Web Security Project List


Abstract: Chronic obstructive pulmonary disease (COPD) is a chronic lung disease that causes a progressive decline in respiratory function. Diagnosing COPD in the early curable stages is very important and may even save the life of a patient. In this paper, we present an integrated model for diagnosing COPD based on a knowledge graph. First, we construct a knowledge graph of COPD to analyze the relationship between feature subsets and further discover the knowledge of implied diseases from the data. Second, we propose an algorithm for sorting features and an adaptive feature subset selection algorithm CMFS-η, which selects an optimal subset of features from the original high-dimensional set. Finally, the DSA-SVM integrated model is suggested to build the classifier for the diagnosis and prediction of COPD. We performed extensive experiments on the dataset from the hospital outpatient electronic medical record database. The classification accuracy of our method was 95.1%. It is superior to some

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Abstract: Accurate comparison of contactless 2D fingerprint images with contact-based fingerprints is critical for the success of emerging contactless 2D fingerprint technologies, which offer more hygienic and deformation-free acquisition of fingerprint features. Convolutional neural networks (CNN) have shown remarkable capabilities in biometrics recognition. However, there has been almost nil attempt to match fingerprint images using CNNbased approaches. This paper develops a CNN-based framework to accurately match contactless and contact-based fingerprint images. Our framework firstly trains a multi-Siamese CNN using fingerprint minutiae, respective ridge map and specific region of ridge map. This network is used to generate deep fingerprint representation using a distance-aware loss function. Deep fingerprint representations generated in such multi-Siamese network are concatenated for more accurate cross comparison. The proposed approach for cross-fingerprint comparison is

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Abstract: —Caricatures refer to a representation of a person in which the distinctive features are deliberately exaggerated, with several studies showing that humans perform better at recognizing people from caricatures than using original images. Inspired by this observation, this paper introduces the first fully automated caricature-based face recognition approach capable of working with data acquired in the wild. Our approach leverages the 3D face structure from a single 2D image and compares it to a reference model for obtaining a compact representation of face features deviations. This descriptor is subsequently deformed using a ’measure locally, weight globally’ strategy to resemble the caricature drawing process. The deformed deviations are incorporated in the 3D model using the Laplacian mesh deformation algorithm, and the 2D face caricature image is obtained by projecting the deformed model in the original camera-view. To demonstrate the advantages of caricatur

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Abstract: Secure password storage is a vital aspect in systems based on password authentication, which is still the most widely used authentication technique, despite its some security flaws. In this paper, we propose a password authentication framework that is designed for secure password storage and could be easily integrated into existing authentication systems. In our framework, first, the received plain password from a client is hashed through a cryptographic hash function (e.g., SHA-256). Then, the hashed password is converted into a negative password. Finally, the negative password is encrypted into an Encrypted Negative Password (abbreviated as ENP) using a symmetric-key algorithm (e.g., AES), and multi-iteration encryption could be employed to further improve security. The cryptographic hash function and symmetric encryption make it difficult to crack passwords from ENPs. Moreover, there are lots of corresponding ENPs for a given plain password, which makes precomput

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Abstract: To keep password users from creating simple and common passwords, major websites and applications provide a password-strength measure, namely a password checker. While critical requirements for a password checker to be stringent have prevailed in the study of password security, we show that regardless of the stringency, such static checkers can leak information and actually help the adversary enhance the performance of their attacks. To address this weakness, we propose and devise the Dynamic Password Policy Generator, namely DPPG, to be an effective and usable alternative to the existing password strength checker. DPPG aims to enforce an evenly-distributed password space and generate dynamic policies for users to create passwords that are diverse and that contribute to the overall security of the password database. Since DPPG is modular and can function with different underlying metrics for policy generation, we further introduce a diversity-based password securi

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Abstract: —Conventional password-based authentication is considered inadequate by users as many online services started to affect each other. Online credentials are used to recover other credentials and complex attacks are directed to the weakest one of many of these online credentials. As researchers are looking for new authentication techniques, one time passwords, which is a two-factor authentication scheme, looks like a natural enhancement over conventional username/password schemes. The manuscript places the OTP verifier to the cloud to ease adoption of its usage by cloud service providers. When the OTP verifier is placed on the cloud as a service, other cloud service providers could outsource their OTP deployments as well as cloud users could activate their respective account on the OTP provider on several cloud services. This enables them to use several cloud services without the difficulty of managing several OTP accounts for each cloud service. On the other hand, O

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Abstract: Spectrum auction is an effective way to redistribute scarce spectrum resources. However, most spectrum auction design only target at economic robustness, while neglecting the inherent privacy leakage problem. Existing secure spectrum auction mechanisms fail to provide adequate security, and they all neglect the online fashion of spectrum request arrival. In this paper, for the first time, we propose a Privacy-preserving and truthful Online double auction mechanism for Spectrum allocation in wireless networks, PROST. Compared with the state-of- the-art solutions, PROST provides a comprehensive and strong protection for users’ sensitive information, especially for location privacy and time dynamics. PROST is constructed based on our carefully-designed security building blocks, which support various arithmetics over encrypted real numbers, and they are also well applicable in other spectrum auctions. Besides,we improve on existing online spectrum auction mechanisms by designing a novel

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Abstract: Application layer distributed denial of service (DDoS) attacks have become a severe threat to the security of web servers. These attacks evade most intrusion prevention systems by sending numerous benign HTTP requests. Since most of these attacks are launched abruptly and severely, a fast intrusion prevention system is desirable to detect and mitigate these attacks as soon as possible. In this paper, we propose an effective defense system, named SkyShield, which leverages the sketch data structure to quickly detect and mitigate application layer DDoS attacks. First, we propose a novel calculation of the divergence between two sketches, which alleviates the impact of network dynamics and improves the detection accuracy. Second, we utilize the abnormal sketch to facilitate the identification of malicious hosts of an ongoing attack. This improves the efficiency of SkyShield by avoiding the reverse calculation of malicious hosts. We have developed a prototype of SkyShie

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