The threat of offensive ai to organizations

Y Mirsky, A Demontis, J Kotak, R Shankar, D Gelei… - Computers & …, 2023 - Elsevier
AI has provided us with the ability to automate tasks, extract information from vast amounts of
data, and synthesize media that is nearly indistinguishable from the real thing. However …

Neural language models for network configuration: Opportunities and reality check

ZB Houidi, D Rossi - Computer Communications, 2022 - Elsevier
Boosted by deep learning, natural language processing (NLP) techniques have recently
seen spectacular progress, mainly fueled by breakthroughs both in representation learning …

Towards a systematic multi-modal representation learning for network data

ZB Houidi, R Azorin, M Gallo, A Finamore… - Proceedings of the 21st …, 2022 - dl.acm.org
Learning the right representations from complex input data is the key ability of successful
machine learning (ML) models. The latter are often tailored to a specific data modality. For …

i-DarkVec: Incremental Embeddings for Darknet Traffic Analysis

L Gioacchini, L Vassio, M Mellia, I Drago… - ACM Transactions on …, 2023 - dl.acm.org
Darknets are probes listening to traffic reaching IP addresses that host no services. Traffic
reaching a darknet results from the actions of internet scanners, botnets, and possibly …

Detecting and interpreting changes in scanning behavior in large network telescopes

M Kallitsis, R Prajapati, V Honavar… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Network telescopes or “Darknets” received unsolicited Internet-wide traffic, thus providing a
unique window into macroscopic Internet activities associated with malware propagation …

CBSeq: A Channel-level Behavior Sequence For Encrypted Malware Traffic Detection

S Cui, C Dong, M Shen, Y Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Machine learning and neural networks have become increasingly popular solutions for
encrypted malware traffic detection. They mine and learn complex traffic patterns, enabling …

Monitoring network telescopes and inferring anomalous traffic through the prediction of probing rates

M Zakroum, J Francois, I Chrisment… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Network reconnaissance is the first step preceding a cyber-attack. Hence, monitoring the
probing activities is imperative to help security practitioners enhancing their awareness …

Ddos2vec: Flow-level characterisation of volumetric DDoS attacks at scale

R Singh Samra, M Barcellos - Proceedings of the ACM on Networking, 2023 - dl.acm.org
Volumetric Distributed Denial of Service (DDoS) attacks have been a severe threat to the
Internet for more than two decades. Some success in mitigation has been achieved based …

Dark-TRACER: Early Detection Framework for Malware Activity Based on Anomalous Spatiotemporal Patterns

C Han, J Takeuchi, T Takahashi, D Inoue - IEEE Access, 2022 - ieeexplore.ieee.org
As cyberattacks become increasingly prevalent globally, there is a need to identify trends in
these cyberattacks and take suitable countermeasures quickly. The darknet, an unused IP …

Drawing the web structure and content analysis beyond the Tor darknet: Freenet as a case of study

E Figueras-Martín, R Magán-Carrión… - Journal of Information …, 2022 - Elsevier
Abstract The World Wide Web is the most widely used service on the Internet, although only
a small part of it, the Surface Web, is indexed and accessible. The rest of the content, the …