Shaya Wolf

2papers

2 Papers

SYJun 7, 2018
Secure and Decentralized Swarm Behavior with Autonomous Agents for Smart Cities

Rafer Cooley, Shaya Wolf, Mike Borowczak

Unmanned Aerial Vehicles (UAVs), referenced as drones, have advanced to consumer adoption for hobby and business use. Drone applications, such as infrastructure technology, security mechanisms, and resource delivery, are just the starting point. More complex tasks are possible through the use of UAV swarms. These tasks increase the potential impacts that drones will have on smart cities, modern cities which have fully adopted technology in order to enhance daily operations as well as the welfare of it's citizens. Smart cities not only consist of static mesh networks of sensors, but can contain dynamic aspects as well including both ground and air based autonomous vehicles. Networked computational devices require paramount security to ensure the safety of a city. To accomplish such high levels of security, services rely on secure-by-design protocols, impervious to security threats. Given the large number of sensors, autonomous vehicles, and other advancements, smart cities necessitates this level of security. The SHARK protocol (Secure, Heterogeneous, Autonomous, and Rotational Knowledge for Swarms) ensures this kind of security by allowing for new applications for UAV swarm technology. Enabling drones to circle a target without a centralized control or selecting lead agents, the SHARKS protocol performs organized movement among agents without creating a central point for attackers to target. Through comparisons on the stability of the protocol in different settings, experiments demonstrate the efficiency and capacity of the SHARKS protocol.

CRMar 7, 2019
Dynamic Anonymized Evaluation for Behavioral Continuous Authentication

Rasana Manandhar, Shaya Wolf, Mike Borowczak

Emerging technology demands reliable authentication mechanisms, particularly in interconnected systems. Current systems rely on a single moment of authentication, however continuous authentication systems assess a users identity utilizing a constant biometric analysis. Spy Hunter, a continuous authentication mechanism uses keystroke dynamics to validate users over blocks of data. This easily-incorporated periodic biometric authentication system validates genuine users and detects intruders quickly. Because it verifies users in the background, Spy Hunter is not constrained to a password box. Instead, it is flexible and can be layered with other mechanisms to provide high-level security. Where other continuous authentication techniques rely on scripted typing, Spy Hunter validates over free text in authentic environments. This is accomplished in two phases, one where the user is provided a prompt and another where the user is allowed free access to their computer. Additionally, Spy Hunter focuses on the timing of different keystrokes rather than the specific key being pressed. This allows for anonymous data to authenticate users and avoids holding personal data. Utilizing a couple K-fold cross-validation techniques, Spy Hunter is assessed based on how often the system falsely accepts an intruder, how often the system falsely rejects a genuine user, and the time it takes to validate a users identity. Spy Hunter maintains error rates below 6% and identifies users in minimal numbers of keystrokes. Continuous authentication provides higher level security than one-time verification processes and Spy Hunter expands on the possibilities for behavioral analysis based on keystroke dynamics.