Related papers: Manipulating OpenFlow Link Discovery Packet Forwar…
Centralized Software-Defined Networking (cSDN) offers flexible and programmable control of networks but suffers from scalability and reliability issues due to its reliance on centralized controllers. Decentralized SDN (dSDN) alleviates…
Deep packet inspection (DPI) has been extensively investigated in software-defined networking (SDN) as complicated attacks may intractably inject malicious payloads in the packets. Existing proprietary pattern-based or port-based…
Software-Defined Networking (SDN) separates the network control plane and data plane, which provides a network-wide view with centralized control (in the control plane) and programmable network configuration for data plane injected by SDN…
Traffic visibility remains a key component for management and security operations. Observing unsolicited and erroneous traffic, such as unanswered traffic or errors, is fundamental to detect misconfiguration, temporary failures or attacks.…
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.…
Deploying deep neural networks (DNNs) on edge devices exposes valuable intellectual property to model-stealing attacks. While TEE-shielded DNN partitioning (TSDP) mitigates this by isolating sensitive computations, existing paradigms fail…
Software defined networking (SDN) has been adopted to enforce the security of large-scale and complex networks because of its programmable, abstract, centralized intelligent control and global and real-time traffic view. However, the…
The evolution of Software-Defined Networking (SDN) has so far been predominantly geared towards defining and refining the abstractions on the forwarding and control planes. However, despite a maturing south-bound interface and a range of…
Data poisoning attacks compromise the integrity of machine-learning models by introducing malicious training samples to influence the results during test time. In this work, we investigate backdoor data poisoning attack on deep neural…
The importance of cloud computing has grown over the last years, which resulted in a significant increase of Data Center (DC) network requirements. Virtualisation is one of the key drivers of that transformation and enables a massive…
With the wide deployment of network facilities and the increasing requirement of network reliability, the disruptive event like natural disaster, power outage or malicious attack has become a non-negligible threat to the current…
As the capacity of deep neural networks (DNNs) increases, their need for huge amounts of data significantly grows. A common practice is to outsource the training process or collect more data over the Internet, which introduces the risks of…
State-of-the-art machine learning models are vulnerable to data poisoning attacks whose purpose is to undermine the integrity of the model. However, the current literature on data poisoning attacks is mainly focused on ad hoc techniques…
The Software-defined networking(SDN) paradigm centralizes control decisions to improve programmability and simplify network management. However, this centralization turns the network vulnerable to denial of service (DoS) attacks, and in the…
Ransomware is currently the key threat for individual as well as corporate Internet users. Especially dangerous is crypto ransomware that encrypts important user data and it is only possible to recover it once a ransom has been paid.…
Future practical implementation of secure quantum communication technology in a multiuser network environment would require automatic monitoring of the optical link condition and quantum system parameters, along with adjusting them in real…
Deep neural networks (DNNs) have demonstrated their superiority in practice. Arguably, the rapid development of DNNs is largely benefited from high-quality (open-sourced) datasets, based on which researchers and developers can easily…
As networks expand in size and complexity, they pose greater administrative and management challenges. Software Defined Networks (SDN) offer a promising approach to meeting some of these challenges. In this paper, we propose a policy driven…
Collaboration opportunities for devices are facilitated with Federated Learning (FL). Edge computing facilitates aggregation at edge and reduces latency. To deal with model poisoning attacks, model-based outlier detection mechanisms may not…
Software Defined Networking (SDN) promises greater flexibility for directing packet flows, and Network Function Virtualization promises to enable dynamic management of software-based network functions. However, the current divide between an…