The Internet of Things (IoT) is revolutionizing society by connect-
ing people and devices seamlessly and providing enhanced user
experience and functionalities. However, the unique properties of
IoT networks, such as heterogeneity and non-standardized protocol,
have created critical security holes and network mismanagement.
We propose a new measurement tool for IoT network data to aid
in analyzing and classifying such network traffic. We use evidence
from both security and machine learning research, which suggests
that the complexity of a dataset can be used as a metric to determine
the trustworthiness of data. We test the complexity of IoT networks
using Intrinsic Dimensionality (ID), a theoretical complexity mea-
surement based on the observation that a few variables can often
describe high dimensional datasets. We use ID to evaluate four mod-
ern IoT network datasets empirically, showing that, for network
and device-level data generated using IoT methodologies, the ID
of the data fits into a low dimensional representation; this makes
such data amenable to the use of machine learning algorithms for
anomaly detection.
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A Robust, Low-Cost and Secure Authentication Scheme for IoT Applications
The edge devices connected to the Internet of Things (IoT) infrastructures are increasingly susceptible to piracy. These pirated edge devices pose a serious threat to security, as an adversary can get access to the private network through these non-authentic devices. It is necessary to authenticate an edge device over an unsecured channel to safeguard the network from being infiltrated through these fake devices. The implementation of security features demands extensive computational power and a large hardware/software overhead, both of which are difficult to satisfy because of inherent resource limitation in the IoT edge devices. This paper presents a low-cost authentication protocol for IoT edge devices that exploits power-up states of built-in SRAM for device fingerprint generations. Unclonable ID generated from the on-chip SRAM could be unreliable, and to circumvent this issue, we propose a novel ID matching scheme that alleviates the need for enhancing the reliability of the IDs generated from on-chip SRAMs. Security and different attack analysis show that the probability of impersonating an edge device by an adversary is insignificant. The protocol is implemented using a commercial microcontroller, which requires a small code overhead. However, no modification of device hardware is necessary.
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- Award ID(s):
- 1755733
- PAR ID:
- 10220224
- Date Published:
- Journal Name:
- Cryptography
- Volume:
- 4
- Issue:
- 1
- ISSN:
- 2410-387X
- Page Range / eLocation ID:
- 8
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/cryptography4010008
