null
(Ed.)
Internet of Things (IoT) devices, web
browsers, phones, and even cars may be fingerprinted for
tracking, and their connections routed through or to malicious
entities. When IoT devices interact with a remote service, the
integrity or authentication of that service is not guaranteed. IoT
and other edge devices could be subject to man-in-the-middle
(MiTM) attacks, with IoT devices attempting to connect to remote
services. It is also straight-forward to use phishing or pharming to
convince a user to accept a connection to a potentially malicious
unfamiliar device. These risks could be mitigated by leveraging
information on the edge of the network about the path to and
destination of a connection. In this work we sample packets,
then use packet analysis and local history to identify risky or
suspicious connections. In contrast to other machine learning and
big data approaches, the use of local data enables risk detection
without loss of privacy.
more »
« less