Search for: All records

Internet-of-Things (IoT) devices are vulnerable to malware and require new mitigation techniques due to their limited resources. To that end, previous research has used periodic Remote Attestation (RA) or Traffic Analysis (T A) to detect malware in IoT devices. However, RA is expensive, and TA only raises suspicion without confirming malware presence. To solve this, we design MADEA, the first system that blends RA and T A to offer a comprehensive approach to malware detection for the IoT ecosystem. T A builds profiles of expected packet traces during benign operations of each device and then uses them to detect malware from network traffic in realtime. RA confirms the presence or absence of malware on the device. MADEA achieves 100% true positive rate. It also outperforms other approaches with 160× faster detection time. Finally, without MADEA, effective periodic RA can consume at least ∼14× the amount of energy that a device needs in one hour. 

Internet of Things (IoT) devices are becoming increasingly commonplace in both public and semi-private settings. Currently, most such devices lack mechanisms that allow for their discovery by casual (nearby) users who are not owners or operators. However, these users are potentially being sensed, and/or actuated upon, by these devices, without their knowledge or consent. This triggers privacy, security, and safety issues. To address this problem, some recent work explored device transparency in the IoT ecosystem. The intuitive approach is for each device to periodically and securely broadcast (announce) its presence and capabilities to all nearby users. While effective, when no new users are present, this 𝑃𝑢𝑠ℎ-based approach generates a substantial amount of unnecessary network traffic and needlessly interferes with normal device operation. In this work, we construct DB-PAISA which addresses these issues via a 𝑃𝑢𝑙𝑙-based method, whereby devices reveal their presence and capabilities only upon explicit user request. Each device guarantees a secure timely response (even if fully compromised by malware) based on a small active Root-of-Trust (RoT). DB-PAISA requires no hardware modifications and is suitable for a range of current IoT devices. To demonstrate its feasibility and practicality, we built a fully functional and publicly available prototype. It is implemented atop a commodity MCU (NXP LCP55S69) and operates in tandem with a smartphone-based app. Using this prototype, we evaluate energy consumption and other performance factors. 

Several prominent privacy regulation (e.g., CCPA and GDPR) require service providers to let consumers request access to, correct, or delete, their personal data. Compliance necessitates verification of consumer identity. This is not a problem for consumers who already have an account with a service provider since they can authenticate themselves via a successful account log-in. However, there are no such methods for accountless consumers, even though service providers routinely collect data about casual consumers, i.e., those without accounts. Currently, in order to access their collected data, accountless consumers are asked to provide Personally Identifiable Information (PII) to service providers, which is privacy-invasive. To address this problem, we propose PIVA: Privacy-Preserving Identity Verification for Accountless Users, a technique based on Private List Intersection (PLI) and its variants. First, we introduce PLI, a close relative of private set intersection (PSI), a well-known cryptographic primitive that allows two or more mutually suspicious parties to compute the intersection of their private input sets. PLI takes advantage of the (ordered and fixed) list structure of each party’s private set. As a result, PLI is more efficient than PSI. We also explore PLI variants: PLI-cardinality (PLI-CA), threshold-PLI (t-PLI), and threshold-PLI-cardinality (t-PLI-CA), all of which yield less information than PLI. These variants are progressively better suited for addressing the accountless consumer authentication problem. We prototype and compare its performance against techniques based on regular PSI and garbled circuits (GCs). Results show that proposed PLI and PLI-CA constructions are more efficient than GC-based techniques, in terms of both computation and communication overheads. While GC-based t-PLI and t-PLI-CA execute faster, proposed constructs greatly outperform the former in terms of bandwidth, e.g., our t-PLI protocol consumes less bandwidth. We also show that proposed protocols can be made secure against malicious adversaries, with only moderate increases in overhead. These variants outperform their GC-based counterparts by at least one order of magnitude.