Computer Sciences Commons^™

Machine Learning Based Approaches Towards Robust Android Malware Detection, Jiayun Xu

Dissertations and Theses Collection (Open Access)

The Android platform is becoming increasingly popular and numerous applications (apps) have been developed by organizations to meet the ever increasing market demand over years. Naturally, security and privacy concerns on Android apps have grabbed considerable attention from both academic and industrial
communities. Many approaches have been proposed to detect Android malware in different ways so far, and most of them produce satisfactory performance under the given Android environment settings and labelled samples. However, existing approaches suffer the following robustness problems:

In many Android malware detection approaches, specific API calls are used to build the feature sets, and their feature …

Looking Back! Using Early Versions Of Android Apps As Attack Vectors, Yue Zhang, Jian Weng, Jia-Si Wneg, Lin Hou, Anjia Yang, Ming Li, Yang Xiang, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Android platform is gaining explosive popularity. This leads developers to invest resources to maintain the upward trajectory of the demand. Unfortunately, as the profit potential grows higher, the chances of these Apps getting attacked also get higher. Therefore, developers improved the security of their Apps, which limits attackers ability to compromise upgraded versions of the Apps. However, developers cannot enhance the security of earlier versions that have been released on the Play Store. The earlier versions of the App can be subject to reverse engineering and other attacks. In this paper, we find that attackers can use these earlier versions …

Do Users Care About Ad's Performance Costs? Exploring The Effects Of The Performance Costs Of In-App Ads On User Experience, Cuiyun Gao, Jichuan Zeng, Federica Sarro, David Lo, Irwin King, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Context: In-app advertising is the primary source of revenue for many mobile apps. The cost of advertising (ad cost) is non-negligible for app developers to ensure a good user experience and continuous profits. Previous studies mainly focus on addressing the hidden performance costs generated by ads, including consumption of memory, CPU, data traffic, and battery. However, there is no research on analyzing users’ perceptions of ads’ performance costs to our knowledge.Objective: To fill this gap and better understand the effects of performance costs of in-app ads on user experience, we conduct a study on analyzing user concerns about ads’ performance …

How Successful Are Open Source Contributions From Countries With Different Levels Of Human Development?, Leonardo Furtado, Bruno Cartaxo, Christoph Treude, Gustavo Pinto

Research Collection School Of Computing and Information Systems

In this article we studied whether developers? locations relate to the outcome of a pull request (PR). Our results suggest that developers from countries with low human development indexes perform a small fraction of the overall PRs and are the ones that face rejection the most.

Proximity-Based Video Communication With Cocktailparty, Addison Fabry, William Heffernan, Andrew Shroyer

Senior Theses

CocktailParty is a video communication application designed to uniquely and efficiently solve the problems faced by traditional online video communication. The proposal for this start-up project was accepted in August 2020. CocktailParty enables users to join a video chat room overlayed on top of a virtual house, in which each user can move their own video feed around the house. Each room in each house layout hosts a different video call, allowing users to easily host large virtual gatherings that facilitate multiple conversations taking place simultaneously. This functionality makes important steps towards effective simulation of the real-life gathering experience.

Best Practices In Industry And Cse Senior Design, Conner Hallett

Honors Program: Senior Projects (Public)

The widespread use of Agile practices in the software development industry creates the need for new college graduates to be adept in Agile processes and teams. The University of Nebraska-Lincoln’s Computer Science and Engineering (CSE) Senior Design courses gives students an introduction to such processes, but is met with many challenges in doing so, such as time constraints and student inexperience. Following a detailed look at the Scrum Agile framework and its expanded practices in industry, potential improvements for CSE Senior Design’s practice of Agile are suggested. These include the creation of resource forums for students to accelerate the early …

Practical Server-Side Wifi-Based Indoor Localization: Addressing Cardinality & Outlier Challenges For Improved Occupancy Estimation, Anuradha Ravi, Archan Misra

