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arXiv 2018年

作者： Homoliak, Ivan Teknös, Martin Ochoa, Martín Breitenbacher, Dominik Hosseini, Saeid Hanacek, Petr Faculty of Information Technology Brno University of Technology Bozetechova 1/2 Brno612 66 Czech Republic STE-SUTD Cyber Security Laboratory 8 Somapah Road Singapore487372 Singapore Department of Applied Mathematics and Computer Science Universidad del Rosario Bogotá Colombia Cyxtera Technologies

Machine-learning based intrusion detection classifiers are able to detect unknown attacks, but at the same time they may be susceptible to evasion by obfuscation techniques. An adversary intruder which possesses a crucial knowledge about a protection system can easily bypass the detection module. The main objective of our work is to improve the performance capabilities of intrusion detection classifiers against such adversaries. To this end, we firstly propose several obfuscation techniques of remote attacks that are based on the modification of various properties of network connections;then we conduct a set of comprehensive experiments to evaluate the effectiveness of intrusion detection classifiers against obfuscated attacks. We instantiate our approach by means of a tool, based on NetEm and Metasploit, which implements our obfuscation operators on any TCP communication. This allows us to generate modified network traffic for machine learning experiments employing features for assessing network statistics and behavior of TCP connections. We perform evaluation on five classifiers: Gaussian Naïve Bayes, Gaussian Naïve Bayes with kernel density estimation, Logistic Regression, Decision Tree, and Support Vector Machines. Our experiments confirm the assumption that it is possible to evade the intrusion detection capability of all classifiers trained without prior knowledge about obfuscated attacks, causing an exacerbation of the TPR ranging from 7.8% to 66.8%. Further, when widening the training knowledge of the classifiers by a subset of obfuscated attacks, we achieve a significant improvement of the TPR by 4.21% – 73.3%, while the FPR is deteriorated only slightly (0.1% – 1.48%). Finally, we test the capability of an obfuscations-aware classifier to detect unknown obfuscated attacks, where we achieve over 90% detection rate on average for most of the obfuscations. Copyright © 2018, The Authors. All rights reserved.

关键词： Intrusion detection

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Modeling Multi-turn conversation with deep utterance aggregation

arXiv

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arXiv 2018年

作者： Zhang, Zhuosheng Li, Jiangtong Zhu, Pengfei Zhao, Hai Liu, Gongshen Department of Computer Science and Engineering Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai200240 College of Zhiyuan Shanghai Jiao Tong University School of Cyber Security Shanghai Jiao Tong University School of Computer Science and Software Engineering East China Normal University

Multi-turn conversation understanding is a major challenge for building intelligent dialogue systems. This work focuses on retrieval-based response matching for multi-turn conversation whose related work simply concatenates the conversation utterances, ignoring the interactions among previous utterances for context modeling. In this paper, we formulate previous utterances into context using a proposed deep utterance aggregation model to form a fine-grained context representation. In detail, a self-matching attention is first introduced to route the vital information in each utterance. Then the model matches a response with each refined utterance and the final matching score is obtained after attentive turns aggregation. Experimental results show our model outperforms the state-of-the-art methods on three multi-turn conversation benchmarks, including a newly introduced e-commerce dialogue corpus. Copyright © 2018, The Authors. All rights reserved.

关键词： Speech processing

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technology of wireless transmission of energy to remote objects based on multi-frequency system of transmitters 11

Technology of wireless transmission of energy to remote obje...

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11th International Conference on Antenna Theory and Techniques, ICATT 2017

作者： Grishin, Igor Yu. Timirgaleeva, Rena R. Titov, Sergey Vl. Titova, Yelena V. Department of Computer Technology and Information Security Kuban State Technological Universityline Krasnodar Russia Department of System Engineering Kharkiv National University of Radioelectronics Kharkiv Ukraine

ISBN: (纸本)9781538629215

The authors of this work offer a form of application of space-phase-frequency focusing of the V-shaped multi-frequency pulses for the creation of the systems of wireless transmission of energy to land-based, mountain and other difficult-To-reach objects. The creation of overhead, above-water, underground and underwater transmission lines of electric power to such facilities are impossible or impractical for technical, economic and other reasons. Technical feasibility of such systems for wireless transmission of energy to remote objects, and areas of environmental safety for the staff and the local population has been estimated. © 2017 IEEE.

