Modern cyber attacks have evolved considerably. The skill level required to conduct
a cyber attack is low. Computing power is cheap, targets are diverse and plentiful.
Point-and-click crimeware kits are widely circulated in the underground economy, while
source code for sophisticated malware such as Stuxnet is available for all to download
and repurpose. Despite decades of research into defensive techniques, such as firewalls,
intrusion detection systems, anti-virus, code auditing, etc, the quantity of successful
cyber attacks continues to increase, as does the number of vulnerabilities identified.
Measures to identify perpetrators, known as attribution, have existed for as long as there
have been cyber attacks. The most actively researched technical attribution techniques
involve the marking and logging of network packets. These techniques are performed
by network devices along the packet journey, which most often requires modification of
existing router hardware and/or software, or the inclusion of additional devices. These
modifications require wide-scale infrastructure changes that are not only complex and
costly, but invoke legal, ethical and governance issues. The usefulness of these techniques
is also often questioned, as attack actors use multiple stepping stones, often innocent
systems that have been compromised, to mask the true source. As such, this thesis
identifies that no publicly known previous work has been deployed on a wide-scale basis
in the Internet infrastructure.
This research investigates the use of an often overlooked tool for attribution: cyber de-
ception. The main contribution of this work is a significant advancement in the field of
deception and honeypots as technical attribution techniques. Specifically, the design and
implementation of two novel honeypot approaches; i) Deception Inside Credential Engine
(DICE), that uses policy and honeytokens to identify adversaries returning from different
origins and ii) Adaptive Honeynet Framework (AHFW), an introspection and adaptive
honeynet framework that uses actor-dependent triggers to modify the honeynet envi-
ronment, to engage the adversary, increasing the quantity and diversity of interactions.
The two approaches are based on a systematic review of the technical attribution litera-
ture that was used to derive a set of requirements for honeypots as technical attribution
techniques. Both approaches lead the way for further research in this field
