Graphical Models for Security
6th International Workshop, GraMSec 2019, Hoboken, NJ, USA, June 24, 2019, Revised Papers
Published on 28. November 2019
Book
Paperback/Softback
IX, 221 pages
978-3-030-36536-3 (ISBN)
Description
This book constitutes revised papers from the 6th International Workshop on Graphical Models for Security, GraMSec 2019, held in Hoboken, NJ, USA, in June 2019.
The 8 full papers presented in this volume were carefully reviewed and selected from 15 submissions. The book also contains two invited talk. The contributions deal with the latest research and developments on graphical models for security.
More details
Series
Edition
2019 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
115 s/w Abbildungen, 73 farbige Abbildungen
IX, 221 p. 188 illus., 73 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 13 mm
Weight
359 gr
ISBN-13
978-3-030-36536-3 (9783030365363)
DOI
10.1007/978-3-030-36537-0
Schweitzer Classification
Other editions
Additional editions
Massimiliano Albanese | Ross Horne | Christian W. Probst
Graphical Models for Security
6th International Workshop, GraMSec 2019, Hoboken, NJ, USA, June 24, 2019, Revised Papers
E-Book
11/2019
Springer
€53.49
Available for download
Content
Invited Papers.-
Graph Models in Tracking Behaviors for Cyber-Security.- Attack tree series: a case for dynamic attack tree analysis.-
Attack Trees.-
Attack trees: a notion of missing attacks.- Optimizing System Architecture Cost and Security Countermeasures.- Security Analysis of IoT systems using Attack Trees.- Attackdefense trees for abusing optical power meters: A case study and the OSEAD tool experience report.-
Risk Management and Attack Graphs.-
Quantifying and Analyzing Information Security Risk from Incident Data.- Poster Support for an Obeya-like Risk Management Approach.- Conceptual Abstraction of Attack Graphs - a Use Case of securiCAD.- High-level Automatic Event Detection and User Classi?cation in a Social Network Context.