Recent Submissions

  • Android System Partition to Traffic Data? 

    Bing, Zhou; Liu, Qingzhou; Byrd, Brittany (International Journal of Knowledge Engineering, 2017-12)
    The familiarity and prevalence of mobile devices inflates their use as instruments of crime. Law enforcement personnel and mobile forensics investigators, are constantly battling to gain the upper-hand at developing a ...
  • Smartphone Sensor-Based Activity Recognition by Using Machine Learning and Deep Learning Algorithms 

    Liu, Qingzhong; Zhaoxian, Zhou; Sarbagya, Shakya Ratna; Prathyusha, Uduthalapally; Mengyu, Qiao; Andrew, Sung H. (International Journal of Machine Learning and Computing, 2018)
    Smartphones are widely used today, and it becomes possible to detect the user's environmental changes by using the smartphone sensors, as demonstrated in this paper where we propose a method to identify human activities ...
  • Security, Privacy and Steganographic Analysis of FaceApp and TikTo 

    Krishnan, Sundar; Liu, Qingzhou; Neyaz, Ashar; Kumar, Avinash; Placker, Jessica (International Journal of Computer Science and Security, 2020)
    Smartphone applications (Apps) can be addictive for users due to their uniqueness, ease-of-use, trendiness, and growing popularity. The addition of Artificial Intelligence (AI) into their functionality has rapidly gained ...
  • IoT Network Attack Detection using Supervised Machine Learning 

    Krishnan, Sundar; Neyaz, Ashar; Liu, Qinzhou (International Journal of Artificial Intelligence and Expert Systems, 2021)
    The use of supervised learning algorithms to detect malicious traffic can be valuable in designing intrusion detection systems and ascertaining security risks. The Internet of things (IoT) refers to the billions of physical, ...
  • Implications of Malicious 3D Printer Firmware 

    Moore, Samuel Bennett; Glisson, William Bradley; Yampolskiy, Mark (Proceedings of the 50th Hawaii International Conference on System Sciences, 2017-01)
    The utilization of 3D printing technology within the manufacturing process creates an environment that is potentially conducive to malicious activity. Previous research in 3D printing focused on attack vector identification ...
  • Attack-Graph Threat Modeling Assessment of Ambulatory Medical Devices 

    Luckett, Patrick; McDonald, J. Todd; Glisson, William Bradley (Proceedings of the 50th Hawaii International Conference on System Sciences, 2017-01)
    The continued integration of technology into all aspects of society stresses the need to identify and understand the risk associated with assimilating new technologies. This necessity is heightened when technology is used ...
  • Exploitation and Detection of a Malicious Mobile Application 

    Nguyen, Thanh; McDonald, J. Todd; Glisson, William Bradley (Proceedings of the 50th Hawaii International Conference on System Sciences, 2017-01)
    Mobile devices are increasingly being embraced by both organizations and individuals in today’s society. Specifically, Android devices have been the prominent mobile device OS for several years. This continued amalgamation ...
  • Investigating 3D Printer Residual Data 

    Miller, Daniel Bradford; Gatlin, Jacob; Glisson, William Bradley; Yampolskiy, Mark; McDonald, Jeffery Todd (Proceedings of the 52nd Hawaii International Conference on System Sciences, 2019-01)
    The continued adoption of Additive Manufacturing (AM) technologies is raising concerns in the security, forensics, and intelligence gathering communities. These concerns range from identifying and mitigating compromised ...
  • How Good is Your Data? Investigating the Quality of Data Generated During Security Incident Response Investigations 

    Grispos, George; Glisson, William Bradley; Storer, Tim (Proceedings of the 52nd Hawaii International Conference on System Sciences, 2019-01)
    An increasing number of cybersecurity incidents prompts organizations to explore alternative security solutions, such as threat intelligence programs. For such programs to succeed, data needs to be collected, validated, ...
  • A Bleeding Digital Heart: Identifying Residual Data Generation from Smartphone Applications Interacting with Medical Devices 

