[HTML][HTML] Artificial intelligence for cybersecurity: Literature review and future research directions
Artificial intelligence (AI) is a powerful technology that helps cybersecurity teams automate
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
[HTML][HTML] Network traffic classification: Techniques, datasets, and challenges
In network traffic classification, it is important to understand the correlation between network
traffic and its causal application, protocol, or service group, for example, in facilitating lawful …
traffic and its causal application, protocol, or service group, for example, in facilitating lawful …
TON_IoT telemetry dataset: A new generation dataset of IoT and IIoT for data-driven intrusion detection systems
Although the Internet of Things (IoT) can increase efficiency and productivity through
intelligent and remote management, it also increases the risk of cyber-attacks. The potential …
intelligent and remote management, it also increases the risk of cyber-attacks. The potential …
[HTML][HTML] {FLAME}: Taming backdoors in federated learning
With the worldwide COVID-19 pandemic in 2020 and 2021 necessitating working from
home, corporate Virtual Private Networks (VPNs) have become an important item securing …
home, corporate Virtual Private Networks (VPNs) have become an important item securing …
[HTML][HTML] Ensemble machine learning approach for classification of IoT devices in smart home
The emergence of the Internet of Things (IoT) concept as a new direction of technological
development raises new problems such as valid and timely identification of such devices …
development raises new problems such as valid and timely identification of such devices …
SAFELearn: Secure aggregation for private federated learning
Federated learning (FL) is an emerging distributed machine learning paradigm which
addresses critical data privacy issues in machine learning by enabling clients, using an …
addresses critical data privacy issues in machine learning by enabling clients, using an …
Boosting-based DDoS detection in internet of things systems
Distributed Denial-of-Service (DDoS) attacks remain challenging to mitigate in the existing
systems, including in-home networks that comprise different Internet of Things (IoT) devices …
systems, including in-home networks that comprise different Internet of Things (IoT) devices …
A survey on encrypted network traffic analysis applications, techniques, and countermeasures
The adoption of network traffic encryption is continually growing. Popular applications use
encryption protocols to secure communications and protect the privacy of users. In addition …
encryption protocols to secure communications and protect the privacy of users. In addition …
Information exposure from consumer iot devices: A multidimensional, network-informed measurement approach
Internet of Things (IoT) devices are increasingly found in everyday homes, providing useful
functionality for devices such as TVs, smart speakers, and video doorbells. Along with their …
functionality for devices such as TVs, smart speakers, and video doorbells. Along with their …
The rise of traffic classification in IoT networks: A survey
With the proliferation of the Internet of Things (IoT), the integration and communication of
various objects have become a prevalent practice. The huge growth of IoT devices and …
various objects have become a prevalent practice. The huge growth of IoT devices and …