Novel deep learning-enabled LSTM autoencoder architecture for discovering anomalous events from intelligent transportation systems

J Ashraf, AD Bakhshi, N Moustafa… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITS), especially Autonomous Vehicles (AVs), are
vulnerable to security and safety issues that threaten the lives of the people. Unlike manual …

Long short-term memory and fuzzy logic for anomaly detection and mitigation in software-defined network environment

MP Novaes, LF Carvalho, J Lloret, ML Proença - IEEE Access, 2020 - ieeexplore.ieee.org
Computer networks become complex and dynamic structures. As a result of this fact, the
configuration and the managing of this whole structure is a challenging activity. Software …

LITNET-2020: An annotated real-world network flow dataset for network intrusion detection

R Damasevicius, A Venckauskas, S Grigaliunas… - Electronics, 2020 - mdpi.com
Network intrusion detection is one of the main problems in ensuring the security of modern
computer networks, Wireless Sensor Networks (WSN), and the Internet-of-Things (IoT). In …

[PDF][PDF] 智能网联车网络安全研究综述.

吴武飞, 李仁发, 曾刚, 谢勇… - Journal on …, 2020 - infocomm-journal.com
针对汽车的网络攻击不仅会造成隐私泄露和经济损失, 严重情况下还会危及生命安全,
甚至上升为国家公共安全问题, 因此智能网联车网络安全问题已成为当前研究的热点. 首先 …

Distributed network intrusion detection system in satellite-terrestrial integrated networks using federated learning

K Li, H Zhou, Z Tu, W Wang, H Zhang - IEEE Access, 2020 - ieeexplore.ieee.org
The existing satellite-terrestrial integrated networks (STINs) suffer from security and privacy
concerns due to the limited resources, poor attack resistance and high privacy requirements …

A review of intrusion detection system in IoT with machine learning approach: current and future research

EP Nugroho, T Djatna, IS Sitanggang… - … on science in …, 2020 - ieeexplore.ieee.org
Internet of Things (IoT) devices with their network services are often vulnerable to attacks
because they are not designed for security. Especially with the rapid technological advances …

GOAMLP: Network intrusion detection with multilayer perceptron and grasshopper optimization algorithm

S Moghanian, FB Saravi, G Javidi, EO Sheybani - IEEE Access, 2020 - ieeexplore.ieee.org
In this paper, an intrusion detection system is introduced that uses data mining and machine
learning concepts to detect network intrusion patterns. In the proposed method, an artificial …

Addressing the lack of comparability & testing in CAN intrusion detection research: A comprehensive guide to CAN IDS data & introduction of the ROAD dataset

ME Verma, MD Iannacone, RA Bridges… - arXiv preprint arXiv …, 2020 - arxiv.org
Although ubiquitous in modern vehicles, Controller Area Networks (CANs) lack basic
security properties and are easily exploitable. A rapidly growing field of CAN security …

On the performance of detecting injection of fabricated messages into the can bus

L ben Othmane, L Dhulipala… - … on Dependable and …, 2020 - ieeexplore.ieee.org
There have been several public demonstrations of attacks on connected vehicles showing
the ability of an attacker to take control of a targeted vehicle by injecting messages into their …

Towards holistic secure networking in connected vehicles through securing CAN-bus communication and firmware-over-the-air updating

G Kornaros, O Tomoutzoglou, D Mbakoyiannis… - Journal of Systems …, 2020 - Elsevier
With the increasing connectivity in modern vehicle infrastructure, solutions are required to
harden the vehicle's electronic architecture against potential attacks. One of the most …