We propose a decentralized but collaborative attribute-based tracing mechanism (a signer-identifying mechanism) for group signatures. Instead of a central tracing party in our scheme, a set of tracers satisfying the attribute set used for generating the group signature can identify the signer. Thus our proposal limits the parties who can identify the signer. On the other hand, it decentralized the tracing authority.

In ISSAC 2017, van der Hoeven and Larrieu showed that evaluating a polynomial P ın Fq [x] of degree <n at all n -th roots of unity in Fqd can essentially be computed d times faster than evaluating Q ın Fqd x at all these roots, assuming Fqd contains a primitive n -th root of unity. Termed the Frobenius FFT, this discovery has a profound impact on polynomial multiplication, especially for multiplying binary polynomials, which finds ample application in coding theory and cryptography. In this paper, we show that the theory of Frobenius FFT beautifully generalizes to a class of additive FFT developed by Cantor and Gao-Mateer. Furthermore, we demonstrate the power of Frobenius additive FFT for q=2: to multiply two binary polynomials whose product is of degree <256, the new technique requires only 29,005 bit operations, while the best result previously reported was 33,397. To the best of our knowledge, this is the first time that FFT-based multiplication outperforms Karatsuba and the like at such a low degree in terms of bit-operation count.

In this paper, we present the implementation of a multi-mode crypto-coprocessor, which can support three different public-key cryptography (PKC) engines (NTRU, TTS, Pairing) used in post-quantum and identity-based cryptosystems. The PKC-based security protocols are more energy-efficient because they usually require less communication overhead than symmetric-key-based counterparts. In this work, we propose the first-of-its-kind tri-mode PKC coprocessor for secured data transmission in Internet-of-Things (IoT) systems. For the purpose of low energy consumption, the crypto-coprocessor incorporates three design features, including 1) specialized instruction set for the multi-mode cryptosystems, 2) a highly parallel arithmetic unit for cryptographic kernel operations, and 3) a smart scheduling unit with intelligent control mechanism. By utilizing the parallel arithmetic unit, the proposed crypto-coprocessor can achieve about 50% speed up. Meanwhile, the smart scheduling unit can save up to 18% of the total latency. The crypto-coprocessor was implemented with AHB interface in TSMC 90nm CMOS technology, and the die size is only 1.96 mm2. Furthermore, our chip is integrated with an ARM-based system-on-chip (SoC) platform for functional verification.

Cloud storage is one of the most rapidly growing cloud services, which at the same time also faces serious security challenges. Recently, several cloud-storage service providers started to provide encryption protection to client data in the cloud. However, encryption imposes significant limits on data use. In this paper, we report our design and implementation of an encrypted cloud storage system that supports multi-user secure indices, allowing efficient search among encrypted documents of multiple users. Experiment results show that keyword search can be performed in real time. We believe that our system represent a first step toward providing secure and useful cloud-storage services in practice.

In physical-layer security, secret bits are extracted from wireless channels. With the assumption of channel reciprocity, the legitimate users share the same channel which is independent of the channels between the legitimate users and the eavesdropper, leading to secure transmissions. However, practical implementation of the physical layer security faces many challenges. First, for the correlated channel such as the multiple-input and multiple-output (MIMO) channel, the security is decreased due to the correlation between the generated secret bits. Second, the nearby eavesdropper posts a security threat due to observing the same channel as the legitimate user's. Third, the eavesdroppers might try to reconstruct the wireless environments. In this paper, we propose two practical physical layer security schemes for the MIMO orthogonal frequency-division multiplexing (MIMO-OFDM) systems: the precoding matrix index (PMI)-based secret key generation with rotation matrix (MOPRO) and the channel quantization-based (MOCHA) scheme. The former utilizes PMI and rotated reference signals to prevent the eavesdroppers from learning the secret key information and the latter applies channel quantization in order to extract more secret key bits. It is shown that not only the secure communication but also the MIMO gain can be guaranteed by using the proposed schemes.

