Kim Hammar

About Kim Hammar

Kim Hammar, With an exceptional h-index of 7 and a recent h-index of 7 (since 2020), a distinguished researcher at Kungliga Tekniska högskolan, specializes in the field of Distributed Systems, Machine Learning, Cyber Security, Game Theory, Self-Learning Systems.

His recent articles reflect a diverse array of research interests and contributions to the field:

Automated Security Response through Online Learning with Adaptive Conjectures

Intrusion Tolerance for Networked Systems through Two-Level Feedback Control

Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games

Scalable Learning of Intrusion Responses through Recursive Decomposition

Optimal Observation-Intervention Trade-Off in Optimisation Problems with Causal Structure

Demonstrating a System for Dynamically Meeting Management Objectives on a Service Mesh

Digital twins for security automation

Learning near-optimal intrusion responses against dynamic attackers

Kim Hammar Information

University

Position

Ph.D. candidate at

Citations(all)

158

Citations(since 2020)

154

Cited By

13

hIndex(all)

7

hIndex(since 2020)

7

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Google Scholar

Kim Hammar Skills & Research Interests

Distributed Systems

Machine Learning

Cyber Security

Game Theory

Self-Learning Systems

Top articles of Kim Hammar

Automated Security Response through Online Learning with Adaptive Conjectures

arXiv preprint arXiv:2402.12499

2024/2/19

Intrusion Tolerance for Networked Systems through Two-Level Feedback Control

arXiv preprint arXiv:2404.01741

2024/4/2

Kim Hammar
Kim Hammar

H-Index: 2

Rolf Stadler
Rolf Stadler

H-Index: 17

Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games

arXiv preprint arXiv:2402.18781

2024/2/29

Scalable Learning of Intrusion Responses through Recursive Decomposition

2023/9/6

Kim Hammar
Kim Hammar

H-Index: 2

Rolf Stadler
Rolf Stadler

H-Index: 17

Optimal Observation-Intervention Trade-Off in Optimisation Problems with Causal Structure

arXiv preprint arXiv:2309.02287

2023/9/5

Kim Hammar
Kim Hammar

H-Index: 2

Demonstrating a System for Dynamically Meeting Management Objectives on a Service Mesh

2023/5/8

Digital twins for security automation

2023/5/8

Kim Hammar
Kim Hammar

H-Index: 2

Rolf Stadler
Rolf Stadler

H-Index: 17

Learning near-optimal intrusion responses against dynamic attackers

IEEE Transactions on Network and Service Management 2023

2023/1/11

Kim Hammar
Kim Hammar

H-Index: 2

Rolf Stadler
Rolf Stadler

H-Index: 17

An online framework for adapting security policies in dynamic it environments

2022/10/31

Kim Hammar
Kim Hammar

H-Index: 2

Rolf Stadler
Rolf Stadler

H-Index: 17

Learning Security Strategies through Game Play and Optimal Stopping

International Conference on Machine Learning (ICML) Ml4Cyber Workshop 2022: International Conference on Machine Learning, Baltimore, USA July 17-23.

2022/5/29

Kim Hammar
Kim Hammar

H-Index: 2

Rolf Stadler
Rolf Stadler

H-Index: 17

A System for Interactive Examination of Learned Security Policies

NOMS 2022 IEEE

2022/4/3

Kim Hammar
Kim Hammar

H-Index: 2

Rolf Stadler
Rolf Stadler

H-Index: 17

Intrusion Prevention through Optimal Stopping

IEEE Transactions on Network and Service Management 2022

2021/10/30

Kim Hammar
Kim Hammar

H-Index: 2

Rolf Stadler
Rolf Stadler

H-Index: 17

Learning intrusion prevention policies through optimal stopping

2021/10/25

Kim Hammar
Kim Hammar

H-Index: 2

Rolf Stadler
Rolf Stadler

H-Index: 17

Finding effective security strategies through reinforcement learning and self-play

2020/11/2

Kim Hammar
Kim Hammar

H-Index: 2

Rolf Stadler
Rolf Stadler

H-Index: 17

Deep text classification of Instagram data using word embeddings and weak supervision

Web Intelligence

2020/1/1

See List of Professors in Kim Hammar University(Kungliga Tekniska högskolan)

Co-Authors

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