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Featured researches published by Arsalan Mosenia.


IEEE Transactions on Emerging Topics in Computing | 2017

A Comprehensive Study of Security of Internet-of-Things

Arsalan Mosenia; Niraj K. Jha

Internet of Things (IoT), also referred to as the Internet of Objects, is envisioned as a transformative approach for providing numerous services. Compact smart devices constitute an essential part of IoT. They range widely in use, size, energy capacity, and computation power. However, the integration of these smart things into the standard Internet introduces several security challenges because the majority of Internet technologies and communication protocols were not designed to support IoT. Moreover, commercialization of IoT has led to public security concerns, including personal privacy issues, threat of cyber attacks, and organized crime. In order to provide a guideline for those who want to investigate IoT security and contribute to its improvement, this survey attempts to provide a comprehensive list of vulnerabilities and countermeasures against them on the edge-side layer of IoT, which consists of three levels: (i) edge nodes, (ii) communication, and (iii) edge computing. To achieve this goal, we first briefly describe three widely-known IoT reference models and define security in the context of IoT. Second, we discuss the possible applications of IoT and potential motivations of the attackers who target this new paradigm. Third, we discuss different attacks and threats. Fourth, we describe possible countermeasures against these attacks. Finally, we introduce two emerging security challenges not yet explained in detail in previous literature.


IEEE Transactions on Multi-Scale Computing Systems | 2017

Wearable Medical Sensor-Based System Design: A Survey

Arsalan Mosenia; Susmita Sur-Kolay; Anand Raghunathan; Niraj K. Jha

Wearable medical sensors (WMSs) are garnering ever-increasing attention from both the scientific community and the industry. Driven by technological advances in sensing, wireless communication, and machine learning, WMS-based systems have begun transforming our daily lives. Although WMSs were initially developed to enable low-cost solutions for continuous health monitoring, the applications of WMS-based systems now range far beyond health care. Several research efforts have proposed the use of such systems in diverse application domains, e.g., education, human-computer interaction, and security. Even though the number of such research studies has grown drastically in the last few years, the potential challenges associated with their design, development, and implementation are neither well-studied nor well-recognized. This article discusses various services, applications, and systems that have been developed based on WMSs and sheds light on their design goals and challenges. We first provide a brief history of WMSs and discuss how their market is growing. We then discuss the scope of applications of WMS-based systems. Next, we describe the architecture of a typical WMS-based system and the components that constitute such a system, and their limitations. Thereafter, we suggest a list of desirable design goals that WMS-based systems should satisfy. Finally, we discuss various research directions related to WMSs and how previous research studies have attempted to address the limitations of the components used in WMS-based systems and satisfy the desirable design goals.


IEEE Transactions on Computers | 2017

CABA: Continuous Authentication Based on BioAura

Arsalan Mosenia; Susmita Sur-Kolay; Anand Raghunathan; Niraj K. Jha

Most computer systems authenticate users only once at the time of initial login, which can lead to security concerns. Continuous authentication has been explored as an approach for alleviating such concerns. Previous methods for continuous authentication primarily use biometrics, e.g., fingerprint and face recognition, or behaviometrics, e.g., key stroke patterns. We describe CABA, a novel continuous authentication system that is inspired by and leverages the emergence of sensors for pervasive and continuous health monitoring. CABA authenticates users based on their BioAura, an ensemble of biomedical signal streams that can be collected continuously and non-invasively using wearable medical devices. While each such signal may not be highly discriminative by itself, we demonstrate that a collection of such signals, along with robust machine learning, can provide high accuracy levels. We demonstrate the feasibility of CABA through analysis of traces from the MIMIC-II dataset. We propose various applications of CABA, and describe how it can be extended to user identification and adaptive access control authorization. Finally, we discuss possible attacks on the proposed scheme and suggest corresponding countermeasures.


