Data · dataset · 2026
Automated intrusion response systems
Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.17034/32639616.v1
This thesis presents new research into Automated Intrusion Response Systems.
Description
These systems seek to evaluate information available to them at the time of attack detection, and subsequently determine and deploy the optimal response. Previous research proposes systems which are generally too static in both their understanding of a defended network, and in their response capability.
This leads to difficulty when handling today’s dynamic networks and the ever-evolving threat landscape. The work in this thesis investigates the application of emerging technologies and proposes new frameworks to develop more dynamic automated Intrusion Response Systems, which are less reliant on pre-defined network security models, can respond to attacker tactics outlined in MITRE’s ATT&CK, and more closely integrate with user-defined security policies.
Read the rest (2 more)
Specifically, the work in this thesis culminates in the proposal of an IRS which leverages Model-Free Deep Reinforcement Learning, a change in direction to model-based methods. Reinforcement Learning in a novel containerised network testbed allows the Intrusion Response System to gain a better understanding of the impact of its actions in terms of stopping an ongoing attack scenario, and also how that action impacts normal network operation through experience.
Results demonstrate successful response selection against multi-stage attack scenarios and restoration of compromised cyber-physical system processes.<br><br>
Links
Where it is published
- DOI doi.org/10.17034/32639616.v1 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
Provenance · 3 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ZivaHub | oai:figshare.com:article/32639616 | 8 d ago | JSON v1 |
| Deakin Research Online | oai:figshare.com:article/32639616 | 8 d ago | JSON v1 |
| DMU Figshare | oai:figshare.com:article/32639616 | 8 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| description | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/description |
| license_text | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |