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Computer Science Faculty Publications

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Full-Text Articles in Information Security

Dial "N" For Nxdomain: The Scale, Origin, And Security Implications Of Dns Queries To Non-Existent Domains, Gunnan Liu, Lin Jin, Shuai Hao, Yubao Zhang, Daiping Liu, Angelos Stavrou, Haining Wang Jan 2023

Dial "N" For Nxdomain: The Scale, Origin, And Security Implications Of Dns Queries To Non-Existent Domains, Gunnan Liu, Lin Jin, Shuai Hao, Yubao Zhang, Daiping Liu, Angelos Stavrou, Haining Wang

Computer Science Faculty Publications

Non-Existent Domain (NXDomain) is one type of the Domain Name System (DNS) error responses, indicating that the queried domain name does not exist and cannot be resolved. Unfortunately, little research has focused on understanding why and how NXDomain responses are generated, utilized, and exploited. In this paper, we conduct the first comprehensive and systematic study on NXDomain by investigating its scale, origin, and security implications. Utilizing a large-scale passive DNS database, we identify 146,363,745,785 NXDomains queried by DNS users between 2014 and 2022. Within these 146 billion NXDomains, 91 million of them hold historic WHOIS records, of which 5.3 million …


Ready Raider One: Exploring The Misuse Of Cloud Gaming Services, Guannan Liu, Daiping Liu, Shuai Hao, Xing Gao, Kun Sun, Haining Wang Jan 2022

Ready Raider One: Exploring The Misuse Of Cloud Gaming Services, Guannan Liu, Daiping Liu, Shuai Hao, Xing Gao, Kun Sun, Haining Wang

Computer Science Faculty Publications

Cloud gaming has become an emerging computing paradigm in recent years, allowing computer games to offload complex graphics and logic computation to the cloud. To deliver a smooth and high-quality gaming experience, cloud gaming services have invested abundant computing resources in the cloud, including adequate CPUs, top-tier GPUs, and high-bandwidth Internet connections. Unfortunately, the abundant computing resources offered by cloud gaming are vulnerable to misuse and exploitation for malicious purposes. In this paper, we present an in-depth study on security vulnerabilities in cloud gaming services. Specifically, we reveal that adversaries can purposely inject malicious programs/URLs into the cloud gaming services …


Camouflaged Poisoning Attack On Graph Neural Networks, Chao Jiang, Yi He, Richard Chapman, Hongyi Wu Jan 2022

Camouflaged Poisoning Attack On Graph Neural Networks, Chao Jiang, Yi He, Richard Chapman, Hongyi Wu

Computer Science Faculty Publications

Graph neural networks (GNNs) have enabled the automation of many web applications that entail node classification on graphs, such as scam detection in social media and event prediction in service networks. Nevertheless, recent studies revealed that the GNNs are vulnerable to adversarial attacks, where feeding GNNs with poisoned data at training time can lead them to yield catastrophically devastative test accuracy. This finding heats up the frontier of attacks and defenses against GNNs. However, the prior studies mainly posit that the adversaries can enjoy free access to manipulate the original graph, while obtaining such access could be too costly in …


How Secure Having Iot Devices In Our Homes?, Debora Estrada, Lo'ai A. Tawalbeh, Robert Vinaja Mar 2020

How Secure Having Iot Devices In Our Homes?, Debora Estrada, Lo'ai A. Tawalbeh, Robert Vinaja

Computer Science Faculty Publications

Nowadays, technology has evolved to be in our daily lives to assist in making our lives easier. We now have technology helping us in our lives at home. Devices used to create our “smart home” have done a great deal in making our lives at home less burdensome, but sadly, these devices have secured our personal lives to be more accessible to outsiders. In this paper, the security of home smart devices and their communication will be researched by using other academic articles to support facts found. The operation of the devices will be discussed along with security risks and …


Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework, Nir Nissim, Aviad Cohen, Jian Wu, Andrea Lanzi, Lior Rokach, Yuval Elovici, Lee Giles Jan 2019

Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework, Nir Nissim, Aviad Cohen, Jian Wu, Andrea Lanzi, Lior Rokach, Yuval Elovici, Lee Giles

Computer Science Faculty Publications

Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles' files safe and thus open PDF-files with little concern. In addition, researchers consider scholarly libraries a reliable, trusted, and untainted corpus of papers. For these reasons, scholarly digital libraries are an attractive-target and inadvertently support the proliferation of cyber-attacks launched via malicious PDF-files. In this study, we present related vulnerabilities and malware distribution approaches that exploit the vulnerabilities of scholarly digital libraries. We evaluated over two-million scholarly papers in the CiteSeerX library and found the library …


An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang Dec 2015

An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang

Computer Science Faculty Publications

We present a tele-immersive system that enables people to interact with each other in a virtual world using body gestures in addition to verbal communication. Beyond the obvious applications, including general online conversations and gaming, we hypothesize that our proposed system would be particularly beneficial to education by offering rich visual contents and interactivity. One distinct feature is the integration of egocentric pose recognition that allows participants to use their gestures to demonstrate and manipulate virtual objects simultaneously. This functionality enables the instructor to effectively and efficiently explain and illustrate complex concepts or sophisticated problems in an intuitive manner. The …


Automatic Video Self Modeling For Voice Disorder, Ju Shen, Changpeng Ti, Anusha Raghunathan, Sen-Ching S. Cheung, Rita Patel Jul 2015

Automatic Video Self Modeling For Voice Disorder, Ju Shen, Changpeng Ti, Anusha Raghunathan, Sen-Ching S. Cheung, Rita Patel

Computer Science Faculty Publications

Video self modeling (VSM) is a behavioral intervention technique in which a learner models a target behavior by watching a video of him- or herself. In the field of speech language pathology, the approach of VSM has been successfully used for treatment of language in children with Autism and in individuals with fluency disorder of stuttering. Technical challenges remain in creating VSM contents that depict previously unseen behaviors. In this paper, we propose a novel system that synthesizes new video sequences for VSM treatment of patients with voice disorders. Starting with a video recording of a voice-disorder patient, the proposed …


Compression Of Video Tracking And Bandwidth Balancing Routing In Wireless Multimedia Sensor Networks, Yin Wang, Jianjun Yang, Ju Shen, Bryson Payne, Juan Guo, Kun Hua May 2015

Compression Of Video Tracking And Bandwidth Balancing Routing In Wireless Multimedia Sensor Networks, Yin Wang, Jianjun Yang, Ju Shen, Bryson Payne, Juan Guo, Kun Hua

Computer Science Faculty Publications

There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs) have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select …


Leading Undergraduate Students To Big Data Generation, Jianjun Yang, Ju Shen Mar 2015

Leading Undergraduate Students To Big Data Generation, Jianjun Yang, Ju Shen

Computer Science Faculty Publications

People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking, image processing, virtualization, scientific computation, and algorithms. The huge data nowadays are called Big Data. Big data is an all encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students hands-on …


Hole Detection And Shape-Free Representation And Double Landmarks Based Geographic Routing In Wireless Sensor Networks, Jianjun Yang, Zongming Fei, Ju Shen Feb 2015

Hole Detection And Shape-Free Representation And Double Landmarks Based Geographic Routing In Wireless Sensor Networks, Jianjun Yang, Zongming Fei, Ju Shen

Computer Science Faculty Publications

In wireless sensor networks, an important issue of geographic routing is “local minimum” problem, which is caused by a “hole” that blocks the greedy forwarding process. Existing geographic routing algorithms use perimeter routing strategies to find a long detour path when such a situation occurs. To avoid the long detour path, recent research focuses on detecting the hole in advance, then the nodes located on the boundary of the hole advertise the hole information to the nodes near the hole. Hence the long detour path can be avoided in future routing. We propose a heuristic hole detecting algorithm which identifies …


Structure Preserving Large Imagery Reconstruction, Ju Shen, Jianjun Yang, Sami Taha Abu Sneineh, Bryson Payne, Markus Hitz Jul 2014

Structure Preserving Large Imagery Reconstruction, Ju Shen, Jianjun Yang, Sami Taha Abu Sneineh, Bryson Payne, Markus Hitz

Computer Science Faculty Publications

With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet. We can trivially collect a huge number of photo streams for various goals, such as image clustering, 3D scene reconstruction, and other big data applications. However, such tasks are not easy due to the fact the retrieved photos can have large variations in their view perspectives, resolutions, lighting, noises, and distortions. Furthermore, with the occlusion of unexpected objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image …


Automatic Objects Removal For Scene Completion, Jianjun Yang, Yin Wang, Honggang Wang, Kun Hua, Wei Wang, Ju Shen Apr 2014

Automatic Objects Removal For Scene Completion, Jianjun Yang, Yin Wang, Honggang Wang, Kun Hua, Wei Wang, Ju Shen

Computer Science Faculty Publications

With the explosive growth of Web-based cameras and mobile devices, billions of photographs are uploaded to the Internet. We can trivially collect a huge number of photo streams for various goals, such as 3D scene reconstruction and other big data applications. However, this is not an easy task due to the fact the retrieved photos are neither aligned nor calibrated. Furthermore, with the occlusion of unexpected foreground objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image completion algorithm for object removal that produces visually …


A Robust Rgbd Slam System For 3d Environment With Planar Surfaces, Po-Chang Su, Ju Shen, Sen-Ching S. Cheung Sep 2013

A Robust Rgbd Slam System For 3d Environment With Planar Surfaces, Po-Chang Su, Ju Shen, Sen-Ching S. Cheung

Computer Science Faculty Publications

With the increasing popularity of RGB-depth (RGB-D) sensors such as the Microsoft Kinect, there have been much research on capturing and reconstructing 3D environments using a movable RGB-D sensor. The key process behind these kinds of simultaneous location and mapping (SLAM) systems is the iterative closest point or ICP algorithm, which is an iterative algorithm that can estimate the rigid movement of the camera based on the captured 3D point clouds. While ICP is a well-studied algorithm, it is problematic when it is used in scanning large planar regions such as wall surfaces in a room. The lack of depth …


Warcreate And Wail: Warc, Wayback, And Heritrix Made Easy, Mat Kelly, Michael L. Nelson, Michele C. Weigle Jan 2013

Warcreate And Wail: Warc, Wayback, And Heritrix Made Easy, Mat Kelly, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

[First slide]

The Problem

Institutional Tools, Personal Archivists

  • ON YOUR MACHINE

-Complex to Operate

-Require Infrastructure

  • DELEGATED TO INSTITUTIONS

-$$$

-Lose original perspective

  • Locale content tailoring (DC vs. San Francisco)
  • Observation Medium (PC web browser vs. Crawler)


Stochastic Analysis Of Horizontal Ip Scanning, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov Mar 2012

Stochastic Analysis Of Horizontal Ip Scanning, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov

Computer Science Faculty Publications

Intrusion Detection Systems (IDS) have become ubiquitous in the defense against virus outbreaks, malicious exploits of OS vulnerabilities, and botnet proliferation. As attackers frequently rely on host scanning for reconnaissance leading to penetration, IDS is often tasked with detecting scans and preventing them. However, it is currently unknown how likely an IDS is to detect a given Internet-wide scan pattern and whether there exist sufficiently fast scan techniques that can remain virtually undetectable at large-scale. To address these questions, we propose a simple analytical model for the window-expiration rules of popular IDS tools (i.e., Snort and Bro) and utilize a …


Warcreate - Create Wayback-Consumable Warc Files From Any Webpage, Mat Kelly, Michele C. Weigle, Michael L. Nelson Jan 2012

Warcreate - Create Wayback-Consumable Warc Files From Any Webpage, Mat Kelly, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

[First Slide]

What is WARCreate?