Research Collection School Of Computing and Information Systems

Server-side WiFi-based indoor localization offers a compelling approach for passive occupancy estimation (i.e., without requiring active participation by client devices, such as smartphones carried by visitors), but is known to suffer from median error of 6–8 meters. By analyzing the characteristics of an operationally-deployed, WiFi-based passive indoor location system, based on the classical RADAR algorithm, we identify and tackle 2 practical challenges for accurate individual device localization. The first challenge is the low-cardinality issue, whereby only the associated AP generates sufficiently frequent RSSI reports, causing a client to experience large localization error due to the absence of sufficient measurements from …

Out Of Sight, Out Of Mind? How Vulnerable Dependencies Affect Open-Source Projects, Gede Artha Azriadi Prana, Abhishek Sharma, Lwin Khin Shar, Darius Foo, Andrew E. Santosa, Asankhaya Sharma, David Lo

Research Collection School Of Computing and Information Systems

Context: Software developers often use open-source libraries in their project to improve development speed. However, such libraries may contain security vulnerabilities, and this has resulted in several high-profile incidents in re- cent years. As usage of open-source libraries grows, understanding of these dependency vulnerabilities becomes increasingly important. Objective: In this work, we analyze vulnerabilities in open-source libraries used by 450 software projects written in Java, Python, and Ruby. Our goal is to examine types, distribution, severity, and persistence of the vulnerabili- ties, along with relationships between their prevalence and project as well as commit attributes. Method: Our data is obtained …

Detection Of Social Identification In Workgroups From A Passively-Sensed Wifi Infrastructure, Camelia Zakaria, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Social identification: how much individuals psychologically associate themselves with a group has been posited as an essential construct to measure individual and group dynamics. Studies have shown that individuals who identify very differently from their workgroup provides critical cues to the lack of social support or work overloads. However, measuring identification is typically achieved through time-consuming and privacy invasive surveys. We hypothesize that the extremitized in-group norm affects individuals' behaviors, thus more likely to give rise to negative appraisals. As a more convenient and less-invasive technique, we propose a method to predict individuals who are increasingly different in identifying themselves …

Spectest: Specification-Based Compiler Testing, Richard Schumi, Jun Sun

Research Collection School Of Computing and Information Systems

Compilers are error-prone due to their high complexity. They are relevant for not only general purpose programming languages, but also for many domain specific languages. Bugs in compilers can potentially render all programs at risk. It is thus crucial that compilers are systematically tested, if not verified. Recently, a number of efforts have been made to formalise and standardise programming language semantics, which can be applied to verify the correctness of the respective compilers. In this work, we present a novel specification-based testing method named SpecTest to better utilise these semantics for testing. By applying an executable semantics as test …

Breaking Neural Reasoning Architectures With Metamorphic Relation-Based Adversarial Examples, Alvin Chan, Lei Ma, Felix Juefei-Xu, Yew-Soon Ong, Xiaofei Xie, Minhui Xue, Yang Liu

Research Collection School Of Computing and Information Systems

The ability to read, reason, and infer lies at the heart of neural reasoning architectures. After all, the ability to perform logical reasoning over language remains a coveted goal of Artificial Intelligence. To this end, models such as the Turing-complete differentiable neural computer (DNC) boast of real logical reasoning capabilities, along with the ability to reason beyond simple surface-level matching. In this brief, we propose the first probe into DNC's logical reasoning capabilities with a focus on text-based question answering (QA). More concretely, we propose a conceptually simple but effective adversarial attack based on metamorphic relations. Our proposed adversarial attack …

On-Device Deep Learning Inference For System-On-Chip (Soc) Architectures, Tom Springer, Elia Eiroa-Lledo, Elizabeth Stevens, Erik Linstead

