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Articles 1951 - 1980 of 4676
Full-Text Articles in Computer Sciences
Classification Of Malware Models, Akriti Sethi
Classification Of Malware Models, Akriti Sethi
Master's Projects
Automatically classifying similar malware families is a challenging problem. In this research, we attempt to classify malware families by applying machine learning to machine learning models. Specifically, we train hidden Markov models (HMM) for each malware family in our dataset. The resulting models are then compared in two ways. First, we treat the HMM matrices as images and experiment with convolutional neural networks (CNN) for image classification. Second, we apply support vector machines (SVM) to classify the HMMs. We analyze the results and discuss the relative advantages and disadvantages of each approach.
Machine Learning Versus Deep Learning For Malware Detection, Parth Jain
Machine Learning Versus Deep Learning For Malware Detection, Parth Jain
Master's Projects
It is often claimed that the primary advantage of deep learning is that such models can continue to learn as more data is available, provided that sufficient computing power is available for training. In contrast, for other forms of machine learning it is claimed that models ‘‘saturate,’’ in the sense that no additional learning can occur beyond some point, regardless of the amount of data or computing power available. In this research, we compare the accuracy of deep learning to other forms of machine learning for malware detection, as a function of the training dataset size. We experiment with a …
Deep Learning For Image Spam Detection, Tazmina Sharmin
Deep Learning For Image Spam Detection, Tazmina Sharmin
Master's Projects
Spam can be defined as unsolicited bulk email. In an effort to evade text-based spam filters, spammers can embed their spam text in an image, which is referred to as image spam. In this research, we consider the problem of image spam detection, based on image analysis. We apply various machine learning and deep learning techniques to real-world image spam datasets, and to a challenge image spam-like dataset. We obtain results comparable to previous work for the real-world datasets, while our deep learning approach yields the best results to date for the challenge dataset.
Earmarked Utxo For Escrow Services And Two-Factor Authentication On The Blockchain, Jisha Pillai
Earmarked Utxo For Escrow Services And Two-Factor Authentication On The Blockchain, Jisha Pillai
Master's Projects
The security of accounts on the blockchain relies on securing private keys, but they are often lost or compromised due to loopholes in key management strategies or due to human error. With an increasing number of thefts in the last few years due to compromised wallets, the security of digital currency has become a significant concern, and no matter how sophisticated and secure mechanisms are put in place to avoid the security risks, it is impossible to achieve a 100% human compliance.
This project introduces a novel concept of Earmarked Unspent Transaction Outputs (EUTXOs). EUTXOs enable every user on the …
Emulation Vs Instrumentation For Android Malware Detection, Anukriti Sinha
Emulation Vs Instrumentation For Android Malware Detection, Anukriti Sinha
Master's Projects
In resource constrained devices, malware detection is typically based on offline analysis using emulation. In previous work it has been claimed that such emulation fails for a significant percentage of Android malware because well-designed malware detects that the code is being emulated. An alternative to emulation is malware analysis based on code that is executing on an actual Android device. In this research, we collect features from a corpus of Android malware using both emulation and on-phone instrumentation. We train machine learning models based on emulated features and also train models based on features collected via instrumentation, and we compare …
Multifamily Malware Models, Samanvitha Basole
Multifamily Malware Models, Samanvitha Basole
Master's Projects
When training a machine learning model, there is likely to be a tradeoff between the accuracy of the model and the generality of the dataset. Previous research has shown that if we train a model to detect one specific malware family, we obtain stronger results as compared to a case where we train a single model on multiple diverse families. During the detection phase, it would be more efficient to have a single model that could detect multiple families, rather than having to score each sample against multiple models. In this research, we conduct experiments to quantify the relationship between …
Implementation Of Group Based Cryptosystems In Information Security, Bailey J. Moers
Implementation Of Group Based Cryptosystems In Information Security, Bailey J. Moers
Undergraduate University Honors Capstones
This capstone will focus on the implementation of cryptography in information security. The implementation can be achieved by studying different cryptosystems that will be secured using group based mathematics. Group based cryptosystems are preferable because research shows that group based cryptosystems are computationally infeasible. Understanding group based mathematics and its implementation in cryptography will allow us to better study the NTRU (Nth Truncated Ring Unit) cryptosystem with previous knowledge of group based cryptosystems. Although this cryptosystem is still very new, two sections of NTRU cryptosystem will be implemented in information security. The selected sections are: Multiplication of Polynomials modulo p …
