Tracing where IoT data are collected and aggregated

Abstract

The Internet of Things (IoT) offers the infrastructure of the information society. It hosts smart objects that automatically collect and exchange data of various kinds, directly gathered from sensors or generated by aggregations. Suitable coordination primitives and analysis mechanisms are in order to design and reason about IoT systems, and to intercept the implied technological shifts. We address some of these issues from a foundational point of view. To study them, we define IoT-LySa, a process calculus endowed with a static analysis that tracks the provenance and the manipulation of IoT data, and how they flow in the system. The results of the analysis can be used by a designer to check the behaviour of smart objects, in particular to verify non-functional properties, among which security. 1 https://www.theguardian.com/technology/2016/oct/22/smart-devices-too-dumb-to-fend-offcyber-attacks-say-experts LOGICAL METHODS lI N COMPUTER SCIENCE

Tool Supported Analysis of IoT

“…This may prevent us from statically determining safe approximants of aggregated data, because we cannot establish how many applications of aggregation functions are necessary by only inspecting the code. The analysis of [10] resorts therefore to tree grammars for keeping finite the abstract values and for improving the precision of the analysis in [9], where instead trees are cut at a fixed depth.…”

“…Indeed, one can inspect the component κ and see if a secret value flows in clear on the network. Other policies are also checked in [10].…”

“…In order to experiment on the CFA, we had to adapt the one in [9,10], so as to take into account the new constructs for the external choice mentioned above. In particular, our extensions help in establishing a finer relation between the program points where a message is sent and where it is received.…”

“…To keep the representation of abstract values finite (and get rid of their unknown depth), we use here regular tree grammars, cf. [10]. For saving space, the entries in Figure 4 are the start symbols of the relevant tree grammars, while their productions are in the lower part of the figure.…”

A process calculus approach to correctness enforcement of PLCs (full version)

“…The goal of the paper is to verify the effectiveness of a process calculus approach to formalise runtime enforcement of specification compliance in networks of PLCs injected with colluding malware that may forge/drop both actuator commands and inter-controller communications 3 . Process calculi represent a successful and widespread formal approach in concurrency theory relying on a variety of behavioural equivalences (e.g., trace equivalence and bisimilarity) for studying complex systems, such as distributed migrating objects [22], IoT systems [12,6,13] and cyber-physical systems [16], and used in many areas, including verification of security protocols [1,18] and security analysis of cyber-physical attacks [15]. On the other hand, runtime enforcement [26,17,8] is a powerful verification/validation technique aiming at correcting possibly-incorrect executions of a system-under-scrutiny (SuS) via a kind of monitor that acts as a proxy between the SuS and its environment.…”