关键词： Transmitters

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A hybrid universal blind quantum computation

arXiv

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arXiv 2018年

作者： Zhang, Xiaoqian Luo, Weiqi Zeng, Guoqiang Weng, Jian Yang, Yaxi Chen, Minrong Tan, Xiaoqing College of Information Science and Technology Jinan University Guangzhou510632 China College of Cyber Security Jinan University Guangzhou510632 China School of Computer South China Normal University Guangzhou510631 China Department of Mathematics Jinan University Guangzhou510632 China

In blind quantum computation (BQC), a client delegates her quantum computation to a server with universal quantum computers who learns nothing about the client's private information. In measurement-based BQC model, entangled states are generally used to realize quantum computing. However, to generate a large-scale entangled state in experiment becomes a challenge issue. In circuit-based BQC model, single-qubit gates can be realized precisely, but entangled gates are probabilistically successful. This remains a challenge to realize entangled gates with a deterministic method in some systems. To solve above two problems, we propose the first hybrid universal BQC protocol based on measurements and circuits, where the client prepares single-qubit states and the server performs universal quantum computing. We analyze and prove the correctness, blindness and verifiability of the proposed protocol. Copyright © 2018, The Authors. All rights reserved.

关键词： Qubits

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Hongtao Liu Lulu Guo Long Chen Xueyan Liu Zhenjia Zhu School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China School of cyber Security and Information Law Chongqing University of Posts and Telecommunications Chongqing China School of Economics and Management Chongqing University of Posts and Telecommunications Chongqing China School of Software Engineering Shenzhen Institute of Information Technology Shenzhen China

ISBN: (纸本)9781728104423;9781728104416

The core of the recommendation system is the recommendation algorithm, especially the application of collaborative filtering recommendation algorithm is the most widely used. With the rapid increase of data sparsity. This paper aims at the problem of data sparsity in collaborative filtering algorithms. By mining the hidden information behind the user and the project, that is, considering different factors in the user's personal rating habits, and using Cosine and Jaccard to calculate the full degree of similarity to effectively use the rate data, improves the similarity calculation method, and solves the problem of low accuracy of the recommendation due to inaccuracy of similarity calculation. This is more in line with the logic of real life and can produce reasonable recommendations.

关键词： Collaboration Filtering algorithms Telecommunications Data mining Internet Recommender systems

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Distributed and adaptive location identification system for mobile devices

arXiv

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arXiv 2018年

作者： Awad, Fahed Al-Sadi, Aisha Al-Quran, Fida'a Alsmady, Abdulsalam Department of Network Engineering and Security Jordan University of Science and Technology P. O. Box 3030 Irbid22110 Jordan Department of Computer Science Jordan University of Science and Technology P. O. Box 3030 Irbid22110 Jordan Department of Computer Engineering Jordan University of Science and Technology P. O. Box 3030 Irbid22110 Jordan

Indoor location identification and navigation need to be as simple, seamless, and ubiquitous as its outdoor GPS-based counterpart is. It would be of great convenience to the mobile user to be able to continue navigating seamlessly as he or she moves from a GPS-clear outdoor environment into an indoor environment or a GPS-obstructed outdoor environment such as a tunnel or forest. Existing infrastructure-based indoor localization systems lack such capability, on top of potentially facing several critical technical challenges such as increased cost of installation, centralization, lack of reliability, poor localization accuracy, poor adaptation to the dynamics of the surrounding environment, latency, system-level and computational complexities, repetitive labor-intensive parameter tuning, and user privacy. To this end, this paper presents a novel mechanism with the potential to overcome most (if not all) of the abovementioned challenges. The proposed mechanism is simple, distributed, adaptive, collaborative, and cost-effective. Based on the proposed algorithm, a mobile blind device can potentially utilize, as GPS-like reference nodes, either in-range location-aware compatible mobile devices or preinstalled low-cost infrastructure-less location-aware beacon nodes. The proposed approach is model-based and calibration-free that uses the received signal strength to periodically and collaboratively measure and update the radio frequency characteristics of the operating environment to estimate the distances to the reference nodes. Trilateration is then used by the blind device to identify its own location, similar to that used in the GPS-based system. Simulation and empirical testing ascertained that the proposed approach can potentially be the core of future indoor and GPS-obstructed environments. Copyright © 2018, The Authors. All rights reserved.

关键词： Location based services

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Detection of Double JPEG Compression with the Same Quantization Matrix Based on Convolutional Neural Networks

Detection of Double JPEG Compression with the Same Quantizat...

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Peng Peng Tanfeng Sun Xinghao Jiang Ke Xu Bin Li Yunqing Shi School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Shenzhen Key Laboratory of Media Security Shenzhen China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark USA

ISBN: (纸本)9781728102436;9789881476852

The detection of double JPEG compression with the same quantization matrix is a challenging problem in image forensics. In this paper, a CNN framework is proposed to solve this problem. This framework contains a preprocessing layer and a well-designed CNN. In the preprocessing layer, the rounding and truncation error images are extracted from continuous recompressed input samples and then fed into the following CNN. In the design of the CNN architecture, several advanced techniques are carefully considered to prevent overfitting, such as 1×1 convolutional kernel and global average pooling layer. The performance of proposed framework is evaluated on the public available image dataset (BOSSbase) with various quality factors (QF). Experimental results have shown the proposed CNN framework performs better than the state-of-the-art method based on hand-crafted features.

