Paper
3 May 2018 IOT honeynet for military deception and indications and warnings
Peter J. Hanson, Lucas Truax, David D. Saranchak
Author Affiliations +
Abstract
Honeyman, named for the American Revolutionary War spy and source of disinformation, is an IoT distributed deception platform (DDP), aka “honeynet”, based approach to military deception and indications and warning (I&W) generation. While DDP approaches have evolved from single honeypots to complex network architectures and have resolved previous challenges associated with revealing a DDP’s signature or “fingerprint” including virtual device information, and therefore have become applicable for IoT uses, these approaches are still bounded in their application to cybersecurity purposes only. For example, data positioned as cyber-bait is meant only to draw in a cyber attacker but not to influence a strategic level of decision-making such as military or national security decisions. Additionally, monitoring within the DDP gathers data to model attackers’ cyber behavior and patterns for explicit purpose of identifying new offensive cyber techniques and thwarting new attacks. Honeyman combines a proxy military logistics and readiness reporting IoT comprised of a mixture of virtual and physical devices with non-cyber information operations for military deception and to stimulate nation-state adversary behavior within the DDP. A machine learning (ML)-based traffic analysis model leverages observations within the honeynet to forecast an adversary’s physical military activity thereby providing critical I&W. Further research is needed to optimize the combination of physical and virtual IoT devices for best deception performance, to evolve the tradecraft of dynamic cyber-bait, and to refine appropriate ML-based I&W models.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter J. Hanson, Lucas Truax, and David D. Saranchak "IOT honeynet for military deception and indications and warnings", Proc. SPIE 10643, Autonomous Systems: Sensors, Vehicles, Security, and the Internet of Everything, 106431A (3 May 2018); https://doi.org/10.1117/12.2305071
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Sensors

Data modeling

Telecommunications

Defense and security

Embedded systems

Systems modeling

Analytics

Back to Top