Architecture-Based Graceful Degradation for Cybersecurity

Successful attacks are nearly inevitable as sophisticated threat actors are committed to inflicting damage, leaving digital and physical destruction in their wakes. As defenders recognize the inevitability of successful attacks, they must change their defense paradigms from only preventing attacks to also weathering the attacks that penetrate first-line defenses. Instead, the systems’ abilities to provide functionality should be minimally disrupted while simultaneously containing an attacker. The engineering challenge is to build and operate systems that are resilient to attack, able to adapt to trade off some functionality to preserve trust in more-critical functionality. We refer to this concept as graceful degradation. Defenders would be in a far better position to address the increasingly dire situation confronting them if they had a method and tool to support graceful degradation. However, this requires the ability to reason despite uncertainties at architecture and design time and at run time. Automation can be supported by formal modeling of systems, but it must not be labor-intensive. We propose and develop an approach that directly addresses these challenges. We can architect and operate systems that are better able to weather attacks by automating the evaluation of systems’ security properties to enable effective automated graceful degradation of systems in the presence of uncertainty through an approach of formally modeling systems and system behavior at an architectural level of abstraction to explore hypothetical attacks and the systems’ abilities to respond. We describe our approach and provide tooling to demonstrate our concept.

Institutions

Publication Details

Journal
KiltHub Repository
Published
2025-01-01
DOI
https://doi.org/10.1184/r1/29315717
Primary Topic
Pasture and Agricultural Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Architecture-Based Graceful Degradation for Cybersecurity

KiltHub Repository
Pasture and Agricultural Systems
article

Architecture-Based Graceful Degradation for Cybersecurity

article en

Abstract

Successful attacks are nearly inevitable as sophisticated threat actors are committed to inflicting damage, leaving digital and physical destruction in their wakes. As defenders recognize the inevitability of successful attacks, they must change their defense paradigms from only preventing attacks to also weathering the attacks that penetrate first-line defenses. Instead, the systems’ abilities to provide functionality should be minimally disrupted while simultaneously containing an attacker. The engineering challenge is to build and operate systems that are resilient to attack, able to adapt to trade off some functionality to preserve trust in more-critical functionality. We refer to this concept as graceful degradation. Defenders would be in a far better position to address the increasingly dire situation confronting them if they had a method and tool to support graceful degradation. However, this requires the ability to reason despite uncertainties at architecture and design time and at run time. Automation can be supported by formal modeling of systems, but it must not be labor-intensive. We propose and develop an approach that directly addresses these challenges. We can architect and operate systems that are better able to weather attacks by automating the evaluation of systems’ security properties to enable effective automated graceful degradation of systems in the presence of uncertainty through an approach of formally modeling systems and system behavior at an architectural level of abstraction to explore hypothetical attacks and the systems’ abilities to respond. We describe our approach and provide tooling to demonstrate our concept.

KiltHub Repository
Carnegie Mellon University (US)
Openalex Percentile: Top 44%
Pasture and Agricultural Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.