDN), to be able to push updates throughout the network. To test our framework, we develop an IP spoofing security application and ensure its correctness through multiple experiments.

Vehicular ad-Hoc Networks (VANETs) have been promoted as a key technology that can provide a wide variety of services such as traffic management, passenger safety, as well as travel convenience and comfort. VANETs are now proposed to be part of the upcoming Fifth Generation (5G) technology, integrated with Software Defined Networking (SDN), as key enabler of 5G. The technology of fog computing in 5G turned out to be an adequate solution for faster processing in delay sensitive application, such as VANETs, being a hybrid solution between fully centralized and fully distributed networks. In this paper, we propose a three-way integration between VANETs, SDN, and 5G for a resilient VANET security design approach, which strikes a good balance between network, mobility, performance and security features. We show how such an approach can secure VANETs from different types of attacks such as Distributed Denial of Service (DDoS) targeting either the controllers or the vehicles in the network, and how to trace back the source of the attack. Our evaluation shows the capability of the proposed system to enforce different levels of real-time user-defined security, while maintaining low overhead and minimal configuration.

Life-cycle management of stateful VNF services is a complicated task, especially when automated resiliency and scaling should be handled in a secure manner, without service degradation. We present FlowSNAC, a resilient and scalable VNF service for user authentication and service deployment. FlowSNAC consists of both stateful and stateless components, some of that are SDN-based and others that are NFVs. We describe how it adapts to changing conditions by automatically updating resource allocations through a series of intermediate steps of traffic steering, resource allocation, and secure state transfer. We conclude by highlighting some of the lessons learned during implementation, and their wider consequences for the architecture of SDN/NFV management and orchestration systems.

Software Defined Networking (SDN) is the new promise towards an easily configured and remotely controlled network. Based on Centralized control, SDN technology has proved its positive impact on the world of network communications from different aspects. Security in SDN, as in traditional networks, is an essential feature that every communication system should possess. In this paper, we propose an SDN security design approach, which strikes a good balance between network performance and security features. We show how such an approach can be used to prevent DDoS attacks targeting either the controller or the different hosts in the network, and how to trace back the source of the attack. The solution lies in introducing a third plane, the security plane, in addition to the data plane, which is responsible for forwarding data packets between SDN switches, and parallel to the control plane, which is responsible for rule and data exchange between the switches and the SDN controller. The security plane is designed to exchange security-related data between a third party agent on the switch and a third party software module alongside the controller. Our evaluation shows the capability of the proposed system to enforce different levels of real-time user-defined security with low overhead and minimal configuration.

In this paper, we propose a hardware-based defense system in Software-Defined Networking architecture to protect against the HTTP GET Flooding attacks, one of the most dangerous Distributed Denial of Service (DDoS) attacks in recent years. Our defense system utilizes per-URL counting mechanism and has been implemented on FPGA as an extension of a NetFPGA-based OpenFlow switch.

Software-Defined Networking (SDN) allows for fast reactions to security threats by dynamically enforcing simple forwarding rules as counter-measures. However, in classic SDN all the intelligence resides at the controller, with the switches only capable of performing stateless forwarding as ruled by the controller. It follows that the controller, in addition to network management and control duties, must collect and process any piece of information required to take advanced (stateful) forwarding decisions. This threatens both to overload the controller and to congest the control channel. On the other hand, stateful SDN represents a new concept, developed both to improve reactivity and to offload the controller and the control channel by delegating local treatments to the switches. In this paper, we adopt this stateful paradigm to protect end-hosts from Distributed Denial of Service (DDoS). We propose StateSec, a novel approach based on in-switch processing capabilities to detect and mitigate DDoS attacks. StateSec monitors packets matching configurable traffic features (e.g., IP src/dst, port src/dst) without resorting to the controller. By feeding an entropy-based algorithm with such monitoring features, StateSec detects and mitigates several threats such as (D)DoS and port scans with high accuracy. We implemented StateSec and compared it with a state-of-the-art approach to monitor traffic in SDN. We show that StateSec is more efficient: it achieves very accurate detection levels, limiting at the same time the control plane overhead.

