Encryption on the air : non-Invasive security for implantable medical devices

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 73-78).Modern implantable medical devices (IMDs) including pacemakers, cardiac defibrillators and nerve stimulators feature wireless connectivity that enables remote monitoring and post-implantation adjustment. However, recent work has demonstrated that flawed security tempers these medical benefits. In particular, an understandable lack of cryptographic mechanisms results in the IMD disclosing private data and being unable to distinguish authorized from unauthorized commands. In this thesis, we present IMD-Shield; a prototype defenses against a previously proposed suite of attacks on IMDs. IMD-Shield is an external entity that uses a new full dulpex radio design to secure transmissions to and from the IMD on the air wihtout incorporating the IMD itself. Because replacing the install base of wireless-enabled IMDs is infeasible, our system non-invasively enhances the security of unmodified IMDs. We implement and evaluate our mechanism against modern IMDs in a variety of attack scenarios and find that it effectively provides confidentiality for private data and shields the IMD from unauthorized commands.by Haitham Al-Hassanieh.S.M

Securing Deployed RFIDs by Randomizing the Modulation and the Channel

RFID cards are widely used today in sensitive applications such as access control, payment systems, and asset tracking. Past work shows that an eavesdropper snooping on the communication between a card and its legitimate reader can break their cryptographic protocol and obtain their secret keys. One solution for this problem is to install stronger cryptographic protocols on the cards. However, RFIDs' size, power, and cost limitations do not allow for conventional cryptographic protocols. Further, installing new protocols requires revoking billions of cards in consumers hands and facilities worldwide, which is costly and impractical. In this paper, we ask whether one can secure RFIDs from such attacks without revoking or changing the insecure cards. We propose LocRF, a solution that changes the signal used to read the RFID cards but does not require any changes to the cards themselves. LocRF introduces a new approach that randomizes the modulation of the RFID signal as well as the wireless channel. This design protects RFIDs from eavesdroppers even if they use multi-antenna MIMO receivers. We built a prototype of LocRF on software-defined radios and used it to secure the communication of off-the-shelf cards. Both our analysis and empirical evaluation demonstrate theeffectiveness of LocRF

SourceSync: A Distributed Wireless Architecture for Exploiting Sender Diversity

Diversity is an intrinsic property of wireless networks. Recent years have witnessed the emergence of many distributed protocols like ExOR, MORE, SOAR, SOFT, and MIXIT that exploit receiver diversity in 802.11-like networks. In contrast, the dual of receiver diversity, sender diversity, has remained largely elusive to such networks. This paper presents SourceSync, a distributed architecture for harnessing sender diversity. SourceSync enables concurrent senders to synchronize their transmissions to symbol boundaries, and cooperate to forward packets at higher data rates than they could have achieved by transmitting separately. The paper shows that SourceSync improves the performance of opportunistic routing protocols. Specifically, SourceSync allows all nodes that overhear a packet in a wireless mesh to simultaneously transmit it to their nexthops, in contrast to existing opportunistic routing protocols that are forced to pick a single forwarder from among the overhearing nodes. Such simultaneous transmission reduces bit errors and improves throughput. The paper also shows that SourceSync increases the throughput of 802.11 last hop diversity protocols by allowing multiple APs to transmit simultaneously to a client, thereby harnessing sender diversity. We have implemented SourceSync on the FPGA of an 802.11-like radio platform. We have also evaluated our system in an indoor wireless testbed, empirically showing its benefits.National Science Foundation (U.S.) (Award CNS-0831660)United States. Defense Advanced Research Projects Agency. Information Theory for Mobile Ad-Hoc Networks Progra

Nearly Optimal Sparse Fourier Transform

We consider the problem of computing the k-sparse approximation to the discrete Fourier transform of an n-dimensional signal. We show: * An O(k log n)-time randomized algorithm for the case where the input signal has at most k non-zero Fourier coefficients, and * An O(k log n log(n/k))-time randomized algorithm for general input signals. Both algorithms achieve o(n log n) time, and thus improve over the Fast Fourier Transform, for any k = o(n). They are the first known algorithms that satisfy this property. Also, if one assumes that the Fast Fourier Transform is optimal, the algorithm for the exactly k-sparse case is optimal for any k = n^{\Omega(1)}. We complement our algorithmic results by showing that any algorithm for computing the sparse Fourier transform of a general signal must use at least \Omega(k log(n/k)/ log log n) signal samples, even if it is allowed to perform adaptive sampling.Comment: 28 pages, appearing at STOC 201

Fast multi-dimensional NMR acquisition and processing using the sparse FFT

Increasing the dimensionality of NMR experiments strongly enhances the spectral resolution and provides invaluable direct information about atomic interactions. However, the price tag is high: long measurement times and heavy requirements on the computation power and data storage. We introduce sparse fast Fourier transform as a new method of NMR signal collection and processing, which is capable of reconstructing high quality spectra of large size and dimensionality with short measurement times, faster computations than the fast Fourier transform, and minimal storage for processing and handling of sparse spectra. The new algorithm is described and demonstrated for a 4D BEST-HNCOCA spectrum.Swedish Research Council (Research Grant 2011-5994)Swedish National Infrastructure for Computing (Grant SNIC 001/12-271

They Can Hear Your Heartbeats: Non-Invasive Security for Implantable Medical Devices