  • Google Chrome extension
  • Creates WARC files
  • Enables preservation by users from their browser
  • First steps in bringing Institutional Archiving facilities to the PC


Automatic Content Generation For Video Self Modeling, Ju Shen, Anusha Raghunathan, Sen-Ching S. Cheung, Ravi R. Patel Jul 2011

Automatic Content Generation For Video Self Modeling, Ju Shen, Anusha Raghunathan, Sen-Ching S. Cheung, Ravi R. Patel

Computer Science Faculty Publications

Video self modeling (VSM) is a behavioral intervention technique in which a learner models a target behavior by watching a video of him or herself. Its effectiveness in rehabilitation and education has been repeatedly demonstrated but technical challenges remain in creating video contents that depict previously unseen behaviors. In this paper, we propose a novel system that re-renders new talking-head sequences suitable to be used for VSM treatment of patients with voice disorder. After the raw footage is captured, a new speech track is either synthesized using text-to-speech or selected based on voice similarity from a database of clean speeches. …


Program Transformations For Information Personalization, Saverio Perugini, Naren Ramakrishnan Oct 2010

Program Transformations For Information Personalization, Saverio Perugini, Naren Ramakrishnan

Computer Science Faculty Publications

Personalization constitutes the mechanisms necessary to automatically customize information content, structure, and presentation to the end user to reduce information overload. Unlike traditional approaches to personalization, the central theme of our approach is to model a website as a program and conduct website transformation for personalization by program transformation (e.g., partial evaluation, program slicing). The goal of this paper is study personalization through a program transformation lens and develop a formal model, based on program transformations, for personalized interaction with hierarchical hypermedia. The specific research issues addressed involve identifying and developing program representations and transformations suitable for classes of hierarchical …


Personalization By Website Transformation: Theory And Practice, Saverio Perugini May 2010

Personalization By Website Transformation: Theory And Practice, Saverio Perugini

Computer Science Faculty Publications

We present an analysis of a progressive series of out-of-turn transformations on a hierarchical website to personalize a user’s interaction with the site. We formalize the transformation in graph-theoretic terms and describe a toolkit we built that enumerates all of the traversals enabled by every possible complete series of these transformations in any site and computes a variety of metrics while simulating each traversal therein to qualify the relationship between a site’s structure and the cumulative effect of support for the transformation in a site. We employed this toolkit in two websites. The results indicate that the transformation enables users …


Robust Lifetime Measurement In Large-Scale P2p Systems With Non-Stationary Arrivals, Xiaoming Wang, Zhongmei Yao, Yueping Zhang, Dmitri Loguinov Sep 2009

Robust Lifetime Measurement In Large-Scale P2p Systems With Non-Stationary Arrivals, Xiaoming Wang, Zhongmei Yao, Yueping Zhang, Dmitri Loguinov

Computer Science Faculty Publications

Characterizing user churn has become an important topic in studying P2P networks, both in theoretical analysis and system design. Recent work has shown that direct sampling of user lifetimes may lead to certain bias (arising from missed peers and round-off inconsistencies) and proposed a technique that estimates lifetimes based on sampled residuals. In this paper, however, we show that under non-stationary arrivals, which are often present in real systems, residual-based sampling does not correctly reconstruct user lifetimes and suffers a varying degree of bias, which in some cases makes estimation completely impossible. We overcome this problem using two contributions: a …


Multicast Encryption Infrastructure For Security In Sensor Networks, Richard R. Brooks, Brijesh Pillai, Matthew Pirretti, Michele C. Weigle Jan 2009

Multicast Encryption Infrastructure For Security In Sensor Networks, Richard R. Brooks, Brijesh Pillai, Matthew Pirretti, Michele C. Weigle

Computer Science Faculty Publications

Designing secure sensor networks is difficult. We propose an approach that uses multicast communications and requires fewer encryptions than pairwise communications. The network is partitioned into multicast regions; each region is managed by a sensor node chosen to act as a keyserver. The keyservers solicit nodes in their neighborhood to join the local multicast tree. The keyserver generates a binary tree of keys to maintain communication within the multicast region using a shared key. Our approach supports a distributed key agreement protocol that identifies the compromised keys and supports membership changes with minimum system overhead. We evaluate the overhead of …


User Interface Design, Moritz Stefaner, Sebastien Ferre, Saverio Perugini, Jonathan Koren, Yi Zhang Jan 2009

User Interface Design, Moritz Stefaner, Sebastien Ferre, Saverio Perugini, Jonathan Koren, Yi Zhang

Computer Science Faculty Publications

As detailed in Chap. 1, system implementations for dynamic taxonomies and faceted search allow a wide range of query possibilities on the data. Only when these are made accessible by appropriate user interfaces, the resulting applications can support a variety of search, browsing and analysis tasks. User interface design in this area is confronted with specific challenges. This chapter presents an overview of both established and novel principles and solutions.


