OpenRaiser/Intern-Atlas huggingface dataset:
Protection and Deception: Discovering Game Theory and Cyber Literacy through a Novel Board Game Experience
Venue: arXiv cs.CY 2015
Year: 2015

Cyber literacy merits serious research attention because it addresses a confluence of specialization and generalization; cybersecurity is often conceived of as approachable only by a technological intelligentsia, yet its interdependent nature demands education for a broad population. Therefore, educational tools should lead participants to discover technical knowledge in an accessible and attractive framework. In this paper, we present Protection and Deception (P&G), a novel two-player board game. P&G has three main contributions. First, it builds cyber literacy by giving participants "hands-on" experience with game pieces that have the capabilities of cyber-attacks such as worms, masquerading attacks/spoofs, replay attacks, and Trojans. Second, P&G teaches the important game-theoretic concepts of asymmetric information and resource allocation implicitly and non-obtrusively through its game play. Finally, it strives for the important objective of security education for underrepresented minorities and people without explicit technical experience. We tested P&G at a community center in Manhattan with middle- and high school students, and observed enjoyment and increased cyber literacy along with suggestions for improvement of the game. Together with these results, our paper also presents images of the attractive board design and 3D printed game pieces, together with a Monte-Carlo analysis that we used to ensure a balanced gaming experience.
Fast exact summation using small and large superaccumulators
Venue: arXiv cs.NA 2015
Year: 2015

I present two new methods for exactly summing a set of floating-point numbers, and then correctly rounding to the nearest floating-point number. Higher accuracy than simple summation (rounding after each addition) is important in many applications, such as finding the sample mean of data. Exact summation also guarantees identical results with parallel and serial implementations, since the exact sum is independent of order. The new methods use variations on the concept of a "superaccumulator" - a large fixed-point number that can exactly represent the sum of any reasonable number of floating-point values. One method uses a "small" superaccumulator with sixty-seven 64-bit chunks, each with 32-bit overlap with the next chunk, allowing carry propagation to be done infrequently. The small superaccumulator is used alone when summing a small number of terms. For big summations, a "large" superaccumulator is used as well. It consists of 4096 64-bit chunks, one for every possible combination of exponent bits and sign bit, plus counts of when each chunk needs to be transferred to the small superaccumulator. To add a term to the large superaccumulator, only a single chunk and its associated count need to be updated, which takes very few instructions if carefully implemented. On modern 64-bit processors, exactly summing a large array using this combination of large and small superaccumulators takes less than twice the time of simple, inexact, ordered summation, with a serial implementation. A parallel implementation using a small number of processor cores can be expected to perform exact summation of large arrays at a speed that reaches the limit imposed by memory bandwidth. Some common methods that attempt to improve accuracy without being exact may therefore be pointless, at least for large summations, since they are slower than computing the sum exactly.
High Speed CAN Transmission Scheme Supporting Data Rate of over 100 Mbps
Venue: arXiv cs.IT 2015
Year: 2015

As the number of electronic components in the car increases, the requirement for the higher data transmission scheme among them is on the sharp rise. Controller area network (CAN) has been widely adopted to support the in-car communications needs but the data rate is far below what other schemes such as Ethernet and optical fibers can offer. A new scheme for enhancing the speed of CAN network has been proposed, where carrier modulated signal is introduced on top of the existing CAN signal whereby the data rate can be enhanced over 100Mbps. The proposed scheme is compatible with the existing CAN network and accordingly enables seamless upgrade of the existing network to support high speed demand using CAN protocol.
New HSL Distance Based Colour Clustering Algorithm
Venue: arXiv cs.CV 2015
Year: 2015

In this paper, we define a distance for the HSL colour system. Next, the proposed distance is used for a fuzzy colour clustering algorithm construction. The presented algorithm is related to the well-known fuzzy c-means algorithm. Finally, the clustering algorithm is used as colour reduction method. The obtained experimental results are presented to demonstrate the effectiveness of our approach.
Complexity of Manipulation in Elections with Top-truncated Ballots
Venue: arXiv cs.GT 2015
Year: 2015

In the computational social choice literature, there has been great interest in understanding how computational complexity can act as a barrier against manipulation of elections. Much of this literature, however, makes the assumption that the voters or agents specify a complete preference ordering over the set of candidates. There are many multiagent systems applications, and even real-world elections, where this assumption is not warranted, and this in turn raises the question "How hard is it to manipulate elections if the agents reveal only partial preference orderings?" It is this question we try to address in this paper. In particular, we look at the weighted manipulation problem -- both constructive and destructive manipulation -- when the voters are allowed to specify any top-truncated ordering over the set of candidates. We provide general results for all scoring rules, for elimination versions of all scoring rules, for the plurality with runoff rule, for a family of election systems known as Copeland$^α$, and for the maximin protocol. Finally, we also look at the impact on complexity of manipulation when there is uncertainty about the non-manipulators' votes.
We Can Track You If You Take the Metro: Tracking Metro Riders Using Accelerometers on Smartphones
Venue: arXiv cs.CR 2015
Year: 2015

