Optimal Denial-of-Service Attack Policy against Wireless Industrial Control Systems

Designing, planning, and managing telecommunication, industrial control, and enterprise networks with special emphasis on effectiveness, efficiency, and reliability without considering security planning, management, and constraints have made them vulnerable. They have become more vulnerable due to their recent connectivity to open networks with the intention of establishing decentralized management and remote control. Existing Intrusion Prevention and Detection Systems (IPS and IDS) do not guarantee absolute security. The new IDS, which employs both signature-based and anomaly detection as its analysis strategies, will be able to detect both known and unknown attacks and further isolate them. Auto-reclosing techniques used on long rural power lines and multi-resolution techniques were used in developing this IDS, which will help update existing IPSs. It should effectively block Distributed Denial of Service attack (DDoS) based on SNY-flood attacks and help eliminate four out of the five major limitations of existing IDSs and IPSs.

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Robust Stabilization of Resource Limited Networked Control Systems Under Denial-of-Service Attack

2019 IEEE 58th Conference on Decision and Control (CDC) ◽

10.1109/cdc40024.2019.9030027 ◽

2019 ◽

Author(s):

Niladri Sekhar Tripathy ◽

Mohammadreza Chamanbaz ◽

Roland Bouffanais

Keyword(s):

Control Systems ◽

Networked Control Systems ◽

Denial Of Service ◽

Robust Stabilization ◽

Networked Control ◽

Denial Of Service Attack ◽

Resource Limited ◽

Service Attack

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A three-tiered intrusion detection system for industrial control systems

Journal of Cybersecurity ◽

10.1093/cybsec/tyab006 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Eirini Anthi ◽

Lowri Williams ◽

Pete Burnap ◽

Kevin Jones

Keyword(s):

Intrusion Detection ◽

Control Systems ◽

Denial Of Service ◽

Cyber Attacks ◽

Network Activity ◽

Intrusion Detection Systems ◽

Industrial Control ◽

Industrial Control Systems ◽

Detection Systems ◽

Attack Type

Abstract This article presents three-tiered intrusion detection systems, which uses a supervised approach to detect cyber-attacks in industrial control systems networks. The proposed approach does not only aim to identify malicious packets on the network but also attempts to identify the general and finer grain attack type occurring on the network. This is key in the industrial control systems environment as the ability to identify exact attack types will lead to an increased response rate to the incident and the defence of the infrastructure. More specifically, the proposed system consists of three stages that aim to classify: (i) whether packets are malicious; (ii) the general attack type of malicious packets (e.g. Denial of Service); and (iii) finer-grained cyber-attacks (e.g. bad cyclic redundancy check, attack). The effectiveness of the proposed intrusion detection systems is evaluated on network data collected from a real industrial gas pipeline system. In addition, an insight is provided as to which features are most relevant in detecting such malicious behaviour. The performance of the system results in an F-measure of: (i) 87.4%, (ii) 74.5% and (iii) 41.2%, for each of the layers, respectively. This demonstrates that the proposed architecture can successfully distinguish whether network activity is malicious and detect which general attack was deployed.

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