Engineering Faculty Articles and Research

As machine learning becomes ubiquitous, the need to deploy models on real-time, embedded systems will become increasingly critical. This is especially true for deep learning solutions, whose large models pose interesting challenges for target architectures at the “edge” that are resource-constrained. The realization of machine learning, and deep learning, is being driven by the availability of specialized hardware, such as system-on-chip solutions, which provide some alleviation of constraints. Equally important, however, are the operating systems that run on this hardware, and specifically the ability to leverage commercial real-time operating systems which, unlike general purpose operating systems such as Linux, can …

Technological Countermeasures Of Copyright Piracy Enforcement In Nigeria: An Alternative To Creative Works Owners’ Livelihood In A Monolithic Economy Post Covid-19, Leonard Ume

Library Philosophy and Practice (e-journal)

The Coronavirus pandemic is a global problem that came with its attendant economic shock that is higher than the one brought by World War 1 and 2 put together. The attendant consequences expectedly landed Nigeria economy to recession. Nigeria over the years has been grappling with the problem of diversification of her economy to forestall the ugly impact of monolithic economy. This paper investigated the effect of using technology in fighting intellectual copyright piracy which will encourage the citizens to harness their creative endowment to eke out a living with its resultant effect on the reduction of unemployment. The study …

An Analysis Of Testing Scenarios For Automated Driving Systems, Luiz Fernando Capretz, Siyuan Liu

Electrical and Computer Engineering Publications

10.1109/SANER50967.2021.00078

Formal Verification For High Assurance Software: A Case Study Using The Spark Auto-Active Verification Toolset, Ryan M. Baity

Theses and Dissertations

Software is an increasingly integral and sophisticated part of safety- and mission-critical systems. Poorly written software can lead to information leakage, undetected cyber breaches, and even human injury in cases where the software directly interfaces with components of a physical system. These systems may range from power facilities to remotely piloted aircraft. Software bugs and vulnerabilities can lead to severe economic hardships and loss of life in these domains. As fast as software spreads to automate many facets of our lives, it also grows in complexity. The complexity of software systems combined with the nature of the critical domains dependent …

Two Published Flight Dynamics Models Rewritten In Rust And Structures As An Ecs, Chad A. Willis

Theses and Dissertations

This thesis explores using the Entity-Component System (ECS) architecture to implement a Flight Dynamics Model (FDM) by re-implementing two published versions in the Rust programming language using the Specs Parallel ECS (SPECS) [1] for military simulation advancement. One FDM is based on Grant Palmers published textbook titled Physics for Game Programmers [2], and another is based on David Bourgs textbook titled Physics for Game Developers [3]. Furthermore, this thesis uses these models within an interactive flight simulator.The ECS architecture is based on the Data-Oriented Design (DOD) paradigm, where Components contain the data and the Systems implement the behavior which transforms …

Assessing Code Clone Harmfulness: Indicators, Factors, And Counter Measures, Bin Hu, Yijian Wu, Xin Peng, Jun Sun, Nanjie Zhan, Jun Wu

Research Collection School Of Computing and Information Systems

Code clones are identical or similar code in software projects. On one hand, developers clone code to achieve higher productivity and thus clones inherently exist; on the other hand, code clones demand extra effort to maintain the consistency between clone instances and may introduce bugs, and thus are often considered harmful for software maintenance and quality. We believe that not all code clones have the same level of harmfulness. A systematic way of assessing the harmfulness level of cloned code would facilitate informed decisions on how to deal with clones. We propose a model for clone harmfulness level assessment with …

Improving Neural Network Verification Through Spurious Region Guided Refinement, Pengfei Yang, Renjue Li, Jianlin Li, Cheng Chao Huang, Jingyi Wang, Jun Sun, Bai Xue, Lijun Zhang

Research Collection School Of Computing and Information Systems

We propose a spurious region guided refinement approach for robustness verification of deep neural networks. Our method starts with applying the DeepPoly abstract domain to analyze the network. If the robustness property cannot be verified, the result is inconclusive. Due to the over-approximation, the computed region in the abstraction may be spurious in the sense that it does not contain any true counterexample. Our goal is to identify such spurious regions and use them to guide the abstraction refinement. The core idea is to make use of the obtained constraints of the abstraction to infer new bounds for the neurons. …

