Matching Items (3)
Description
Malware that perform identity theft or steal bank credentials are becoming increasingly common and can cause millions of dollars of damage annually. A large area of research focus is the automated detection and removal of such malware, due to their large impact on millions of people each year. Such a detector will be beneficial to any industry that is regularly the target of malware, such as the financial sector. Typical detection approaches such as those found in commercial anti-malware software include signature-based scanning, in which malware executables are identified based on a unique signature or fingerprint developed for that malware. However, as malware authors continue to modify and obfuscate their malware, heuristic detection is increasingly popular, in which the behaviors of the malware are identified and patterns recognized. We explore a malware analysis and classification framework using machine learning to train classifiers to distinguish between malware and benign programs based upon their features and behaviors. Using both decision tree learning and support vector machines as classifier models, we obtained overall classification accuracies of around 80%. Due to limitations primarily including the usage of a small data set, our approach may not be suitable for practical classification of malware and benign programs, as evident by a high error rate.
ContributorsAnwar, Sajid (Co-author) / Chan, Tsz (Co-author) / Ahn, Gail-Joon (Thesis director) / Zhao, Ziming (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Over the past several years, the three major mobile platforms have seen
tremendous growth and success; as a result, the platforms have been the target
of many malicious attacks. These attacks often request certain permissions in
order to carry out the malicious activities, and uninformed users usually grant
them. One prevalent example of this type of malware is one that requests
permission to the device’s SMS service, and once obtained, uses the SMS
service to accrue charges to the user. This type of attack is one of the most
prevalent on the Android application marketplace, and requires a long-term
solution. Replication of an attack is necessary to fully understand efficient
prevention methods, and due to the open-source nature of Android development,
to determine the likely mechanics of the attack as feasible.
This study uses the Hacker News application, an open source application
that is available for download through GitHub as a basis for creating a malware
application to study the SMS attack and explore prevention methods. From the
results and knowledge gained from both research and experimentation, a
proposition for a more secure operating system architecture was defined to
prevent and mitigate various attacks on mobile systems with a focus on SMS
attacks.
tremendous growth and success; as a result, the platforms have been the target
of many malicious attacks. These attacks often request certain permissions in
order to carry out the malicious activities, and uninformed users usually grant
them. One prevalent example of this type of malware is one that requests
permission to the device’s SMS service, and once obtained, uses the SMS
service to accrue charges to the user. This type of attack is one of the most
prevalent on the Android application marketplace, and requires a long-term
solution. Replication of an attack is necessary to fully understand efficient
prevention methods, and due to the open-source nature of Android development,
to determine the likely mechanics of the attack as feasible.
This study uses the Hacker News application, an open source application
that is available for download through GitHub as a basis for creating a malware
application to study the SMS attack and explore prevention methods. From the
results and knowledge gained from both research and experimentation, a
proposition for a more secure operating system architecture was defined to
prevent and mitigate various attacks on mobile systems with a focus on SMS
attacks.
ContributorsRomo, James Tyler (Co-author) / Rezende, Bryan (Co-author) / Whitaker, Jeremy (Co-author) / Ahn, Gail-Joon (Thesis director) / Wilkerson, Kelly (Committee member) / Conquest, Kevin (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
Command and Control (C2) tactics are commonly used by ethical hackers and other offensive security professionals to emulate a realistic adversary attack on a network. This helps security teams measure how prepared they are for a real attack. This thesis documents the creative process of designing and creating Meltout, an open-source C2 framework written in the Rust programming language.
ContributorsShinno, Thaddeus (Author) / Meuth, Ryan (Thesis director) / Shoshitaishvili, Yan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05