    Grispos, George; Glisson, William Bradley; Cooper, Peter (Proceedings of the 52nd Hawaii International Conference on System Sciences, 2019-01)
    The integration of medical devices in everyday life prompts the idea that these devices will increasingly have evidential value in civil and criminal proceedings. However, the investigation of these devices presents new ...
  • Insight from a Docker Container Introspection 

    Watts, Thomas; Benton, Ryan G.; Glisson, William Bradley; Shropshire, Jordan (2019-01)
    Large-scale adoption of virtual containers has stimulated concerns by practitioners and academics about the viability of data acquisition and reliability due to the decreasing window to gather relevant data points. These ...
  • Detecting Deception Using Machine Learning 

    Ceballos Delgado, Alberto Alejandro; Glisson, William Bradley; Shashidhar, Narasimha; McDonald, J. Todd; Grispos, George; Benton, Ryan (Proceedings of the 54th Hawaii International Conference on System Sciences, 2021-01)
    Today’s digital society creates an environment potentially conducive to the exchange of deceptive information. The dissemination of misleading information can have severe consequences on society. This research investigates ...
  • Knock! Knock! Who is There? Investigating Data Leakage from a Medical Internet of Things Hijacking Attack 

    Flynn, Talon; Grispos, George; Glisson, William Bradley; Mahoney, William (Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020-01)
    The amalgamation of Medical Internet of Things (MIoT) devices into everyday life is influencing the landscape of modern medicine. The implementation of these devices potentially alleviates the pressures and physical demands ...
  • Detecting Repackaged Android Applications Using Perceptual Hashing 

    Nguyen, Thanh; McDonald, J. Todd; Glisson, William Bradley; Andel, Todd R. (Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020-01)
    The last decade has shown a steady rate of Android device dominance in market share and the emergence of hundreds of thousands of apps available to the public. Because of the ease of reverse engineering Android applications, ...
  • Attack Modeling and Mitigation Strategies for Risk-Based Analysis of Networked Medical Devices 

    Hodges, Bronwyn J.; McDonald, J. Todd; Glisson, William Bradley; Jacobs, Michael; Van Devender, Maureen; Pardue, J. Harold (Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020-01)
    The escalating integration of network-enabled medical devices raises concerns for both practitioners and academics in terms of introducing new vulnerabilities and attack vectors. This prompts the idea that combining medical ...
  • Network Attack Detection using an Unsupervised Machine Learning Algorithm 

    Kumar, Avinash; Glisson, William Bradley; Benton, Ryan (Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020)
    With the increase in network connectivity in today's web-enabled environments, there is an escalation in cyber-related crimes. This increase in illicit activity prompts organizations to address network security risk issues ...
  • Calm Before the Storm: The Challenges of Cloud Computing in Digital Forensics 

    Grispos, George; Storer, Tim; Glisson, William Bradley (International Journal of Digital Crime and Forensics, 2012-04)
    Cloud computing is a rapidly evolving information technology (IT) phenomenon. Rather than procure, deploy, and manage a physical IT infrastructure to host their software applications, organizations are increasingly deploying ...
  • Machine Learning-Based Android Malware Detection Using Manifest Permissions 

    Herron, Nathan; Glisson, William Bradley; McDonald, J. Todd; Benton, Ryan K. (Proceedings of the 54th Hawaii International Conference on System Sciences, 2021-01-05)
    The Android operating system is currently the most prevalent mobile device operating system holding roughly 54 percent of the total global market share. Due to Android’s substantial presence, it has gained the attention ...
  • Web Engineering Security (WES) Methodology 

    Glisson, William Bradley; Welland, Ray (Communications of the Association for Information Systems, 2014)
    The impact of the World Wide Web on basic operational economical components in global information-rich civilizations is significant. The repercussions force organizations to provide justification for security from a ...
  • In-The-Wild Residual Data Research and Privacy 

    Glisson, William Bradley; Storer, Tim; Blyth, Andrew; Grispos, George; Campbell, Matt (Journal of Digital Forensics, Security and Law, 2016)
    As the world becomes increasingly dependent on technology, researchers in industry and academia endeavor to understand how technology is used, the impact it has on everyday life, the artifact life-cycle and overall ...

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