Many solutions have been proposed to curb unexpected behavior of automation apps installed on programmable IoT platforms by enforcing safety policies at runtime. However, all prior work addresses a weaker version of the actual problem due to a simpler, unrealistic threat model. These solutions are not general enough as they are heavily dependent on the installed apps and catered to specific IoT platforms. Here, we address a stronger version of the problem via a realistic threat model, where (i) undesired cyber actions can come from not only automation platform backends (e.g., SmartThings) but also close-sourced third-party services (e.g., IFTTT), and (ii) physical actions (e.g., user interactions) on devices can move the IoT system to an undesirable state. We propose a runtime mechanism, dubbed Maverick, which employs an app-independent, platform-agnostic mediator to enforce policies against all undesired cyber actions and applies corrective-actions to bring the IoT system back to a safe state from an unsafe state transition. Maverick is equipped with a policy language capable of expressing rich temporal invariants and an automated toolchain that includes a policy synthesizer and a policy analyzer for user assistance. We implemented Maverick in a prototype and showed its efficacy in both physical and virtual testbeds, incurring minimal overhead.

In this paper, we perform the first multifaceted measurement study to investigate the widespread insecure practices employed by tertiary education institutes (TEIs) around the globe when offering WPA2-Enterprise Wi-Fi services. The security of such services critically hinges on two aspects: (1) the connection configuration on the client-side; and (2) the TLS setup on the authentication servers. Weaknesses in either can leave users susceptible to credential theft. Typically, TEIs prescribe to their users either manual instructions or pre-configured profiles (e.g., eduroam CAT). For studying the security of configurations, we present a framework in which each configuration is mapped to an abstract security label drawn from a strict partially ordered set. We first used this framework to evaluate the configurations supported by the user interfaces (UIs) of mainstream operating systems (OSs), and discovered many design weaknesses. We then considered 7045 TEIs in 54 countries/regions, and collected 7275 configuration instructions from 2061 TEIs. Our analysis showed that majority of these instructions lead to insecure configurations, and nearly 86% of those TEIs can suffer from credential thefts on at least one OS. We also analyzed a large corpus of pre-configured eduroam CAT profiles and discovered several misconfiguration issues that can negatively impact security. Finally, we evaluated the TLS parameters used by authentication servers of thousands of TEIs and discovered perilous practices, such as the use of expired certificates, deprecated versions of TLS, weak signature algorithms, and suspected cases of private key reuse among TEIs. Our long list of findings have been responsibly disclosed to the relevant stakeholders, many of which have already been positively acknowledged.

This paper focuses on developing an automatic, black-box testing approach called Morpheus to check the non-compliance of libraries implementing PKCS#1-v1.5 signature verification with the PKCS#1-v1.5 standard. Non-compliance can not only make implementations vulnerable to Bleichenbacher-style RSA signature forgery attacks but also can induce interoperability issues. For checking non-compliance, Morpheus adaptively generates interesting test cases and then takes advantage of an oracle, a formally proven correct implementation of PKCS#1-v1.5 signature standard, to detect non-compliance in an implementation under test. We have used Morpheus to test 45 implementations of PKCS#1-v1.5 signature verification and discovered that 6 of them are susceptible to variants of the Bleichenbacher-style low public exponent RSA signature forgery attack, 1 implementation has a buffer overflow, 33 implementations have incompatibility issues, and 8 implementations have minor leniencies. Our findings have been responsibly disclosed and positively acknowledged by the developers.

We consider the problem of multiple robots that must cooperate within a shared environment, but which wish to limit the information they disclose during their coordination efforts. Specifically, we examine the problems of privacy-preserving rendezvous and persistent monitoring. In the former, the robots construct a joint plan to have them meet, without either knowing beforehand where or when the meeting will occur. In the latter, multiple robots dynamically cover a region of space-they plan collective motions which are collision-free but with the assurance that agents remain ignorant of the paths of others. Accordingly, the tasks are sort of inverses in that the robots must collectively determine whether their joint paths collide or not, then, using this, achieve their collective task. Other than what is learned by the outcome of the joint-collision determination, the robots possess no details of the other paths. Our approach builds on garbled circuits and homomorphic encryption to realize basic secure path intersection primitives. We present algorithms, a software implementation, and a physical experiment on mobile robots to test the practical feasibility of our approach. We believe that these ideas provide a valuable direction for adoption in small Unmanned Systems belonging to different stakeholders.