A Holistic Systems Security Approach Featuring Thin Secure Elements for Resilient IoT Deployments

Abstract

IoT systems differ from traditional Internet systems in that they are different in scale, footprint, power requirements, cost and security concerns that are often overlooked. IoT systems inherently present different fail-safe capabilities than traditional computing environments while their threat landscapes constantly evolve. Further, IoT devices have limited collective security measures in place. Therefore, there is a need for different approaches in threat assessments to incorporate the interdependencies between different IoT devices. In this paper, we run through the design cycle to provide a security-focused approach to the design of IoT systems using a use case, namely, an intelligent solar-panel project called Daedalus. We utilise STRIDE/DREAD approaches to identify vulnerabilities using a thin secure element that is an embedded, tamper proof microprocessor chip that allows the storage and processing of sensitive data. It benefits from low power demand and small footprint as a crypto processor as well as is compatible with IoT requirements. Subsequently, a key agreement based on an asymmetric cryptographic scheme, namely B-SPEKE was used to validate and authenticate the source. We find that end-to-end and independent stand-alone procedures used for validation and encryption of the source data originating from the solar panel are cost-effective in that the validation is carried out once and not several times in the chain as is often the case. The threat model proved useful not so much as a panacea for all threats but provided the framework for the consideration of known threats, and therefore appropriate mitigation plans to be deployed.

A Formal Verification of a Reputation Multi-Factor Authentication Mechanism for Constrained Devices and Low-Power Wide-Area Network Using Temporal Logic

“…This is an acronym for damage, reproducibility, exploitability, affect users, and discoverability [ 65 , 66 ], which are the categorizations used to quantify risk in this methodology. Furthermore, such a methodology can be viewed as a way of measuring the vulnerability risk associated with each associated threat [ 67 ] through the use of numerical values. Additionally, it is observed that each of the five categories is evaluated from 0 to 3, where zero is the absence of risk and three is the highest value (a more detailed quantification can be seen in the Table 4 ) since using this table helps reduce the subjectivity inherent to DREAD, which has been considered a drawback of this method.…”

Enabling Security Services in Socially Assistive Robot Scenarios for Healthcare Applications

“…On one hand, lightweight, low-power security algorithms were proposed [ 25 ]. On the other hand, there is a novel practice to design devices with built-in secure elements [ 26 ], following the hardware-based security approach [ 27 ]. Another manufacturing-based solution to protect against physical cloning implies the use of physical, unclonable functions [ 22 , 28 ] that assigns the device a unique fingerprint.…”

Hardware-Based Methods for Electronic Device Protection against Invasive and Non-Invasive Attacks

“…By analyzing information from physical side-channels such as power consumption, timing or electromagnetic emissions, even mathematically secure cryptographic algorithms can be effectively compromised. The relevance and necessity of hardware device protection [10] are further underscored by standards that define required levels of physical protection for specific classes and types of devices. Some notable standards that encompass hardware protection include Common Criteria, TEMPEST, FIPS, IEEE and IEC CISPR, to name a few.…”