Securing Internet of Things (IoT) systems is a challenge because of its multiple points of vulnerability. A spate of recent hacks and security breaches has unveiled glaring vulnerabilities in the IoT. Due to the computational and memory requirement constraints associated with anomaly detection algorithms in core networks, commercial in-line (part of the direct line of communication) Anomaly Detection Systems (ADSs) rely on sampling-based anomaly detection approaches to achieve line rates and truly-inline anomaly detection accuracy in real-time. However, packet sampling is inherently a lossy process which might provide an incomplete and biased approximation of the underlying traffic patterns. Moreover, commercial routers uses proprietary software making them closed to be manipulated from the outside. As a result, detecting malicious packets on the given network path is one of the most challenging problems in the field of network security. We argue that the advent of Software Defined Networking (SDN) provides a unique opportunity to effectively detect and mitigate DDoS attacks. Unlike sampling-based approaches for anomaly detection and limitation of proprietary software at routers, we use the SDN infrastructure to relax the sampling-based ADS constraints and collect traffic flow statistics which are maintained at each SDN-enabled switch to achieve high detection accuracy. In order to implement our idea, we discuss how to mitigate DDoS attacks using the features of SDN infrastructure.

With the advent of smart devices and lowering prices of sensing devices, adoption of Internet of Things (IoT) is gaining momentum. These IoT devices come with greater threat of being attacked or compromised that could lead to Denial of Service (DoS) and Distributed Denial of Service (DDoS). The high volume of IoT devices with high level of heterogeneity, magnify the possibility of security threats. So far, there is no protocol to guarantee the security of IoT devices. But to enable resilience, continuous monitoring is required along with adaptive decision making. These challenges can be addressed with the help of Software Defined Networking (SDN) which can effectively handle the security threats to the IoT devices in dynamic and adaptive manner without any burden on the IoT devices. In this paper, we propose an SDN-based secure IoT framework called SoftThings to detect abnormal behaviors and attacks as early as possible and mitigate as appropriate. Machine Learning is used at the SDN controller to monitor and learn the behavior of IoT devices over time. We have conducted experiments on Mininet emulator. Initial results show that this framework is capable to detect attacks on IoT with around 98% precision.

One of the recent focuses in Cloud Computing networks is Software Defined Clouds (SDC), where the Software-Defined Networking (SDN) technology is combined with the traditional Cloud network. SDC is aimed to create an effective Cloud environment by extending the virtualization concept to all resources. In that, the control plane is decoupled from the data plane in a network device and controlled by the centralized controller using the OpenFlow Protocol (OFP). As the centralized controller performs all control functions in a network, it requires strong security. Already, Cloud Computing faces many security challenges. Most vulnerable attacks in SDC is Denial-of-Service (DoS) and Distributed DoS (DDoS) attacks. To overcome the DoS attacks, we propose a distributed Firewall with Intrusion Prevention System (IPS) for SDC. The proposed distributed security mechanism is investigated for two DoS attacks, ICMP and SYN flooding attacks for different network scenarios. From the simulation results and discussion, we showed that the distributed Firewall with IPS security detects and prevents the DoS attack effectively.

The evolution of information and communication technologies has brought new challenges in managing the Internet. Software-Defined Networking (SDN) aims to provide easily configured and remotely controlled networks based on centralized control. Since SDN will be the next disruption in networking, SDN security has become a hot research topic because of its importance in communication systems. A centralized controller can become a focal point of attack, thus preventing attack in controller will be a priority. The whole network will be affected if attacker gain access to the controller. One of the attacks that affect SDN controller is DDoS attacks. This paper reviews different detection techniques that are available to prevent DDoS attacks, characteristics of these techniques and issues that may arise using these techniques.

Software Defined Networks (SDNs) have gained prominence recently due to their flexible management and superior configuration functionality of the underlying network. SDNs, with OpenFlow as their primary implementation, allow for the use of a centralised controller to drive the decision making for all the supported devices in the network and manage traffic through routing table changes for incoming flows. In conventional networks, machine learning has been shown to detect malicious intrusion, and classify attacks such as DoS, user to root, and probe attacks. In this work, we extend the use of machine learning to improve traffic tolerance for SDNs. To achieve this, we extend the functionality of the controller to include a resilience framework, ReSDN, that incorporates machine learning to be able to distinguish DoS attacks, focussing on a neptune attack for our experiments. Our model is trained using the MIT KDD 1999 dataset. The system is developed as a module on top of the POX controller platform and evaluated using the Mininet simulator.

