  The rise of IoT has made possible the development of %increasingly
personalized services, like industrial services that often deal with massive
amounts of data. However, as IoT grows, its threats are even greater. The false
data injection (FDI) attack stands out as being one of the most harmful to data
networks like IoT. The majority of current systems to handle this attack do not
take into account the data validation, especially on the data clustering
service. This work introduces CONFINIT, an intrusion detection system against
FDI attacks on the data dissemination service into dense IoT. It combines
watchdog surveillance and collaborative consensus among IoT devices for getting
the swift detection of attackers. CONFINIT was evaluated in the NS-3 simulator
into a dense industrial IoT and it has gotten detection rates of 99%, 3.2% of
false negative and 3.6% of false positive rates, adding up to 35% in clustering
without FDI attackers.