Motion sensors (e.g., accelerometers) on smartphones have been demonstrated to be a powerful side channel for attackers to spy on users' inputs on touchscreen. In this paper, we reveal another motion accelerometer-based attack which is particularly serious: when a person takes the metro, a malicious application on her smartphone can easily use accelerator readings to trace her. We first propose a basic attack that can automatically extract metro-related data from a large amount of mixed accelerator readings, and then use an ensemble interval classier built from supervised learning to infer the riding intervals of the user. While this attack is very effective, the supervised learning part requires the attacker to collect labeled training data for each station interval, which is a significant amount of effort. To improve the efficiency of our attack, we further propose a semi-supervised learning approach, which only requires the attacker to collect labeled data for a very small number of station intervals with obvious characteristics. We conduct real experiments on a metro line in a major city. The results show that the inferring accuracy could reach 89\% and 92\% if the user takes the metro for 4 and 6 stations, respectively.
A comparative study between proposed Hyper Kurtosis based Modified Duo-Histogram Equalization (HKMDHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) for Contrast Enhancement Purpose of Low Contrast Human Brain CT scan images
Venue: arXiv cs.CV 2015
Year: 2015

In this paper, a comparative study between proposed hyper kurtosis based modified duo-histogram equalization (HKMDHE) algorithm and contrast limited adaptive histogram enhancement (CLAHE) has been presented for the implementation of contrast enhancement and brightness preservation of low contrast human brain CT scan images. In HKMDHE algorithm, contrast enhancement is done on the hyper-kurtosis based application. The results are very promising of proposed HKMDHE technique with improved PSNR values and lesser AMMBE values than CLAHE technique.
Tunnel Surface 3D Reconstruction from Unoriented Image Sequences
Venue: arXiv cs.CV 2015
Year: 2015

The 3D documentation of the tunnel surface during construction requires fast and robust measurement systems. In the solution proposed in this paper, during tunnel advance a single camera is taking pictures of the tunnel surface from several positions. The recorded images are automatically processed to gain a 3D tunnel surface model. Image acquisition is realized by the tunneling/advance/driving personnel close to the tunnel face (= the front end of the advance). Based on the following fully automatic analysis/evaluation, a decision on the quality of the outbreak can be made within a few minutes. This paper describes the image recording system and conditions as well as the stereo-photogrammetry based workflow for the continuously merged dense 3D reconstruction of the entire advance region. Geo-reference is realized by means of signalized targets that are automatically detected in the images. We report on the results of recent testing under real construction conditions, and conclude with prospects for further development in terms of on-site performance.
Interest-Based Access Control for Content Centric Networks (extended version)
Venue: arXiv cs.NI 2015
Year: 2015

Content-Centric Networking (CCN) is an emerging network architecture designed to overcome limitations of the current IP-based Internet. One of the fundamental tenets of CCN is that data, or content, is a named and addressable entity in the network. Consumers request content by issuing interest messages with the desired content name. These interests are forwarded by routers to producers, and the resulting content object is returned and optionally cached at each router along the path. In-network caching makes it difficult to enforce access control policies on sensitive content outside of the producer since routers only use interest information for forwarding decisions. To that end, we propose an Interest-Based Access Control (IBAC) scheme that enables access control enforcement using only information contained in interest messages, i.e., by making sensitive content names unpredictable to unauthorized parties. Our IBAC scheme supports both hash- and encryption-based name obfuscation. We address the problem of interest replay attacks by formulating a mutual trust framework between producers and consumers that enables routers to perform authorization checks when satisfying interests from their cache. We assess the computational, storage, and bandwidth overhead of each IBAC variant. Our design is flexible and allows producers to arbitrarily specify and enforce any type of access control on content, without having to deal with the problems of content encryption and key distribution. This is the first comprehensive design for CCN access control using only information contained in interest messages.
New DNA Cyclic Codes over Rings
Venue: arXiv cs.IT 2015
Year: 2015