In this paper, we describe COCA -- Computation Offload to Clouds using AOP (aspect-oriented programming). COCA is a programming framework that allows smart phones application developers to offload part of the computation to servers in the cloud easily. COCA works at the source level. By harnessing the power of AOP, COCA inserts appropriate offloading code into the source code of the target application based on the result of static and dynamic profiling. As a proof of concept, we integrate COCA into the Android development environment and fully automate the new build process, making application programming and software maintenance easier. With COCA, mobile applications can now automatically offload part of the computation to the cloud, achieving better performance and longer battery life. Smart phones such as iPhone and Android phones can now easily leverage the immense computing power of the cloud to achieve tasks that were considered difficult before, such as having a more complicated artificial-intelligence engine.

We describe our implementation of the Elliptic Curve Method (ECM) of integer factorization on the Cell processor. ECM is the method of choice for finding medium-sized prime factors, e.g., between $2^{30}$ and $2^{100}$. A good ECM implementation is of paramount importance for evaluating the security of cryptosystems like RSA because it is a critical step in the modern versions of the Number Field Sieves (NFS), currently the most efficient cryptanalysis technique against RSA. We use ECM as a benchmark to understand how the performance of integer number crunching applications can benefit from several architectural design features of the Cell including wide arithmetic pipeline, auxiliary pipeline for handling managerial tasks, and large on-die memory per thread of execution. As a result, our ECM implementation on the PowerXCell~8i Cell processor outperforms all previously published implementations on other hardware platforms including graphics processing units (GPUs). For example, compared with the best published result on an NVIDIA GTX 295 graphics card, ours is more than three times faster on absolute basis. This is in spite of the fact that GPUs have greater raw number-crunching capability, not to mention that the Cell consumes less power and hence delivers much better performance per watt.

A MIMO-OFDM PHY Integrated (MOPI) scheme is proposed to provide confidentiality against eavesdroppers in wireless networks. The proposed MOPI scheme prevents any eavesdropper from learning the channel state information (CSI) of the wiretap channel and decoding the information being exchanged. This is achieved by the use of channel sounding combined with a novel physical-layer network coding (PNC) scheme such that the eavesdropper, due to lack of CSI, will suffer from very poor decoding performance. The security of the proposed MOPI scheme is verified by computer simulation. The simulation results show that confidentiality is guaranteed as long as the eavesdropper's channel realization is independent of the legal receiver's, which is usually the case in a typical wireless network.

Radio-frequency identification (RFID) technologies allow remote identification as well as generic data access using radio waves. It is also commonly used in transportation and other payment systems, e.g., the MIFAREof NXP Semiconductors, one of the most widely deployed contactless smart card standards. Recently, the interest in using RFID for micro payment grows rapidly as users get used to the convenience brought by RFID,and corporations discover that RFID can significantly lower the cost of operation. However, there are security concerns, as many passive RFID technologies do not have adequate cryptographic protection. Furthermore, thecommunication can be eavesdropped by a third party, making RFID particularly vulnerable to all sorts of attacks.In this work, we examine the EasyCard of the Taipei Metro Rapid Transit (MRT) Corporation, a transportation ticketing system based on the MIFARE Classic technology. We capture and analyze the communication between a legitimate reader and an EasyCard using GNURadio, an open-source software-defined radio running on PC. We will share our experiences with EasyCard security and hopefully provide some insights into RFID security inpractice.

We consider the task of using one or more unmanned aerial vehicles (UAVs) to relay messages between two distant ground nodes. For delay-tolerant applications like latency-insensitive bulk data transfer, we seek to maximize throughput by having a UAV load from a source ground node, carry the data while flying to the destination, and finally deliver the data to a destination ground node. We term this the "load-carry-and-deliver" (LCAD) paradigm and compare it against the conventional multi-hop, store-and-forward paradigm. We identify and analyze several of the most important factors in constructing a throughput-maximizing framework subject to constraints on both application allowable delay and UAV maneuverability. We report performance measurement results for IEEE 802.11g devices in three flight tests, based on which we derive a statistical model for predicting throughput performance for LCAD. Due to the nature of commercial off-the-shelf systems, this methodology is of essential importance for allowing better flight-path design to achieve high throughput.