Summary form only given. Strong light-matter coupling has been recently successfully explored in the GHz and THz [1] range with on-chip platforms. New and intriguing quantum optical phenomena have been predicted in the ultrastrong coupling regime [2], when the coupling strength Ω becomes comparable to the unperturbed frequency of the system ω. We recently proposed a new experimental platform where we couple the inter-Landau level transition of an high-mobility 2DEG to the highly subwavelength photonic mode of an LC meta-atom [3] showing very large Ω/ωc = 0.87. Our system benefits from the collective enhancement of the light-matter coupling which comes from the scaling of the coupling Ω ∝ √n, were n is the number of optically active electrons. In our previous experiments [3] and in literature [4] this number varies from 104-103 electrons per meta-atom. We now engineer a new cavity, resonant at 290 GHz, with an extremely reduced effective mode surface Seff = 4 × 10-14 m2 (FE simulations, CST), yielding large field enhancements above 1500 and allowing to enter the few (\textbackslashtextless;100) electron regime. It consist of a complementary metasurface with two very sharp metallic tips separated by a 60 nm gap (Fig.1(a, b)) on top of a single triangular quantum well. THz-TDS transmission experiments as a function of the applied magnetic field reveal strong anticrossing of the cavity mode with linear cyclotron dispersion. Measurements for arrays of only 12 cavities are reported in Fig.1(c). On the top horizontal axis we report the number of electrons occupying the topmost Landau level as a function of the magnetic field. At the anticrossing field of B=0.73 T we measure approximately 60 electrons ultra strongly coupled (Ω/ω- \textbackslashtextbar\textbackslashtextbar

A Software-Defined Wireless Sensor Network (SD-WSN) is a recently developed model which is expected to play a large role not only in the development of the Internet of Things (IoT) paradigm but also as a platform for other applications such as smart water management. This model makes use of a Software-Defined Networking (SDN) approach to manage a Wireless Sensor Network (WSN) in order to solve most of the inherent issues surrounding WSNs. One of the most important aspects of any network, is security. This is an area that has received little attention within the development of SDWSNs, as most research addresses security concerns within SDN and WSNs independently. There is a need for research into the security of SDWSN. Some concepts from both SDN and WSN security can be adjusted to suit the SDWSN model while others cannot. Further research is needed into consolidating SDN and WSN security measures to consider security in SDWSN. Threats, challenges and potential solutions to securing SDWSN are presented by considering both the WSN and SDN paradigms.

Two emerging architectural paradigms, i.e., Software Defined Networking (SDN) and Network Function Virtualization (NFV), enable the deployment and management of Service Function Chains (SFCs). A SFC is an ordered sequence of abstract Service Functions (SFs), e.g., firewalls, VPN-gateways, traffic monitors, that packets have to traverse in the route from source to destination. While this appealing solution offers significant advantages in terms of flexibility, it also introduces new challenges such as the correct configuration and ordering of SFs in the chain to satisfy overall security requirements. This paper presents a formal model conceived to enable the verification of correct policy enforcements in SFCs. Software tools based on the model can then be designed to cope with unwanted network behaviors (e.g., security flaws) deriving from incorrect interactions of SFs of the same SFC. 

Software-defined networking is considered a promising new paradigm, enabling more reliable and formally verifiable communication networks. However, this paper shows that the separation of the control plane from the data plane, which lies at the heart of Software-Defined Networks (SDNs), introduces a new vulnerability which we call teleportation. An attacker (e.g., a malicious switch in the data plane or a host connected to the network) can use teleportation to transmit information via the control plane and bypass critical network functions in the data plane (e.g., a firewall), and to violate security policies as well as logical and even physical separations. This paper characterizes the design space for teleportation attacks theoretically, and then identifies four different teleportation techniques. We demonstrate and discuss how these techniques can be exploited for different attacks (e.g., exfiltrating confidential data at high rates), and also initiate the discussion of possible countermeasures. Generally, and given today's trend toward more intent-based networking, we believe that our findings are relevant beyond the use cases considered in this paper.