Cybersecurity For Critical Infrastructure: Addressing Threats And Vulnerabilities In Canada, Samuel A. Cohen
Cybersecurity For Critical Infrastructure: Addressing Threats And Vulnerabilities In Canada, Samuel A. Cohen
Graduate Theses/Dissertations
The aim of this thesis is to assess the unique technical and policy-based cybersecurity challenges facing Canada’s critical infrastructure environment and to analyze how current government and industry practices are not equipped to remediate or offset associated strategic risks to the country. Further, the thesis also provides cases and evidence demonstrating that Canada’s critical infrastructure has been specifically targeted by foreign and domestic cyber threat actors to pressure the country’s economic, safety and national security interests. Essential services that Canadians and Canadian businesses rely on daily are intricately linked to the availability and integrity of vital infrastructure sectors, such as …
Forensic Analysis Of Spy Applications In Android Devices, Shinelle Hutchinson, Umit Karabiyik
Forensic Analysis Of Spy Applications In Android Devices, Shinelle Hutchinson, Umit Karabiyik
Annual ADFSL Conference on Digital Forensics, Security and Law
Smartphones with Google's Android operating system are becoming more and more popular each year, and with this increased user base, comes increased opportunities to collect more of these users' private data. There have been several instances of malware being made available via the Google Play Store, which is one of the predominant means for users to download applications. One effective way of collecting users' private data is by using Android Spyware. In this paper, we conduct a forensic analysis of a malicious Android spyware application and present our findings. We also highlight what information the application accesses and what it …
Assessing Code Obfuscation Of Metamorphic Javascript, Kaushik Murli
Assessing Code Obfuscation Of Metamorphic Javascript, Kaushik Murli
Master's Projects
Metamorphic malware is one of the biggest and most ubiquitous threats in the digital world. It can be used to morph the structure of the target code without changing the underlying functionality of the code, thus making it very difficult to detect using signature-based detection and heuristic analysis. The focus of this project is to analyze Metamorphic JavaScript malware and techniques that can be used to mutate the code in JavaScript. To assess the capabilities of the metamorphic engine, we performed experiments to visualize the degree of code morphing. Further, this project discusses potential methods that have been used to …
Cptc - A Security Competition Unlike Any Other, Bill Stackpole, Daryl Johnson
Cptc - A Security Competition Unlike Any Other, Bill Stackpole, Daryl Johnson
Presentations and other scholarship
Participating in cybersecurity competitions has become increasing popular for students in higher education programs that have a focus on computing or cyber security. The Collegiate Penetration Testing Competition was developed to address the industry skills gap and assist in identifying ethically minded security personnel with experience identifying, exercising, and mitigating vulnerabilities.
Analysis Of Computer Audit Data To Create Indicators Of Compromise For Intrusion Detection, Steven Millett, Michael Toolin, Justin Bates
Analysis Of Computer Audit Data To Create Indicators Of Compromise For Intrusion Detection, Steven Millett, Michael Toolin, Justin Bates
SMU Data Science Review
Network security systems are designed to identify and, if possible, prevent unauthorized access to computer and network resources. Today most network security systems consist of hardware and software components that work in conjunction with one another to present a layered line of defense against unauthorized intrusions. Software provides user interactive layers such as password authentication, and system level layers for monitoring network activity. This paper examines an application monitoring network traffic that attempts to identify Indicators of Compromise (IOC) by extracting patterns in the network traffic which likely corresponds to unauthorized access. Typical network log data and construct indicators are …
Intrusion-Tolerant Order-Preserving Encryption, John Huson
Intrusion-Tolerant Order-Preserving Encryption, John Huson
Masters Theses, 2010-2019
Traditional encryption schemes such as AES and RSA aim to achieve the highest level of security, often indistinguishable security under the adaptive chosen-ciphertext attack. Ciphertexts generated by such encryption schemes do not leak useful information. As a result, such ciphertexts do not support efficient searchability nor range queries.
Order-preserving encryption is a relatively new encryption paradigm that allows for efficient queries on ciphertexts. In order-preserving encryption, the data-encrypting key is a long-term symmetric key that needs to stay online for insertion, query and deletion operations, making it an attractive target for attacks.