arXiv: Cryptography and Security | 2018

PinMe: Tracking a Smartphone User around the World

Arsalan Mosenia; Xiaoliang Dai; Prateek Mittal; Niraj K. Jha

With the pervasive use of smartphones that sense, collect, and process valuable information about the environment, ensuring location privacy has become one of the most important concerns in the modern age. A few recent research studies discuss the feasibility of processing sensory data gathered by a smartphone to locate the phone’s owner, even when the user does not intend to share his location information, e.g., when the user has turned off the Global Positioning System (GPS) on the device. Previous research efforts rely on at least one of the two following fundamental requirements, which impose significant limitations on the adversary: (i) the attacker must accurately know either the user’s initial location or the set of routes through which the user travels and/or (ii) the attacker must measure a set of features, e.g., device acceleration, for different potential routes in advance and construct a training dataset. In this paper, we demonstrate that neither of the above-mentioned requirements is essential for compromising the user’s location privacy. We describe PinMe, a novel user-location mechanism that exploits non-sensory/sensory data stored on the smartphone, e.g., the environment’s air pressure and device’s timezone, along with publicly-available auxiliary information, e.g., elevation maps, to estimate the user’s location when all location services, e.g., GPS, are turned off. Unlike previously-proposed attacks, PinMe neither requires any prior knowledge about the user nor a training dataset on specific routes. We demonstrate that PinMe can accurately estimate the user’s location during four activities (walking, traveling on a train, driving, and traveling on a plane). We also suggest several defenses against the proposed attack.


arXiv: Computers and Society | 2018

ProCMotive: Bringing Programmability and Connectivity into Isolated Vehicles

Arsalan Mosenia; Jad F. Bechara; Tao Zhang; Prateek Mittal; Mung Chiang

In recent years, numerous vehicular technologies, e.g., cruise control and steering assistant, have been proposed and deployed to improve the driving experience, passenger safety, and vehicle performance. Despite the existence of several novel vehicular applications in the literature, there still exists a significant gap between resources needed for a variety of vehicular (in particular, data-dominant, latency-sensitive, and computationally-heavy) applications and the capabilities of already-in-market vehicles. To address this gap, different smartphone-/Cloud-based approaches have been proposed that utilize the external computational/storage resources to enable new applications. However, their acceptance and application domain are still very limited due to programability, wireless connectivity, and performance limitations, along with several security/privacy concerns. In this paper, we present a novel architecture that can potentially enable rapid development of various vehicular applications while addressing shortcomings of smartphone-/Cloud-based approaches. The architecture is formed around a core component, called SmartCore, a privacy/security-friendly programmable dongle that brings general-purpose computational and storage resources to the vehicle and hosts in-vehicle applications. Based on the proposed architecture, we develop an application development framework for vehicles, that we call ProCMotive. ProCMotive enables developers to build customized vehicular applications along the Cloud-to-edge continuum, i.e., different functions of an application can be distributed across SmartCore, the users personal devices, and the Cloud. To highlight potential benefits that the framework provides, we design and develop two different vehicular applications based on ProCMotive, namely, Amber Response and Insurance Monitor.


Proceedings of the 2018 Workshop on Attacks and Solutions in Hardware Security - ASHES '18 | 2018

Acoustic Denial of Service Attacks on Hard Disk Drives

Mohammad Shahrad; Arsalan Mosenia; Liwei Song; Mung Chiang; David Wentzlaff; Prateek Mittal

Bridging concepts from information security and resonance theory, we propose a novel denial of service attack against hard disk drives (HDDs). In this attack, acoustic signals are used to cause rotational vibrations in HDD platters in an attempt to create failures in read/write operations, ultimately halting the correct operation of HDDs. We perform a comprehensive examination of multiple HDDs to characterize the attack and show the feasibility of the attack in two real-world systems, namely, surveillance devices and personal computers. Our attack highlights an overlooked security vulnerability of HDDs, introducing a new threat that can potentially endanger the security of numerous systems.


arXiv: Cryptography and Security | 2018

Rogue Signs: Deceiving Traffic Sign Recognition with Malicious Ads and Logos.

Chawin Sitawarin; Arjun Nitin Bhagoji; Arsalan Mosenia; Prateek Mittal; Mung Chiang


2017 IEEE Fog World Congress (FWC) | 2017

OpenFog security requirements and approaches

Bridget A. Martin; Frank Michaud; Don Banks; Arsalan Mosenia; Riaz Zolfonoon; Susanto Irwan; Sven Schrecker; John K. Zao


arXiv: Cryptography and Security | 2018

DARTS: Deceiving Autonomous Cars with Toxic Signs.

Chawin Sitawarin; Arjun Nitin Bhagoji; Arsalan Mosenia; Mung Chiang; Prateek Mittal


IEEE Transactions on Multi-Scale Computing Systems | 2018

OpSecure: A Secure Unidirectional Optical Channel for Implantable Medical Devices

Arsalan Mosenia; Niraj K. Jha

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Susmita Sur-Kolay

Indian Statistical Institute

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