The Internet of Things: Secure Distributed Inference

TL;DR

This paper discusses algorithms for secure distributed inference in IoT, addressing security challenges due to the distributed nature of devices and potential data compromises.

Contribution

It provides an overview of algorithms designed to enhance security and trustworthiness in IoT data analytics through distributed inference methods.

Findings

Highlights the importance of resilient analytics in IoT security

Reviews algorithms for secure distributed inference

Emphasizes reactive countermeasures like intrusion detection

Abstract

The growth in the number of devices connected to the Internet of Things (IoT) poses major challenges in security. The integrity and trustworthiness of data and data analytics are increasingly important concerns in IoT applications. These are compounded by the highly distributed nature of IoT devices, making it infeasible to prevent attacks and intrusions on all data sources. Adversaries may hijack devices and compromise their data. As a result, reactive countermeasures, such as intrusion detection and resilient analytics, become vital components of security. This paper overviews algorithms for secure distributed inference in IoT.