Providing Vanet Security Through Active Position Detection, Gongjun Yan, Gyanesh Choudhary, Michele C. Weigle, Stephan Olariu Jan 2007

Providing Vanet Security Through Active Position Detection, Gongjun Yan, Gyanesh Choudhary, Michele C. Weigle, Stephan Olariu

Computer Science Faculty Publications

Our main contribution is a novel approach to enhancing position security in VANET. We achieve local and global position security by using the on-board radar to detect neighboring vehicles and to confirm their announced coordinates. We compute cosine similarity among data collected by radar and neighbors' reports to filter the forged data from the truthful data. Based on filtered data, we create a history of vehicle movement. By checking the history and computing similarity, we can prevent a large number of Sybil attacks and some combinations of Sybil and position-based attacks.


Modeling Heterogeneous User Churn And Local Resilience Of Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov, Xiaoming Wang Nov 2006

Modeling Heterogeneous User Churn And Local Resilience Of Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov, Xiaoming Wang

Computer Science Faculty Publications

Previous analytical results on the resilience of unstructured P2P systems have not explicitly modeled heterogeneity of user churn (i.e., difference in online behavior) or the impact of in-degree on system resilience. To overcome these limitations, we introduce a generic model of heterogeneous user churn, derive the distribution of the various metrics observed in prior experimental studies (e.g., lifetime distribution of joining users, joint distribution of session time of alive peers, and residual lifetime of a randomly selected user), derive several closed-form results on the transient behavior of in-degree, and eventually obtain the joint in/out degree isolation probability as a simple …


Information Assurance Through Binary Vulnerability Auditing, William B. Kimball, Saverio Perugini Jan 2006

Information Assurance Through Binary Vulnerability Auditing, William B. Kimball, Saverio Perugini

Computer Science Faculty Publications

The goal of this research is to develop improved methods of discovering vulnerabilities in software. A large volume of software, from the most frequently used programs on a desktop computer, such as web browsers, e-mail programs, and word processing applications, to mission-critical services for the space shuttle, is unintentionally vulnerable to attacks and thus insecure. By seeking to improve the identification of vulnerabilities in software, the security community can save the time and money necessary to restore compromised computer systems. In addition, this research is imperative to activities of national security such as counterterrorism. The current approach involves a systematic …


On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov Nov 2005

On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov

Computer Science Faculty Publications

In this paper, we analyze the problem of network disconnection in the context of large-scale P2P networks and understand how both static and dynamic patterns of node failure affect the resilience of such graphs. We start by applying classical results from random graph theory to show that a large variety of deterministic and random P2P graphs almost surely (i.e., with probability 1-o(1)) remain connected under random failure if and only if they have no isolated nodes. This simple, yet powerful, result subsequently allows us to derive in closed-form the probability that a P2P network develops isolated nodes, and therefore partitions, …


Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao Jun 2005

Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao

Computer Science Faculty Publications

Clustering is well-suited for Web mining by automatically organizing Web pages into categories, each of which contains Web pages having similar contents. However, one problem in clustering is the lack of general methods to automatically determine the number of categories or clusters. For the Web domain in particular, currently there is no such method suitable for Web page clustering. In an attempt to address this problem, we discover a constant factor that characterizes the Web domain, based on which we propose a new method for automatically determining the number of clusters in Web page data sets. We discover that the …


Recommender Systems Research: A Connection-Centric Survey, Saverio Perugini, Marcos André Gonçalves, Edward A. Fox Sep 2004

Recommender Systems Research: A Connection-Centric Survey, Saverio Perugini, Marcos André Gonçalves, Edward A. Fox

Computer Science Faculty Publications

Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from …