Interactional Motifs: Leveraging Risks In Large And Distributed Software Development Teams, Subhajit Datta, Amrita Bhattacharjee, Subhashis Majumder

Research Collection School Of Computing and Information Systems

DeMarco and Lister begin their classic Peopleware with an air of ominous inevitability “somewhere today, a project is failing” (DeMarco and Lister, 2013). They are talking about software projects, and as the book so brilliantly establishes, software is peopleware. A failed project is the dreaded culmination of all the perceptible and imperceptible risks that are associated with the project. For software projects, a large majority of such risks originate in the interactions of people who are involved in the project. People who build the software are the most valued and the most vulnerable asset of any software project, something that …

Recent Advances On Intelligent Mobility And Edge Computing, Xun Shao, Zhi Liu, Xianfu Chen, Seng W. Loke, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

In recent years, we have seen fast development of wireless communications, networking, and cloud computing: 4G, 5G and multiaccess networks greatly enhance the quality of service (QoS) of wireless access networks; software-defined networking, network function virtualization, and information-centric networking largely reduce the cost of network service providers and improve the quality of experience (QoE) of end-users; the development of mobile devices and mobile cloud computing lead to explosive deployment of mobile services and applications; the recent development of advanced algorithms such as Deep Learning has shown great potential in resource allocation and service orchestration. Deep integration of the above technologies …

Adaptive Simultaneous Pervasive Visible Light Communication And Sensing, Ila Nitin Gokarn, Archan Misra

Research Collection School Of Computing and Information Systems

Driven by the rapid growth in the proliferation of low-cost LED luminaries, visible light is being increasingly explored as both a high-speed communication and sensing channel for a variety of IoT applications. Visible Light Communication (VLC) exploits the high-frequency modulation of an optical source while ensuring imperceptibility to the human eye. In parallel, recent approaches in Visible Light Sensing (VLS) have demonstrated how high frequency optical strobing can be used to perform vision-based remote sensing of mechanical vibrations (e.g., of factory equipment). To date, exemplars of VLC and VLS have, however, been explored in isolation, without consideration of their mutual …

Combining Query Reduction And Expansion For Text-Retrieval-Based Bug Localization, Juan Manuel Florez, Oscar Chaparro, Christoph Treude, Andrian Marcus

Research Collection School Of Computing and Information Systems

Automated text-retrieval-based bug localization (TRBL) techniques normally use the full text of a bug report to formulate a query and retrieve parts of the code that are buggy. Previous research has shown that reducing the size of the query increases the effectiveness of TRBL. On the other hand, researchers also found improvements when expanding the query (i.e., adding more terms). In this paper, we bring these two views together to reformulate queries for TRBL. Specifically, we improve discourse-based query reduction strategies, by adopting a combinatorial approach and using task phrases from bug reports, and combine them with a state-of-the-art query …

Csci 40500/77100: Software Engineering, Raffi Khatchadourian

Open Educational Resources

This course is intended to be an introductory survey on the fundamental concepts and principles that underlie current and emerging methods, tools, and techniques for the efficient engineering of high-quality software systems. This may include understanding and appreciating problems in large-scale software development such as functional analysis of information processing systems, system design concepts, timing estimates, documentation, and system testing.

Csci 40500/77100: Software Engineering, Raffi Khatchadourian

Open Educational Resources

This course is intended to be an introductory survey on the fundamental concepts and principles that underlie current and emerging methods, tools, and techniques for the efficient engineering of high-quality software systems. This may include understanding and appreciating problems in large-scale software development such as functional analysis of information processing systems, system design concepts, timing estimates, documentation, and system testing.

