Soteria: Automated IoT Safety and Security Analysis (1805.08876v1)

Abstract: Broadly defined as the Internet of Things (IoT), the growth of commodity devices that integrate physical processes with digital systems have changed the way we live, play and work. Yet existing IoT platforms cannot evaluate whether an IoT app or environment is safe, secure, and operates correctly. In this paper, we present Soteria, a static analysis system for validating whether an IoT app or IoT environment (collection of apps working in concert) adheres to identified safety, security, and functional properties. Soteria operates in three phases; (a) translation of platform-specific IoT source code into an intermediate representation (IR), (b) extracting a state model from the IR, (c) applying model checking to verify desired properties. We evaluate Soteria on 65 SmartThings market apps through 35 properties and find nine (14%) individual apps violate ten (29%) properties. Further, our study of combined app environments uncovered eleven property violations not exhibited in the isolated apps. Lastly, we demonstrate Soteria on MalIoT, a novel open-source test suite containing 17 apps with 20 unique violations.

• The paper introduces an automated framework, Soteria, that detects violations of safety, security, and functional properties in IoT applications.
• It implements a three-phase process—translating source code to an intermediate representation, extracting a state model, and applying model checking for property verification.
• The study reveals that both individual and inter-app analyses uncover critical property violations, underscoring the need for proactive security measures in IoT ecosystems.

Overview of "Soteria: Automated IoT Safety and Security Analysis"

The paper presents Soteria, an automated framework aimed at enhancing the safety and security of Internet of Things (IoT) applications. It addresses the lack of comprehensive validation tools that ensure IoT applications comply with essential safety, security, and functional properties. The research introduces a static analysis approach, primarily focusing on IoT applications within the SmartThings platform, to systematically identify property violations in both individual and multi-application environments.

Methodological Contributions

Soteria operates through a structured three-phase process:

1. Intermediate Representation Translation: The IoT app’s platform-specific source code is converted into an intermediate representation (IR). This IR abstracts the application’s lifecycle, encompassing aspects such as entry points and event handler methods. The IR facilitates a detailed static analysis of the app's code.
2. State Model Extraction: From the IR, Soteria extracts a state model, capturing the app's states and transitions. This model reflects the app’s behavior concerning its interactions with IoT devices and the external environment.
3. Model Checking: Utilizing techniques from model checking, the framework verifies whether the app or the collective apportionment adheres to predefined properties, expressed in temporal logic. These properties encapsulate safety, security, and functional requirements pertinent to IoT ecosystems.

Key Findings

The implementation of Soteria on 65 IoT apps from the SmartThings platform revealed critical insights:

• 14% of individual apps violated 29% of the specified properties.
• Moreover, within multi-app environments, the framework discovered additional property violations not visible when apps were analyzed in isolation.

These findings underscore the complexity and interdependencies of IoT applications, where seemingly innocuous apps can interact to produce unsafe or undesired outcomes.

Implications and Future Directions

Soteria significantly contributes to the field of IoT security by providing a systematic methodology to detect unsafe states and interactions. Practically, this work suggests an urgent need for IoT platforms to incorporate automated verification tools to preemptively address potential security and safety risks. Theoretically, the research highlights the utility of formal verification techniques, like model checking, within the parameterized and dynamic environments typical of IoT applications.

Future research could extend the Soteria framework beyond the SmartThings platform, adapting it to diverse IoT domains such as healthcare, agriculture, and automotive industries. Further exploration into dynamic analysis techniques might also address current limitations, such as the handling of dynamic device permissions and configurations.

Overall, this work lays a foundational approach for proactive security management in IoT ecosystems, setting a precedent for both academic inquiry and practical application in safeguarding digitally integrated environments.