This paper is dealing with DNA cyclic codes which play an important role in DNA computing and have attracted a particular attention in the literature. Firstly, we introduce a new family of DNA cyclic codes over the ring $R=\mathbb{F}_2[u]/(u^6)$. Such codes have theoretical advantages as well as several applications in DNA computing. A direct link between the elements of such a ring and the $64$ codons used in the amino acids of the living organisms is established. Such a correspondence allows us to extend the notion of the edit distance to the ring $R$ which is useful for the correction of the insertion, deletion and substitution errors. Next, we define the Lee weight, the Gray map over the ring $R$ as well as the binary image of the cyclic DNA codes allowing the transfer of studying DNA codes into studying binary codes. Secondly, we introduce another new family of DNA skew cyclic codes constructed over the ring $\tilde {R}=\mathbb{F}_2+v\mathbb{F}_2=\{0,1,v,v+1\}$ where $v^2=v$ and study their property of being reverse-complement. We show that the obtained code is derived from the cyclic reverse-complement code over the ring $\tilde {R}$. We shall provide the binary images and present some explicit examples of such codes.
On the Sum Capacity of the Gaussian X Channel in the Mixed Interference Regime
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, we analyze the Gaussian X channel in the mixed interference regime. In this regime, multiple access transmission to one of the receivers is shown to be close to optimal in terms of sum rate. Three upper bounds are derived for the sum capacity in the mixed interference regime, and the subregions where each of these bounds dominate the others are identified. The genie-aided sum capacity upper bounds derived also show that the gap between sum capacity and the sum rate of the multiple access transmission scheme is small for a significant part of the mixed interference region. For any δ> 0, the region where multiple access transmission to one of the receivers is within δfrom sum capacity is determined.
Un algorithme incrémental dirigé par les flots et basé sur les contraintes pour l'aide à la localisation d'erreurs
Venue: arXiv cs.SE 2015
Year: 2015

In this article, we present our improved algorithm for error localization from counterexamples, LocFaults, flow-driven and constraint-based. This algorithm analyzes the paths of CFG (Control Flow Graph) of the erroneous program to calculate the subsets of suspicious instructions to correct the program. Indeed, we generate a system of constraints for paths of control flow graph for which at most k conditional statements can be wrong. Then we compute the MCSs (Minimal Correction Set) of bounded size on each of these paths. Removal of one of these sets of constraints gives maximal satisfiable subset, in other words, a maximal satisfiable subset satisfying the postcondition. To calculate the MCSs, we extend the generic algorithm proposed by Liffiton and Sakallah in order to deal programs with numerical instructions more effectively. We are interested to present the incremental aspect of this new algorithm that is not yet presented.
Domain Adaptation Extreme Learning Machines for Drift Compensation in E-nose Systems
Venue: arXiv cs.LG 2015
Year: 2015

This paper addresses an important issue, known as sensor drift that behaves a nonlinear dynamic property in electronic nose (E-nose), from the viewpoint of machine learning. Traditional methods for drift compensation are laborious and costly due to the frequent acquisition and labeling process for gases samples recalibration. Extreme learning machines (ELMs) have been confirmed to be efficient and effective learning techniques for pattern recognition and regression. However, ELMs primarily focus on the supervised, semi-supervised and unsupervised learning problems in single domain (i.e. source domain). To our best knowledge, ELM with cross-domain learning capability has never been studied. This paper proposes a unified framework, referred to as Domain Adaptation Extreme Learning Machine (DAELM), which learns a robust classifier by leveraging a limited number of labeled data from target domain for drift compensation as well as gases recognition in E-nose systems, without loss of the computational efficiency and learning ability of traditional ELM. In the unified framework, two algorithms called DAELM-S and DAELM-T are proposed for the purpose of this paper, respectively. In order to percept the differences among ELM, DAELM-S and DAELM-T, two remarks are provided. Experiments on the popular sensor drift data with multiple batches collected by E-nose system clearly demonstrate that the proposed DAELM significantly outperforms existing drift compensation methods without cumbersome measures, and also bring new perspectives for ELM.
Robust multiuser detection in impulsive channels based on M-estimation using a new penalty function
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, we consider the problem of multiuser detection in non-Gaussian channels. We propose a new penalty function for robust multiuser detection. The proposed detector outperforms other suboptimal detectors in non-Gaussian environment. Analytical and simulation result shows the performance of the proposed detector compare to other detectors.
Placement Optimization of Energy and Information Access Points in Wireless Powered Communication Networks
Venue: arXiv cs.NI 2015
Year: 2015

The applications of wireless power transfer technology to wireless communications can help build a wireless powered communication network (WPCN) with more reliable and sustainable power supply compared to the conventional battery-powered network. However, due to the fundamental differences in wireless information and power transmissions, many important aspects of conventional battery-powered wireless communication networks need to be redesigned for efficient operations of WPCNs. In this paper, we study the placement optimization of energy and information access points in WPCNs, where the wireless devices (WDs) harvest the radio frequency energy transferred by dedicated energy nodes (ENs) in the downlink, and use the harvested energy to transmit data to information access points (APs) in the uplink. In particular, we are interested in minimizing the network deployment cost with minimum number of ENs and APs by optimizing their locations, while satisfying the energy harvesting and communication performance requirements of the WDs. Specifically, we first study the minimum-cost placement problem when the ENs and APs are separately located, where an alternating optimization method is proposed to jointly optimize the locations of ENs and APs. Then, we study the placement optimization when each pair of EN and AP are co-located and integrated as a hybrid access point, and propose an efficient algorithm to solve this problem. Simulation results show that the proposed methods can effectively reduce the network deployment cost and yet guarantee the given performance requirements, which is a key consideration in the future applications of WPCNs.
ML Detection in Phase Noise Impaired SIMO Channels with Uplink Training
Venue: arXiv cs.IT 2015
Year: 2015