In this paper, we propose transmit antenna selection based on receiver feedback of channel information obtained via link-layer probing. Furthermore, we report the performance gain of the proposed antenna selection scheme in an experimental multi-antenna 802.11 network. We built a low-altitude Unmanned Aerial Vehicle (UAV) testbed using commodity dual-antenna 802.11 hardware and performed field experiments to collect traces of link performance using antennas of various types and orientations. Based on the collected traces, we demonstrate that transmit antenna selection can achieve a significant amount of gain using a link-layer channel probing protocol at a relatively low probing rate. The largest improvement we observed with joint transmit/receive antenna selection in 2x2 systems was 32%, about twice as much as that of receive-only antenna selection in 1x2 systems, which achieved 17%. Moreover, a similar improvement is obtained with probing intervals up to about 200 milliseconds, which is infrequently enough to consume only a small fraction of the available 802.11 channel capacity. Since these results require only a low implementation and operational cost, we conclude that transmit antenna selection is a worthwhile technique to use with the kind of multi-antenna mobile ad-hoc networks we examined.

We evaluate the performance impact of adjacent channel interference (ACI) in multi-hop wireless networks based on dual-radio 802.11a nodes. Although these nodes use chipsets that satisfy the transmit-mask requirements set by the IEEE 802.11 standard, the multi-hop performance is still significantly affected by ACI. That is, a node's transmitter can interfere with its own receiver on a different channel; as a result, multi-hop throughput is severely degraded. This degradation is especially pronounced for 802.11a. We use a spectrum analyzer with a signal combiner to quantify ACI under various conditions and propose solutions to mitigate the effect of such interference on multi-hop forwarding. Field experiments with multi-hop relay have validated these findings as well as the effectiveness of our solutions.

We report measured performance of 802.11a wireless links from an unmanned aerial vehicle (UAV) to ground stations. In a set of field experiments, we record the received signal strength indicator (RSSI) and measure the raw link-layer throughput for various antenna orientations, communication distances and ground-station elevations. By comparing the performance of 32 simultaneous pairs of UAV and ground station configurations, we are able to conclude that, in order to achieve the highest throughput under a typical flyover UAV flight path, both the UAV and the ground station should use omni-directional dipole (as opposed to high-gain, narrow- beam) antennas positioned horizontally, with their respective antenna null pointing to a direction perpendicular to the UAV's flight path. In addition, a moderate amount of elevation of the ground stations can also improve performance significantly.

We present an overlay network routing scheme, called path probing relay routing (PPRR), which is capable of promptly switching to alternative paths when the direct paths provided by the underlying IP networks suffer from serious performance degradation or outage. PPRR uses a randomized search algorithm to discover available alternative paths and employs an end-to-end, on-demand probing technique to determine their quality. To assess the effectiveness of PPRR, we conduct performance simulations using four sets of real-world traces, collected by various research groups at different times and places. Our simulation results show that the performance of PPRR is comparable to that of a typical link state relay routing algorithm. Compared with the latter, PPRR has lower probing overhead in the sense that the overhead remains constant as network size grows. In particular, PPRR avoids the need to flood the overlay network with link state updates.

We propose using spectral analysis to identify normal TCP traffic so that it will not be dropped or rate-limited in defense against denial of service (DoS) attacks. The approach can reduce false positives of attacker identification schemes and thus decrease the associated unnecessary slowdown or stoppage of legitimate traffic. For the spectral analysis, we use the number of packet arrivals of a flow in fixed-length time intervals as the signal. We then estimate the power spectral density of the signal, in which information of periodicity, or lack thereof, in the signal reveals itself. A normal TCP flow should exhibit strong periodicity around its round-trip time in both flow directions, whereas an attack flow usually does not. We validate the effectiveness of the approach with simulation and trace analysis. We argue that the approach complements existing DoS defense mechanisms that focus on identifying attack traffic.