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| 1 | NEXT:a neural network framework for next POI recommendation显示文摘The task of next POI recommendations has been studied extensively in recent years.However,developing a unified recommendation framework to incorporate multiple factors associated with both POIs and users remains challenging,because of the heterogeneity nature of these information.Further,effective mechanisms to smoothly handle cold-start cases are also a difficult topic.Inspired by the recent success of neural networks in many areas,in this paper,we propose a simple yet effective neural network framework,named NEXT,for next POI recommendations.NEXT is a unified framework to learn the hidden intent regarding user's next move,by incorporating different factors in a unified manner.Specifically,in NEXT,we incorporate meta-data information,e.g.,user friendship and textual descriptions of POIs,and two kinds of temporal contexts(i.e.,time interval and visit time).To leverage sequential relations and geographical influence,we propose to adopt DeepWalk,a network representation learning technique,to encode such knowledge.We evaluate the effectiveness of NEXT against other state-of-the-art alternatives and neural networks based solutions.Experimental results on three publicly available datasets demonstrate that NEXT significantly outperforms baselines in real-time next POI recommendations.Further experiments show inherent ability of NEXT in handling cold-start. | Zhiqian ZHANG Chenliang LI Zhiyong WU Aixin SUN Dengpan YE Xiangyang LUO | 2020 | Frontiers of Computer Science2020，14，2： | 5 |
| 2 | Defend Against Adversarial Samples by Using Perceptual Hash显示文摘Image classifiers that based on Deep Neural Networks(DNNs)have been proved to be easily fooled by well-designed perturbations.Previous defense methods have the limitations of requiring expensive computation or reducing the accuracy of the image classifiers.In this paper,we propose a novel defense method which based on perceptual hash.Our main goal is to destroy the process of perturbations generation by comparing the similarities of images thus achieve the purpose of defense.To verify our idea,we defended against two main attack methods(a white-box attack and a black-box attack)in different DNN-based image classifiers and show that,after using our defense method,the attack-success-rate for all DNN-based image classifiers decreases significantly.More specifically,for the white-box attack,the attack-success-rate is reduced by an average of 36.3%.For the black-box attack,the average attack-success-rate of targeted attack and non-targeted attack has been reduced by 72.8%and 76.7%respectively.The proposed method is a simple and effective defense method and provides a new way to defend against adversarial samples. | Changrui Liu Dengpan Ye Yueyun Shang Shunzhi Jiang Shiyu Li Yuan Mei Liqiang Wang | 2020 | Computers, Materials & Continua2020，，3： | 1 |
| 3 | A Specific Steganalysis Approach to Effective Attacking the MB1显示文摘 | HU Donghui HU Donghui WANG Lina WANG Lina JIANG Xiaqiu JIANG Xiaqiu YE Dengpan YE Dengpan LIAN Shiguo LIAN Shiguo | 2009 | Chinese Journal of Electronics2009，18，4： | 1 |
| 4 | Delay-Distance Correlation Study for IP Geolocation显示文摘Although many classical IP geolocation algorithms are suitable to rich-connected networks,their performances are seriously affected in poor-connected networks with weak delay-distance correlation. This paper tries to improve the performances of classical IP geolocation algorithms by finding rich-connected sub-networks inside poor-connected networks. First,a new delay-distance correlation model(RTD-Corr model)is proposed. It builds the relationship between delay-distance correlation and actual network factors such as the tortuosity of the network path and the ratio of propagation delay. Second,based on the RTD-Corr model and actual network characteristics,this paper discusses about how to find rich-connected networks inside China Internet which is a typical actual poor-connected network. Then we find rich-connected sub-networks of China Internet through a large-scale network measurement which covers three major ISPs and thirty provinces. At last,based on the founded rich-connected sub-networks,we modify two classical IP geolocation algorithms and the experiments in China Internet show that their accuracy is significantly increased. | DING Shichang LUO Xiangyang YE Dengpan LIU Fenlin | 2017 | Wuhan University Journal of Natural Sciences2017，22，2： | 1 |
| 5 | Novel encryption model for multimedia data显示文摘A novel encryption model is proposed.It combines encryption process with compression process,and realizes compression and encryption at the same time.The model's feasibility and security are analyzed in detail. And the relationship between its security and compression ratio is also analyzed. | Ye Dengpan~(1,2) & Lian Shiguo~3 1.The Key Laboratory of Aerospace Information Security and Trust Computing,Ministry of Education,Wuhan 430072,P.R.China 2.School of Computer Science,Wuhan Univ.,Wuhan 430072,P.R.China 3.France Telecom R&D Beijing,Beijing 100080,P.R.China | 2009 | Journal of Systems Engineering and Electronics2009，20，5： | 1 |
| 6 | An Image Steganography Algorithm Based on Quantization Index Modulation Resisting Scaling Attacks and Statistical Detection显示文摘In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method,this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection.For the spatial image,this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain.Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography,and use the minimum distortion coding to realize the embedding of the secret messages.Finally,according to the embedding modification amplitude of secret messages in the new embedded domain,the quantization index modulation algorithm is applied to realize the final embedding of secret messages in the original embedded domain.The experimental results show that the algorithm proposed is robust to the three common interpolation attacks including the nearest neighbor interpolation,the bilinear interpolation and the bicubic interpolation.And the average correct extraction rate of embedded messages increases from 50%to over 93% after 0.5 times-fold scaling attack using the bicubic interpolation method,compared with the classical steganography algorithm S-UNIWARD.Also the algorithm proposed has higher detection resistance than the original watermarking algorithm based on quantization index modulation. | Yue Zhang Dengpan Ye Junjun Gan Zhenyu Li Qingfeng Cheng | 2018 | Computers, Materials & Continua2018，，7： | 0 |
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