Wireless communication has become an intrinsic part of modern implantable medical devices (IMDs). Recent work, however, has demonstrated that wireless connectivity can be exploited to compromise the confidentiality of IMDs' transmitted data or to send unauthorized commands to IMDs---even commands that cause the device to deliver an electric shock to the patient. The key challenge in addressing these attacks stems from the difficulty of modifying or replacing already-implanted IMDs. Thus, in this paper, we explore the feasibility of protecting an implantable device from such attacks without modifying the device itself. We present a physical-layer solution that delegates the security of an IMD to a personal base station called the shield. The shield uses a novel radio design that can act as a jammer-cum-receiver. This design allows it to jam the IMD's messages, preventing others from decoding them while being able to decode them itself. It also allows the shield to jam unauthorized commands---even those that try to alter the shield's own transmissions. We implement our design in a software radio and evaluate it with commercial IMDs. We find that it effectively provides confidentiality for private data and protects the IMD from unauthorized commands.National Science Foundation (U.S.). (Grant number CNS-0831244)National Science Foundation (U.S.). Graduate Research Fellowship ProgramAlfred P. Sloan Foundation. FellowshipUnited States. Dept. of Health and Human Services. Cooperative Agreement (90TR0003/01

BigBand: GHz-Wide Sensing and Decoding on Commodity Radios

The goal of this paper is to make sensing and decoding GHz of spectrum simple, cheap, and low power. Our thesis is simple: if we can build a technology that captures GHz of spectrum using commodity Wi-Fi radios, it will have the right cost and power budget to enable a variety of new applications such as GHz-widedynamic access and concurrent decoding of diverse technologies. This vision will change today s situation where only expensive power-hungry spectrum analyzers can capture GHz-wide spectrum. Towards this goal, the paper harnesses the sparse Fourier transform to compute the frequency representation of a sparse signal without sampling it at full bandwidth. The paper makes the following contributions. First, it presents BigBand, a receiver that can sense and decode a sparse spectrum wider than its own digital bandwidth. Second, it builds a prototype of its design using 3 USRPs that each samples the spectrum at 50 MHz, producing a device that captures 0.9 GHz -- i.e., 6x larger bandwidth than the three USRPs combined. Finally, it extends its algorithm to enable spectrum sensing in scenarios where the spectrum is not sparse

The sparse fourier transform : theory & practice

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 237-250).The Fourier transform is one of the most fundamental tools for computing the frequency representation of signals. It plays a central role in signal processing, communications, audio and video compression, medical imaging, genomics, astronomy, as well as many other areas. Because of its widespread use, fast algorithms for computing the Fourier transform can benefit a large number of applications. The fastest algorithm for computing the Fourier transform is the FFT (Fast Fourier Transform) which runs in near-linear time making it an indispensable tool for many applications. However, today, the runtime of the FFT algorithm is no longer fast enough especially for big data problems where each dataset can be few terabytes. Hence, faster algorithms that run in sublinear time, i.e., do not even sample all the data points, have become necessary. This thesis addresses the above problem by developing the Sparse Fourier Transform algorithms and building practical systems that use these algorithms to solve key problems in six different applications. Specifically, on the theory front, the thesis introduces the Sparse Fourier Transform algorithms: a family of sublinear time algorithms for computing the Fourier transform faster than FFT. The Sparse Fourier Transform is based on the insight that many real-world signals are sparse, i.e., most of the frequencies have negligible contribution to the overall signal. Exploiting this sparsity, the thesis introduces several new algorithms which encompass two main axes: * Runtime Complexity: The thesis presents nearly optimal Sparse Fourier Transform algorithms that are faster than FFT and have the lowest runtime complexity known to date. " Sampling Complexity: The thesis presents Sparse Fourier Transform algorithms with optimal sampling complexity in the average case and the same nearly optimal runtime complexity. These algorithms use the minimum number of input data samples and hence, reduce acquisition cost and I/O overhead. On the systems front, the thesis develops software and hardware architectures for leveraging the Sparse Fourier Transform to address practical problems in applied fields. Our systems customize the theoretical algorithms to capture the structure of sparsity in each application, and hence maximize the resulting gains. We prototype all of our systems and evaluate them in accordance with the standard's of each application domain. The following list gives an overview of the systems presented in this thesis. " Wireless Networks: The thesis demonstrates how to use the Sparse Fourier Transform to build a wireless receiver that captures GHz-wide signals without sampling at the Nyquist rate. Hence, it enables wideband spectrum sensing and acquisition using cheap commodity hardware. * Mobile Systems: The thesis uses the Sparse Fourier Transform to design a GPS receiver that both reduces the delay to find the location and decreases the power consumption by 2 x. " Computer Graphics: Light fields enable new virtual reality and computational photography applications like interactive viewpoint changes, depth extraction and refocusing. The thesis shows that reconstructing light field images using the Sparse Fourier Transform reduces camera sampling requirements and improves image reconstruction quality. * Medical Imaging: The thesis enables efficient magnetic resonance spectroscopy (MRS), a new medical imaging technique that can reveal biomarkers for diseases like autism and cancer. The thesis shows how to improve the image quality while reducing the time a patient spends in an MRI machine by 3 x (e.g., from two hours to less than forty minutes). * Biochemistry: The thesis demonstrates that the Sparse Fourier Transform reduces NMR (Nuclear Magnetic Resonance) experiment time by 16 x (e.g. from weeks to days), enabling high dimensional NMR needed for discovering complex protein structures. * Digital Circuits: The thesis develops a chip with the largest Fourier Transform to date for sparse data. It delivers a 0.75 million point Sparse Fourier Transform chip that consumes 40 x less power than prior FFT VLSI implementations.by Haitham Al Hassanieh.Ph. D