Using Smartphones to Enable Low-Cost Secure Consumer IoT Devices

Abstract

This paper proposes a solution for low-cost consumer IoT devices to employ end-to-end security without requiring additional hardware. Manufacturers of consumer IoT devices often sacrifice security in favour of features, user-friendliness, time to market or cost, in order to stay ahead of their competitors. However, this is unwise, as demonstrated by recent hacks on consumer IoT devices. Low-cost embedded devices struggle to create suitable entropy for key generation; on the other hand, smartphones are both abundant and have multiple sources of entropy for strong key generation. The proposed architecture takes advantage of these properties and offloads key generation and transfer to the user's smartphone, removing the need for constrained IoT devices to perform public key infrastructure and generate symmetric keys. The authors implemented the design on a $1 general-purpose microcontroller and then analysed the performance. The design allows all communication to and from the device to be encrypted while being simple to setup, low-cost and responsive without any additional manufacturing cost. The architecture presents a general solution, which could be implemented on any microcontroller. Since the architecture does not require any additional hardware, it can be retroactively applied to deployed devices through a firmware update.

Smart-home anomaly detection using combination of in-home situation and user behavior

“…This method estimates the states of the home based on the sensed values and operating statuses of IoT devices. As with the proposed method, the estimation-based method calculated the b and α using Equations (5)(6)(7)(8)(9). We calculated the probability that the operation was legitimate by multiplying b to α and by summarizing them.…”

“…After training the model, when an event sequence, y, includes operations of the detection target device, the proposed method calculates the state probability α (T (y)−∆T ) (i) using Equations ( 7), (8), and (9). The proposed method calculates the probability of occurrence δ (T (y)−∆T ) (y) of the sequence y by multiplying the state probabilities, α (T (y)−∆T ) (i), by the behavior sequence probability, b ′ (i, y), as described in Equation ( 13):…”

“…Notably, it is very difficult to maintain the boundary security of IoT devices [8] because they employ many different communication protocols and connect to many different platforms. Moreover, proper boundary security would be exceedingly expensive [9].…”

Secure Decentralised Deployment of LoRaWAN Sensors

“…However, this creates a barrier requiring additional hardware which would increase the cost of the device. IoT devices are price sensitive, and even a small increase in cost deters consumers [15], [16]. Manufacturers also struggle to differentiate themselves based on security features so instead invest in more marketable features [17].…”