In this thesis, an intrusion-tolerant order-preserving encryption system …
Managing The Power And Pitfalls Of Data In Ai, Singapore Management University
Managing The Power And Pitfalls Of Data In Ai, Singapore Management University
Perspectives@SMU
Ethics and education are crucial in maintaining data privacy and augmenting human ability
“It’s difficult to imagine the power that you’re going to have when so many different sorts of data are available.” – Tim Berners-Lee, father of the Internet
“Before Google, and long before Facebook, Bezos had realised that the greatest value of an online company lay in the consumer data it collected.” – George Packer, author for the New Yorker
“Greening” Worcester: Municipal Best Practices For Sustainability, Erin Mckeon, Charline Kirongozi, Jared Duval, Antannia Greene, Qianshu Sun, Zewei Yao
“Greening” Worcester: Municipal Best Practices For Sustainability, Erin Mckeon, Charline Kirongozi, Jared Duval, Antannia Greene, Qianshu Sun, Zewei Yao
School of Professional Studies
In response to the urgent threat posed by climate change, more and more cities, including Worcester, are attempting to become more environmentally responsible and sustainable. Worcester is attempting to develop ways to become more sustainable; both to strengthen their communities and to protect the planet. The Green Worcester Working Group (GWWG) tasked the Clark Capstone Team with researching best practices for municipal sustainability. The GWWG has set the following priorities: climate change mitigation, resilience, open spaces, sustainable resource management, education and awareness. Taking these into account, the Clark Capstone Team researched the sustainability practices of cities in New England, across …
Worcester Chamber Of Commerce: Recruiting Minority Business Owners, Ryan Dimaria, Alexander Hull, Xikun Lu, Haopeng Wang, Jiacheng Hou, Danning Zhao
Worcester Chamber Of Commerce: Recruiting Minority Business Owners, Ryan Dimaria, Alexander Hull, Xikun Lu, Haopeng Wang, Jiacheng Hou, Danning Zhao
School of Professional Studies
Our capstone project was to help the Worcester Regional Chamber of Commerce identify how to re-frame their marketing so it would be appealing to immigrant and minority owned businesses. Based on interviews and external research, our group was able to create a tangible and resourceful data set that provided justified recommendations and ideas on how the Chamber could make adjustments to their marketing plan to attract more businesses of this particular demographic in the city of Worcester. By implementing these recommendations, we believe the Chamber has the opportunity to create a more diverse group of Chamber members, add value to …
Service Now: Cmdb Research, Monika Patel, Smita Patil, Katerina Tzanavara, Manish Chauhan, Yuhao Wang, Houmin Xie, Lei Shi
Service Now: Cmdb Research, Monika Patel, Smita Patil, Katerina Tzanavara, Manish Chauhan, Yuhao Wang, Houmin Xie, Lei Shi
School of Professional Studies
The MAPFRE Capstone team has been tasked with reviewing and recommending roadmap on the existing CMDB configuration. Paper discusses the team’s overall research on ServiceNow CMDB, Client’s deliverables and introduction to the latest technological innovations. Based on given objectives and team’s analysis we have recommended key solutions for the client to better understand the IT environment areas of business service impact, asset management, compliance, and configuration management. In addition, our research has covered all the majority of the technical and functional areas to provide greater visibility and insight into existing CMDB and IT environment.
For One Child, Zion Bereket, Xin Huang, Yitong Lin, Ruobing Pei, Rachel White, Ziyuan Li
For One Child, Zion Bereket, Xin Huang, Yitong Lin, Ruobing Pei, Rachel White, Ziyuan Li
School of Professional Studies
The entirety of this project was completed on the foundation of the three focus areas, which were identified by our client as areas of high need. The client wanted to prioritize these three areas as they believed that these three areas were the most integral to the successful achievement of their mission, as well as to the overall health and longevity of the organization.
Hiv/Aids In The Latino Community Of San Francisco: Past And Present, Jessica Da Silva
Hiv/Aids In The Latino Community Of San Francisco: Past And Present, Jessica Da Silva
School of Professional Studies
There are approximately 122,000 people of Latino origin in San Francisco, which account for 15% of the total population (Census, 2010). Historically, Latinos have and still face several barriers to access healthcare and improvements in health (Aguirre-Molina, Molina & Zambrana, 2001). When the world was exposed to the spread of a new and unknown virus, the broader population suffered from the epidemic. The Latino community in San Francisco was and still is one of the hardest hit by the virus.
