Abstract
Advanced persistent threat (APT) attacks are arguably
among the most serious security hazards of computer
systems and information networks (information
infrastructure, II) supporting e.g. critical
infrastructures (CI). Due
to their nature, APT's are usually very difficult to
detect, and even if detected, difficult to recover from.
Further,
new forms of APT are probably being developed all the
time, with considerable resources. Thus, the defenders of
the infrastructure - typically, the personnel of a
security operating center (SOC) - face a formidable task
in
mitigation and need assistance. Existing incident
management systems generally do not provide active
mitigation
assistance. If mitigation-related information is only
available in a passive form (e.g. as part of help files),
the
defenders are unlikely to find the needed information or
even search for it in a meaningful way. Thus, there is a
need for active decision support system that provides the
defenders with advice on how to proceed with
mitigation, given the current phase in the attack
lifecycle and various kinds of information available on
the II, CI,
and APT attacks.
We propose a framework for active mitigation support
against APTs to SOC personnel. Operational information is
collected, and, combined with information about the
structure and functioning of the II and CI, and possible
threats,
used to provide advice to the defenders on what
mitigation actions to take in different phases of defense
lifecycle
(preparation, detection, resolution and closure). The
framework uses ontologies for knowledge representation,
and expert systems for selecting appropriate mitigation
actions for a given situation. Altogether, the actions
constitute a mitigation process that covers the whole
defense lifecycle. We briefly describe a demonstration
prototype constructed for the resolution phase, and its
use as a part of a larger demonstration covering the
defense
of a banking infrastructure against APT. We propose that
active mitigation support could be a useful means of the
management of information security risks more generally,
and could also provide a basis for the automation of
mitigation against information security risks.
Original language | English |
---|---|
Title of host publication | SRA Nordic 2017 Abstracts |
Publisher | Aalto University |
Publication status | Published - 2017 |
MoE publication type | Not Eligible |
Event | Society for Risk Analysis (SRA) Nordic Chapter Conference, RISK 2017 - Espoo, Finland Duration: 2 Nov 2017 → 3 Nov 2017 https://blogs.aalto.fi/risk2017/ (Web page) |
Conference
Conference | Society for Risk Analysis (SRA) Nordic Chapter Conference, RISK 2017 |
---|---|
Abbreviated title | RISK 2017 |
Country/Territory | Finland |
City | Espoo |
Period | 2/11/17 → 3/11/17 |
Internet address |
|
Keywords
- artificial intelligence
- decision support
- expert systems
- information security
- mitigation
- network security