关键词： Transform coding Image coding Quantization (signal) Discrete cosine transforms Finite wordlength effects Kernel Digital images

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Fog-assisted multi-user swipt networks: Local computing or offloading

arXiv

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arXiv 2019年

作者： Zheng, Haina Xiong, Ke Fan, Pingyi Zhong, Zhangdui Letaief, Khaled Ben School of Computer and Information Technology Beijing Key Lab of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing China Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing100044 China National Laboratory for Information Science and Technology Department of Electronic Engineering Tsinghua University Beijing100084 China State Key Lab of Rail Traffic Control and Safety Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Clear Water Bay Hong Kong

This paper investigates a fog computing-assisted multi-user simultaneous wireless information and power transfer (SWIPT) network, where multiple sensors with power splitting (PS) receiver architectures receive information and harvest energy from a hybrid access point (HAP), and then process the received data by using local computing mode or fog offloading mode. For such a system, an optimization problem is formulated to minimize the sensors' required energy while guaranteeing their required information transmissions and processing rates by jointly optimizing the multi-user scheduling, the time assignment, the sensors' transmit powers and the PS ratios. Since the problem is a mixed integer programming (MIP) problem and cannot be solved with existing solution methods, we solve it by applying problem decomposition, variable substitutions and theoretical analysis. For a scheduled sensor, the closed-form and semi-closedform solutions to achieve its minimal required energy are derived, and then an efficient multi-user scheduling scheme is presented, which can achieve the suboptimal user scheduling with low computational complexity. Numerical results demonstrate our obtained theoretical results, which show that for each sensor, when it is located close to the HAP or the fog server (FS), the fog offloading mode is the better choice;otherwise, the local computing mode should be selected. The system performances in a frame-by-frame manner are also simulated, which show that using the energy stored in the batteries and that harvested from the signals transmitted by previous scheduled sensors can further decrease the total required energy of the sensors. Copyright © 2019, The Authors. All rights reserved.

关键词： Energy harvesting

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Local distinguishability of orthogonal quantum states with multiple copies of 2⊗2 maximally entangled states

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Physical Review A 2018年第2期97卷 022334-022334页

作者： Zhi-Chao Zhang Yan-Qi Song Ting-Ting Song Fei Gao Su-Juan Qin Qiao-Yan Wen State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing 100876 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 China Department of Computer Science College of Information Science and Technology Jinan University Guangzhou 510632 China

For general quantum systems, many sets of locally indistinguishable orthogonal quantum states have been constructed so far. However, it is interesting how much entanglement resources are sufficient and/or necessary to distinguish these states by local operations and classical communication (LOCC). Here we first present a method to locally distinguish a set of orthogonal product states in 5⊗5 by using two copies of 2⊗2 maximally entangled states. Then we generalize the distinguishing method for a class of orthogonal product states in d⊗d (d is odd). Furthermore, for a class of nonlocality of orthogonal product states in d⊗d (d≥5), we prove that these states can be distinguished by LOCC with two copies of 2⊗2 maximally entangled states. Finally, for some multipartite orthogonal product states, we also present a similar method to locally distinguish these states with multiple copies of 2⊗2 maximally entangled states. These results also reveal the phenomenon of less nonlocality with more entanglement.

关键词： Nonlocality Quantum cryptography Quantum entanglement

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Unsupervised resource-free entity discovery and linking in natural language questions

Unsupervised resource-free entity discovery and linking in n...

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2017 Evaluation Task at the China Conference on Knowledge Graph and Semantic Computing, CCKS-Tasks 2017

作者： Guo, Shu Cao, Jiangxia Wang, Quan Wang, Lihong Wang, Bin Institute of Information Engineering Chinese Academy of Sciences China School of Cyber Security University of Chinese Academy of Sciences China School of Computer Scince and Technology Heilongjiang University China National Computer Network Emergency Response Technical Team Coordination Center of China China

We present the solution to the CCKS 2017 question entity discovery and linking (QEDL) task. This task is to discover and link entity mentions in natural language questions with their referent entities in a knowledge base (KB). For entity discovery, we devise recognition patterns based on word segmentation and POS tagging. For entity linking, we leverage contextual similarity refined by rich side information contained in the KB. Our solution is fully unsupervised and resource-free, requiring neither labeled data nor auxiliary resources. Experimental results show that our solution is simple yet effective, achieving an F1-score of 44.3% which ranks the third in the QEDL task.

关键词： Knowledge based systems

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