Changing The Current Perception Of Affordable Housing In Worcester, Simone Mcguinness, William Roberts, Vaske Gjino, Tong Zhou, Mengxin Ma, Sarawadee Sonpuak
Changing The Current Perception Of Affordable Housing In Worcester, Simone Mcguinness, William Roberts, Vaske Gjino, Tong Zhou, Mengxin Ma, Sarawadee Sonpuak
School of Professional Studies
One of Worcester Interfaith’s goals is to eradicate the stigma of affordable housing in Worcester. Currently, the perception of affordable housing is of an image of unkept and old residences filled with destitute citizens who cannot afford basic needs to live in a city, let alone housing. This image is perpetuated by media, stigma, and a lack of education of the true reality of affordable housing and who its recipients are. Affordable housing-qualified citizens represent a range of educations, professions, age, race, and income levels. Affordable housing units, too, represent a variety of homes, many of which are extremely well-kept …
A Privacy-Preserving Framework For Collaborative Association Rule Mining In Cloud, Salha Albehairi
A Privacy-Preserving Framework For Collaborative Association Rule Mining In Cloud, Salha Albehairi
Theses, Dissertations and Culminating Projects
Collaborative Data Mining facilitates multiple organizations to integrate their datasets and extract useful knowledge from their joint datasets for mutual benefits. The knowledge extracted in this manner is found to be superior to the knowledge extracted locally from a single organization’s dataset. With the rapid development of outsourcing, there is a growing interest for organizations to outsource their data mining tasks to a cloud environment to effectively address their economic and performance demands. However, due to privacy concerns and stringent compliance regulations, organizations do not want to share their private datasets neither with the cloud nor with other participating organizations. …
A Privacy-Aware Framework For Friend Recommendations In Online Social Networks, Mona Fahad Alkanhal
A Privacy-Aware Framework For Friend Recommendations In Online Social Networks, Mona Fahad Alkanhal
Theses, Dissertations and Culminating Projects
Online social networks (OSN), such as Facebook, Twitter, and LinkedIn, have revolutionized the way how people share information and stay connected with family and friends. Along this direction, user’s privacy has been a significant concern to all users in the social networks. In this thesis, we propose a privacyaware framework that allows users to outsource their encrypted profile data to a cloud environment. In order to achieve better security and efficiency, our framework utilizes a hybrid approach that consists of Paillier’s encryption scheme and AES. Furthermore, we develop a privacy-aware friend recommendation protocol that recommends new friends to social network …
Hardware Ip Classification Through Weighted Characteristics, Brendan Mcgeehan
Hardware Ip Classification Through Weighted Characteristics, Brendan Mcgeehan
Graduate Theses and Dissertations
Today’s business model for hardware designs frequently incorporates third-party Intellectual Property (IP) due to the many benefits it can bring to a company. For instance, outsourcing certain components of an overall design can reduce time-to-market by allowing each party to specialize and perfect a specific part of the overall design. However, allowing third-party involvement also increases the possibility of malicious attacks, such as hardware Trojan insertion. Trojan insertion is a particularly dangerous security threat because testing the functionality of an IP can often leave the Trojan undetected. Therefore, this thesis work provides an improvement on a Trojan detection method known …
A Blockchain-Based Location Privacy-Preserving Crowdsensing System, Mengmeng Yang, Tianqing Zhu, Kaitai Liang, Wanlei Zhou, Robert H. Deng
A Blockchain-Based Location Privacy-Preserving Crowdsensing System, Mengmeng Yang, Tianqing Zhu, Kaitai Liang, Wanlei Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
With the support of portable electronic devices and crowdsensing, a new class of mobile applications based on the Internet of Things (IoT) application is emerging. Crowdsensing enables workers with mobile devices to travel to specified locations and collect data, then send it back to the requester for rewards. However, the majority of the existing crowdsensing systems are based on centralized servers, which are prone to a high chance of attack, intrusion, and manipulation. Further, during the process of transmitting information to and from the service server, the worker's location is usually exposed. This raises the potential risk of a privacy …
Adversarial Sample Detection For Deep Neural Network Through Model Mutation Testing, Jingyi Wang, Guoliang Dong, Jun Sun, Xinyu Wang, Zhang Peixin
Adversarial Sample Detection For Deep Neural Network Through Model Mutation Testing, Jingyi Wang, Guoliang Dong, Jun Sun, Xinyu Wang, Zhang Peixin
Research Collection School Of Computing and Information Systems
No abstract provided.