Terrace-Based Food Counting And Segmentation, Huu-Thanh Nguyen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper represents object instance as a terrace, where the height of terrace corresponds to object attention while the evolution of layers from peak to sea level represents the complexity in drawing the finer boundary of an object. A multitask neural network is presented to learn the terrace representation. The attention of terrace is leveraged for instance counting, and the layers provide prior for easy-to-hard pathway of progressive instance segmentation. We study the model for counting and segmentation for a variety of food instances, ranging from Chinese, Japanese to Western food. This paper presents how the terrace model deals with …

Understanding Adversarial Robustness Via Critical Attacking Route, Tianlin Li, Aishan Liu, Xianglong Liu, Yitao Xu, Chongzhi Zhang, Xiaofei Xie

Research Collection School Of Computing and Information Systems

Deep neural networks (DNNs) are vulnerable to adversarial examples which are generated by inputs with imperceptible perturbations. Understanding adversarial robustness of DNNs has become an important issue, which would for certain result in better practical deep learning applications. To address this issue, we try to explain adversarial robustness for deep models from a new perspective of critical attacking route, which is computed by a gradient-based influence propagation strategy. Similar to rumor spreading in social net-works, we believe that adversarial noises are amplified and propagated through the critical attacking route. By exploiting neurons' influences layer by layer, we compose the critical …

Treecaps: Tree-Based Capsule Networks For Source Code Processing, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Recently program learning techniques have been proposed to process source code based on syntactical structures (e.g., Abstract Syntax Trees) and/or semantic information (e.g., Dependency Graphs). While graphs may be better at capturing various viewpoints of code semantics than trees, constructing graph inputs from code need static code semantic analysis that may not be accurate and introduces noise during learning. On the other hand, syntax trees are precisely defined according to the language grammar and easier to construct and process than graphs. We propose a new tree-based learning technique, named TreeCaps, by fusing capsule networks with tree-based convolutional neural networks, to …

Efficientderain: Learning Pixel-Wise Dilation Filtering For High-Efficiency Single-Image Deraining, Qing Guo, Jingyang Sun, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Wei Feng, Yang Liu, Jianjun Zhao

Research Collection School Of Computing and Information Systems

Single-image deraining is rather challenging due to the unknown rain model. Existing methods often make specific assumptions of the rain model, which can hardly cover many diverse circumstances in the real world, compelling them to employ complex optimization or progressive refinement. This, however, significantly affects these methods’ efficiency and effectiveness for many efficiency-critical applications. To fill this gap, in this paper, we regard the single-image deraining as a general image-enhancing problem and originally propose a model-free deraining method, i.e., EfficientDeRain, which is able to process a rainy image within 10 ms (i.e., around 6 ms on average), over 80 times …

Visual Analysis Of Discrimination In Machine Learning, Qianwen Wang, Zhenghua Xu, Zhutian Chen, Yong Wang, Shixia Liu, Huamin Qu

Research Collection School Of Computing and Information Systems

The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning. How can we decide whether different treatments are reasonable or discriminatory? In this paper, we investigate discrimination in machine learning from a visual analytics perspective and propose an interactive visualization tool, DiscriLens, to support a more comprehensive analysis. To reveal detailed information on algorithmic discrimination, DiscriLens identifies a collection of potentially discriminatory itemsets based on causal modeling and classification rules mining. By combining an extended Euler diagram with a matrix-based visualization, we develop a novel set …

Fault Analysis And Debugging Of Microservice Systems: Industrial Survey, Benchmark System, And Empirical Study, Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenhai Li, Dan Ding

Research Collection School Of Computing and Information Systems

The complexity and dynamism of microservice systems pose unique challenges to a variety of software engineering tasks such as fault analysis and debugging. In spite of the prevalence and importance of microservices in industry, there is limited research on the fault analysis and debugging of microservice systems. To fill this gap, we conduct an industrial survey to learn typical faults of microservice systems, current practice of debugging, and the challenges faced by developers in practice. We then develop a medium-size benchmark microservice system (being the largest and most complex open source microservice system within our knowledge) and replicate 22 industrial …