The robustness of a network's connectivity to other networks is often highly dependent on a few critical nodes and links that tie the network to the larger topology. The failure or degradation to such network bottlenecks can result in outages that may propagate throughout the network. Unfortunately, the presence of the bottlenecks also offers opportunities for targeted link flooding attacks (LFAs). Researchers have proposed a new and promising defense to counter LFAs, referred to as topology deception. This strategy centers on hindering the discovery of bottlenecks by presenting false trace responses to adversaries as they perform topological probing of the target network. Even though the goal of topology deception centers on obscuring critical links, node dependencies can be exploited by an adversary. However, current approaches do not consider a wide range of metrics that may reveal important and diverse aspects of network bottlenecks. Furthermore, existing approaches create a simple form of virtual topology, which is subject to relatively easy detection by the adversary, reducing its effectiveness. In this paper, we propose a comprehensive topology deception framework, which we refer to as BottleNet. Our suggested approach can analyze various network topology features both with respect to static and dynamic metrics and then use this information to identify bottlenecks, finally producing complex virtual topologies that are resilient to adversarial detection.

While the use of containerization technologies for virtual application deployment has grown at an astonishing rate, the question of the robustness of container networking has not been well scrutinized from a security perspective, even though inter-container networking is indispensable for microservices. Thus, this paper first analyzes container networks from a security perspective, discussing the implications based on their architectural limitations. Then, it presents, a secure inter-container communication bridge. introduces ( $i$ ) a network security enforcement stack that provides fine-grained control per container application and securely isolates inter-container traffic in a point-to-point manner. also supports ( $ii$ ) selective security function chaining, enabling various security functions to be chained between containers for further security inspections (e.g., deep packet inspection) according to the container’s network context. incorporates ( $iii$ ) a security policy assistant that helps an administrator discover inter-container networking dependencies correctly. Our evaluation demonstrates how can effectively mitigate several adversarial attacks in container networks while improving the overall performance up to 25.4% within single-host containers and 17.7% for cross-host container communications.

While container adoption has witnessed significant growth in facilitating the operation of large-scale applications, this increased attention has also attracted adversaries who exploit numerous vulnerabilities present in contemporary containers. Unfortunately, existing security solutions largely overlooked the need to restrict container access to the shared host kernel, particularly exhibiting critical limitations in enforcing the least privilege for containers during runtime. Hence, we propose Optimus, an automated and comprehensive system that confines container operations and governs their interactions with the host kernel using an association-based system call filtering. Optimus efficiently identifies the essential system calls required by containers and enhances their security posture by dynamically enforcing the minimal set of system calls for each container during runtime. This is achieved through (1) lightweight system call monitoring leveraging eBPF, (2) system call validation via association analysis, and (3) dynamic system call filtering by adopting covert container renewal. Our evaluation shows that Optimus effectively minimizes the necessary system calls for containers while maintaining their serviceability and operational efficiency during runtime.

Containerization has gained significant popularity in cloud-native applications, offering lightweight and portable capabilities, with container orchestration platforms such as Kubernetes, simplifying deployment and management. However, the presence of human errors, especially misconfigurations, continues to pose substantial security risks to containers. One specific challenge lies in generating effective network security policies, given the intricate nature of label-based container management and the dynamic characteristics of container deployments. This paper introduces KUNERVA, an innovative and automated solution specifically designed to tackle the critical security challenge in container environments. KUNERVA focuses on policy discovery utilizing network logs to generate a minimum set of network security policies to achieve maximum network traffic coverage while ensuring the security isolation between containers. To enhance the reliability of the generated policies, KUNERVA seamlessly integrates with a policy enforcement system, Gatekeeper, for accurate policy verification. Consequently, KUNERVA ensures the discovery of an efficient and effective network policy set, blocking the enforcement of malicious network policies.

With the increasing adoption of containerization in cloud services, container networking has become a critical concern, as it enables the agile deployment of microservices but also introduces new vulnerabilities susceptible to network attacks, posing a threat to container environments. While several security solutions have been introduced to address this concern, they unfortunately exhibit significant shortcomings, including security vulnerabilities and limited performance. We thus propose Helios, a novel hardware-based network security extension that addresses the security and performance limitations in existing solutions. Leveraging a smartNIC, Helios enhances both the security and performance facets of container networking through two key mechanisms: (i) the establishment of physically isolated container communication channels and (ii) the network security engines fully offloaded to the smartNIC. Our evaluation shows that Helios mitigates various network threats initiated from both container- and host-side while performing up to 3x faster than the existing solutions in container communication.

Software-Defined Networking (SDN) has aggressively grown in data center networks, telecommunication providers, and enterprises by virtue of its programmable and extensible control plane. Also, there have been many kinds of research on the security of SDN components along with the growth of SDN. Some of them have inspected network policy inconsistency problems that can severely cause network reliability and security issues in SDN. However, they do not consider whether a single network policy itself is corrupted during processing inside and between SDN components. In this paper, we thus focus on the question of how to automatically identify cases in which the SDN stack fails to prevent policy inconsistencies from arising among those components. We then present AudiSDN, an automated fuzz-testing framework designed to formulate test cases in which policy inconsistencies can arise in OpenFlow networks, the most prevalent SDN protocol. To prove its feasibility, we applied AudiSDN to two widely used SDN controllers, Floodlight and ONOS, and uncovered three separate CVEs (Common Vulnerabilities and Exposures) that cause the network policy inconsistencies among SDN components. Furthermore, we investigate the design flaws that cause the inconsistencies in modern SDN components, suggesting specific validations to address such a serious but understudied pragmatic concern.