Bilateral Liability-Based Contracts In Information Security Outsourcing, Kai-Lung Hui, Ping Fan Ke, Yuxi Yao, Wei Thoo Yue
Bilateral Liability-Based Contracts In Information Security Outsourcing, Kai-Lung Hui, Ping Fan Ke, Yuxi Yao, Wei Thoo Yue
Research Collection School Of Computing and Information Systems
We study the efficiency of bilateral liability-based contracts in managed security services (MSSs). We model MSS as a collaborative service with the protection quality shaped by the contribution of both the service provider and the client. We adopt the negligence concept from the legal profession to design two novel contracts: threshold-based liability contract and variable liability contract. We find that they can achieve the first best outcome when postbreach effort verification is feasible. More importantly, they are more efficient than a multilateral contract when the MSS provider assumes limited liability. Our results show that bilateral liability-based contracts can work in …
Pptds: A Privacy-Preserving Truth Discovery Scheme In Crowd Sensing Systems, Chuan Zhang, Liehuang Zhu, Chang Xu, Kashif Sharif, Ximeng Liu
Pptds: A Privacy-Preserving Truth Discovery Scheme In Crowd Sensing Systems, Chuan Zhang, Liehuang Zhu, Chang Xu, Kashif Sharif, Ximeng Liu
Research Collection School Of Computing and Information Systems
Benefiting from the fast development of human-carried mobile devices, crowd sensing has become an emerging paradigm to sense and collect data. However, reliability of sensory data provided by participating users is still a major concern. To address this reliability challenge, truth discovery is an effective technology to improve data accuracy, and has garnered significant attention. Nevertheless, many of state of art works in truth discovery, either failed to address the protection of participants' privacy or incurred tremendous overhead on the user side. In this paper, we first propose a privacy-preserving truth discovery scheme, named PPTDS-I, which is implemented on two …
Designated-Server Identity-Based Authenticated Encryption With Keyword Search For Encrypted Emails, Hongbo Li, Qiong Huang, Jian Shen, Guomin Yang, Willy Susilo
Designated-Server Identity-Based Authenticated Encryption With Keyword Search For Encrypted Emails, Hongbo Li, Qiong Huang, Jian Shen, Guomin Yang, Willy Susilo
Research Collection School Of Computing and Information Systems
In encrypted email system, how to search over encrypted cloud emails without decryption is an important and practical problem. Public key encryption with keyword search (PEKS) is an efficient solution to it. However, PEKS suffers from the complex key management problem in the public key infrastructure. Its variant in the identity-based setting addresses the drawback, however, almost all the schemes does not resist against offline keyword guessing attacks (KGA) by inside adversaries. In this work we introduce the notion of designated-server identity-based authenticated encryption with keyword search (dIBAEKS), in which the email sender authenticates the message while encrypting so that …
The Golden Ticket: How Blockchain Technology Can Be Implemented Into Event Ticketing, Jack Singer
The Golden Ticket: How Blockchain Technology Can Be Implemented Into Event Ticketing, Jack Singer
Renée Crown University Honors Thesis Projects - All
When the group/individual named Satoshi Nakamoto first conceptualized blockchain in 2008, it served as the underlying foundation to the cryptocurrency Bitcoin. In the years following, cryptocurrencies alike experiences massive gains in profitability; however, after the bubble had burst organizations began to look at the technology from a more academic standpoint. It was quickly found out that there is a massive application for blockchain in almost all sectors of industry from bulk stores (Walmart) to banking (IBM). This paper will explore how blockchain technology can be implemented into event ticketing, more specifically concerts. The current landscape of the industry is under …
Federal, State And Local Law Enforcement Agency Interoperability Capabilities And Cyber Vulnerabilities, Tyrone Trapnell
Federal, State And Local Law Enforcement Agency Interoperability Capabilities And Cyber Vulnerabilities, Tyrone Trapnell
Electronic Theses and Dissertations
The National Data Exchange (N-DEx) System is the central informational hub located at the Federal Bureau of Investigation (FBI). Its purpose is to provide network subscriptions to all Federal, state and local level law enforcement agencies while increasing information collaboration across all domains. The National Data Exchange users must satisfy the Advanced Permission Requirements, confirming the terms of N-DEx information use, and the Verification Requirement (verifying the completeness, timeliness, accuracy, and relevancy of N-DEx information) through coordination with the record-owning agency (Management, 2018). A network infection model is proposed to simulate the spread impact of various cyber-attacks within Federal, state …