The problem of maximum likelihood (ML) detection in training-assisted single-input multiple-output (SIMO) systems with phase noise impairments is studied for two different scenarios, i.e. the case when the channel is deterministic and known (constant channel) and the case when the channel is stochastic and unknown (fading channel). Further, two different operations with respect to the phase noise sources are considered, namely, the case of identical phase noise sources and the case of independent phase noise sources over the antennas. In all scenarios the optimal detector is derived for a very general parametrization of the phase noise distribution. Further, a high signal-to-noise-ratio (SNR) analysis is performed to show that symbol-error-rate (SER) floors appear in all cases. The SER floor in the case of identical phase noise sources (for both constant and fading channels) is independent of the number of antenna elements. In contrast, the SER floor in the case of independent phase noise sources is reduced when increasing the number of antenna elements (for both constant and fading channels). Finally, the system model is extended to multiple data channel uses and it is shown that the conclusions are valid for these setups, as well.
Analysis of GPU Parallel Computing based on Matlab
Venue: arXiv cs.DC 2015
Year: 2015

Matlab is very widely used in scientific computing, but Matlab computational efficiency is lower than C language program. In order to improve the computing speed, some toolbox can use GPU to accelerate the computation. This paper describes GPU working principle, our experiments and results analysis of parallel computing by using GPU based on Matlab. Experimental results show that for parallel operations, GPU computing speed is faster than CPU, for the logical instructions, GPU computing speed is slower than CPU.
A Simple Yet Effective Improvement to the Bilateral Filter for Image Denoising
Venue: arXiv cs.CV 2015
Year: 2015

The bilateral filter has diverse applications in image processing, computer vision, and computational photography. In particular, this non-linear filter is quite effective in denoising images corrupted with additive Gaussian noise. The filter, however, is known to perform poorly at large noise levels. Several adaptations of the filter have been proposed in the literature to address this shortcoming, but often at an added computational cost. In this paper, we report a simple yet effective modification that improves the denoising performance of the bilateral filter at almost no additional cost. We provide visual and quantitative results on standard test images which show that this improvement is significant both visually and in terms of PSNR and SSIM (often as large as 5 dB). We also demonstrate how the proposed filtering can be implemented at reduced complexity by adapting a recent idea for fast bilateral filtering.
Stochastic Block Coordinate Frank-Wolfe Algorithm for Large-Scale Biological Network Alignment
Venue: arXiv cs.CE 2015
Year: 2015

With increasingly "big" data available in biomedical research, deriving accurate and reproducible biology knowledge from such big data imposes enormous computational challenges. In this paper, motivated by recently developed stochastic block coordinate algorithms, we propose a highly scalable randomized block coordinate Frank-Wolfe algorithm for convex optimization with general compact convex constraints, which has diverse applications in analyzing biomedical data for better understanding cellular and disease mechanisms. We focus on implementing the derived stochastic block coordinate algorithm to align protein-protein interaction networks for identifying conserved functional pathways based on the IsoRank framework. Our derived stochastic block coordinate Frank-Wolfe (SBCFW) algorithm has the convergence guarantee and naturally leads to the decreased computational cost (time and space) for each iteration. Our experiments for querying conserved functional protein complexes in yeast networks confirm the effectiveness of this technique for analyzing large-scale biological networks.
Supercharge me: Boost Router Convergence with SDN
Venue: arXiv cs.NI 2015
Year: 2015

Software Defined Networking (SDN) is a promising approach for improving the performance and manageability of future network architectures. However, little work has gone into using SDN to improve the performance and manageability of existing networks without requiring a major overhaul of the existing network infrastructure. In this paper, we show how we can dramatically improve, or supercharge, the performance of existing IP routers by combining them with SDN-enabled equipment in a novel way. More particularly, our supercharged solution substantially reduces the convergence time of an IP router upon link or node failure without inducing any reconfiguration of the IP router itself. Our key insight is to use the SDN controller to precompute backup forwarding entries and immediately activate them upon failure, enabling almost immediate data-plane recovery, while letting the router converge at its typical slow pace. By boosting existing equipment's performance, we not only increase their lifetime but also provide new incentives for network operators to kickstart SDN deployment. We implemented a fully functional "supercharger" and use it to boost the convergence performance of a Cisco Nexus 7k router. Using a FPGA-based traffic generator, we show that our supercharged router systematically converges within ~150ms, a 900x reduction with respect to its normal convergence time under similar conditions.