Related papers: CHAOS: an SDN-based Moving Target Defense System

Distributed Denial of Service (DDoS) attacks persist as significant threats to online services and infrastructure, evolving rapidly in sophistication and eluding traditional detection mechanisms. This evolution demands a comprehensive…

Intrusion Detection Systems (IDSs) are integral to safeguarding networks by detecting and responding to threats from malicious traffic or compromised devices. However, standalone IDS deployments often fall short when addressing the…

The unmanned aerial vehicle (UAV) network has gained significant attentions in recent years due to its various applications. However, the traffic security becomes the key threatening public safety issue in an emergency rescue system due to…

Denial-of-Service (DoS) and Distributed DoS (DDoS) attacks can cause serious problems in wireless networks due to limited network and host resources. Attacker traceback is a promising solution to take a proper countermeasure near the attack…

The Software-Defined Networks (SDNs) face persistent threats from various adversaries that attack them using different methods to mount Denial of Service attacks. These attackers have different motives and follow diverse tactics to achieve…

DDoS attacks are simple, effective, and still pose a significant threat even after more than two decades. Given the recent success in machine learning, it is interesting to investigate how we can leverage deep learning to filter out…

We propose a neural network model with transient chaos, or a transiently chaotic neural network (TCNN) as an approximation method for combinatorial optimization problem, by introducing transiently chaotic dynamics into neural networks.…

DDoS attacks have become a major threat to the security of IoT devices and can cause severe damage to the network infrastructure. IoT devices suffer from the inherent problem of resource constraints and are therefore susceptible to such…

Differentiable Architecture Search (DARTS) is an effective continuous relaxation-based network architecture search (NAS) method with low search cost. It has attracted significant attentions in Auto-ML research and becomes one of the most…

Software-defined networking (SDN) is a promising technology to overcome many challenges in wireless sensor networks (WSN), particularly with respect to flexibility and reuse. Conversely, the centralization and the planes' separation turn…

We consider a cloud based multiserver system consisting of a set of replica application servers behind a set of proxy (indirection) servers which interact directly with clients over the Internet. We study a proactive moving-target defense…

Software-Defined Networking (SDN) is a novel architectural model for cloud network infrastructure, improving resource utilization, scalability and administration. SDN deployments increasingly rely on virtual switches executing on commodity…

Reactive defense mechanisms, such as intrusion detection systems, have made significant efforts to secure a system or network for the last several decades. However, the nature of reactive security mechanisms has limitations because…

While the adoption of connected vehicles is growing, security and privacy concerns are still the key barriers raised by society. These concerns mandate automakers and standardization groups to propose convenient solutions for privacy…

Distributed denial-of-service attacks on public servers have recently become a serious problem. To assure that network services will not be interrupted and more effective defense mechanisms to protect against malicious traffic, especially…

Large scale cloud networks consist of distributed networking and computing elements that process critical information and thus security is a key requirement for any environment. Unfortunately, assessing the security state of such networks…

As one of the most sophisticated attacks against power grids, coordinated cyber-physical attacks (CCPAs) damage the power grid's physical infrastructure and use a simultaneous cyber attack to mask its effect. This work proposes a novel…

Network intrusion attacks are a known threat. To detect such attacks, network intrusion detection systems (NIDSs) have been developed and deployed. These systems apply machine learning models to high-dimensional vectors of features…

The scarcity of data and the high complexity of Advanced Persistent Threats (APTs) attacks have created challenges in comprehending their behavior and hindered the exploration of effective detection techniques. To create an effective APT…

This study focuses on a method for detecting and classifying distributed denial of service (DDoS) attacks, such as SYN Flooding, ACK Flooding, HTTP Flooding, and UDP Flooding, using neural networks. Machine learning, particularly neural…