SDN Architecture and Southbound APIs for IPv6 Segment Routing Enabled Wide Area Networks

The SRv6 architecture (Segment Routing based on IPv6 data plane) is a promising solution to support services like Traffic Engineering, Service Function Chaining and Virtual Private Networks in IPv6 backbones and datacenters. The SRv6 architecture has interesting scalability properties as it reduces the amount of state information that needs to be configured in the nodes to support the network services. In this paper, we describe the advantages of complementing the SRv6 technology with an SDN based approach in backbone networks. We discuss the architecture of a SRv6 enabled network based on Linux nodes. In addition, we present the design and implementation of the Southbound API between the SDN controller and the SRv6 device. We have defined a data-model and four different implementations of the API, respectively based on gRPC, REST, NETCONF and remote Command Line Interface (CLI). Since it is important to support both the development and testing aspects we have realized an Intent based emulation system to build realistic and reproducible experiments. This collection of tools automate most of the configuration aspects relieving the experimenter from a significant effort. Finally, we have realized an evaluation of some performance aspects of our architecture and of the different variants of the Southbound APIs and we have analyzed the effects of the configuration updates in the SRv6 enabled nodes

The Rise of Mobile and the Diffusion of Technology-Facilitated Trafficking

In this report, researchers at the USC Annenberg Center on Communication Leadership & Policy (CCLP) reveal how those involved in human trafficking have been quick to adapt to the 21st-century global landscape. While the rapid diffusion of digital technologies such as mobile phones, social networking sites, and the Internet has provided significant benefits to society, new channels and opportunities for exploitation have also emerged. Increasingly, the business of human trafficking is taking place online and over mobile phones. But the same technologies that are being used for trafficking can become a powerful tool to combat trafficking. The precise role that digital technologies play in human trafficking still remains unclear, however, and a closer examination of the phenomenon is vital to identify and respond to new threats and opportunities.This investigation indicates that mobile devices and networks have risen in prominence and are now of central importance to the sex trafficking of minors in the United States. While online platforms such as online classifieds and social networking sites remain a potential venue for exploitation, this research suggests that technology facilitated trafficking is more diffuse and adaptive than initially thought. This report presents a review of current literature, trends, and policies; primary research based on mobile phone data collected from online classified sites; a series of firsthand interviews with law enforcement; and key recommendations to policymakers and stakeholders moving forward

The Challenges in SDN/ML Based Network Security : A Survey

Machine Learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking (SDN) emerge. Sitting at the application layer and communicating with the control layer, machine learning based SDN security models exercise a huge influence on the routing/switching of the entire SDN. Compromising the models is consequently a very desirable goal. Previous surveys have been done on either adversarial machine learning or the general vulnerabilities of SDNs but not both. Through examination of the latest ML-based SDN security applications and a good look at ML/SDN specific vulnerabilities accompanied by common attack methods on ML, this paper serves as a unique survey, making a case for more secure development processes of ML-based SDN security applications.Comment: 8 pages. arXiv admin note: substantial text overlap with arXiv:1705.0056

Outsmarting Network Security with SDN Teleportation

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 \emph{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.Comment: Accepted in EuroSP'1

Know Your Enemy: Stealth Configuration-Information Gathering in SDN

Software Defined Networking (SDN) is a network architecture that aims at providing high flexibility through the separation of the network logic from the forwarding functions. The industry has already widely adopted SDN and researchers thoroughly analyzed its vulnerabilities, proposing solutions to improve its security. However, we believe important security aspects of SDN are still left uninvestigated. In this paper, we raise the concern of the possibility for an attacker to obtain knowledge about an SDN network. In particular, we introduce a novel attack, named Know Your Enemy (KYE), by means of which an attacker can gather vital information about the configuration of the network. This information ranges from the configuration of security tools, such as attack detection thresholds for network scanning, to general network policies like QoS and network virtualization. Additionally, we show that an attacker can perform a KYE attack in a stealthy fashion, i.e., without the risk of being detected. We underline that the vulnerability exploited by the KYE attack is proper of SDN and is not present in legacy networks. To address the KYE attack, we also propose an active defense countermeasure based on network flows obfuscation, which considerably increases the complexity for a successful attack. Our solution offers provable security guarantees that can be tailored to the needs of the specific network under consideratio