Sixiao Wei

Simulation Study of Unmanned Aerial Vehicle Communication Networks Addressing Bandwidth Disruptions

To date, Unmanned Aerial Vehicles (UAVs) have been widely used for numerous applications. UAVs can directly connect to ground stations or satellites to transfer data. Multiple UAVs can communicate and cooperate with each other and then construct an ad-hoc network. Multi-UAV systems have the potential to provide reliable and timely services for end users in addition to satellite networks. In this paper, we conduct a simulation study for evaluating the network performance of multi-UAV systems and satellite networks using the ns-2 networking simulation tool. Our simulation results show that UAV communication networks can achieve better network performance than satellite networks and with a lower cost and increased timeliness. We also investigate security resiliency of UAV networks. As a case study, we simulate false data injection attacks against UAV communication networks in ns-2 and demonstrate the impact of false data injection attacks on network performance.

On simulation studies of cyber attacks against LTE networks

Because of ever-increasing performance and capacity gains, the popularity of LTE as a 4G technology has skyrocketed. Unfortunately, cyber adversaries may launch attacks against the LTE network. In this paper, we develop a theoretical framework to systematically explore the attack space which consists of three dimensions: communication services attacked, planes of attack, and network components under attack. Based on the developed framework, we carried out extensive simulations to evaluate the impact of some representative attacks on LTE network performance. Our developed framework and simulation models enables a foundation for advancing the understanding of threats on the LTE network and assists in developing counter-measures to secure LTE networks.

On effective localization attacks against Internet Threat monitors

Internet Threat Monitoring (ITM) systems have been widely deployed to detect and characterize dangerous Internet global threats such as botnet and malware propagation. Nonetheless, the effectiveness of ITM systems largely depends on the confidentiality of their monitor locations. In this paper, we investigate localization attacks aiming to identify ITM monitor location and propose the formal model of such attacks using communication channel theory. We also develop novel techniques that significantly increases the accuracy, efficiency, and secrecy of ITM localization attacks. Specifically, we introduce (i) a frequency-based modulation technique to effectively reduce the interference from the background traffic and achieve a high attack accuracy, (ii) both time and space hopping techniques to randomize signal pattern and make the attack hard to detect by the defender, and (iii) Multiple Input and Multiple Output (MIMO) based techniques to increase the attack efficiency of identifying multiple monitors simultaneously. We derive closed formulae for the performance analysis of our proposed techniques and conduct extensive simulations. Our data validate our theoretical findings and demonstrate that the adversary can identify ITM monitors accurately, efficiently, and secretly.

ScanMe mobile: a local and cloud hybrid service for analyzing APKs

As mobile malware increases in numbers and sophistication, it becomes pertinent for users to have access to tools that can inform them of potentially malicious applications. In this paper, we developed a cloud based Android malware analysis service called ScanMe Mobile. The objective of this service is to allow users to learn information about Android application package (APK) files before installing them on their Android devices. With ScanMe Mobile, users can locally scan APK files on their phones SD (Secure Digital) memory card, compile a comprehensive report, and share the report by publishing it through a web interface. ScanMe Mobile allows users to perform both static and dynamic analysis on APK files. In addition to integrating some existing analysis tools into the system, we performed Android malware detection based on machine learning techniques. Our experimental data shows that our proposed system can effectively detect malware on the Android platform.

On effectiveness of game theoretic modeling and analysis against cyber threats for avionic systems

Cyber-attack defense requires network security situation awareness through distributed collaborative monitoring, detection, and mitigation. An issue of developing and demonstrating innovative and effective situational awareness techniques for avionics has increased in importance in the last decade. In this paper, we first conducted a game theoretical based modeling and analysis to study the interaction between an adversary and a defender. We then introduced the implementation of game-theoretic analysis on an Avionics Sensor-based Defense System (ASDS), which consists of distributed passive and active network sensors. A trade-off between defense and attack strategy was studied via existing tools for game theory (Gambit). To further enhance the defense and mitigate attacks, we designed and implemented a multi-functional web display to integrate the game theocratic analysis. Our simulation validates that the game theoretical modeling and analysis can help the Avionics Sensor-based Defense System (ASDS) adapt detection and response strategies to efficiently and dynamically deal with various cyber threats.

On effectiveness of routing algorithms for satellite communication networks

For worldwide, a satellite communication network is an integral component of the global networking infrastructure. In this paper, we focus on developing effective routing techniques that consider both user preferences and network dynamic conditions. In particular, we develop a weighted-based route selection scheme for the core satellite communication network. Unlike the shortest path routing scheme, our scheme chooses the route from multiple matched entries based on the assigned weights that reflect the dynamic condition of networks. We also discuss how to derive the optimal weights for route assignment. To further meet user’s preference, we implement the multiple path routing scheme to achieve the high rate of data transmission and the preemption based routing scheme to guarantee the data transmission for high priority users. Through extensive simulation studies, our data validates the effectiveness of our proposed routing schemes.

ScanMe mobile: a cloud-based Android malware analysis service

As mobile malware have increased in number and sophistication, it has become pertinent for users to have tools that can inform them of potentially malicious applications. To fulfill this need, we develop a cloud-based malware analysis service called ScanMe Mobile, for the Android platform. The objective of this service is to provide users with detailed information about Android Application Package (APK) files before installing them on their devices. With ScanMe Mobile, users are able to upload APK files from their device SD card, scan the APK in the malware detection system that could be deployed in the cloud, compile a comprehensive report, and store or share the report by publishing it to the website. ScanMe Mobile works by running the APK in a virtual sandbox to generate permission data, and analyzes the result in the machine learning detection system. Through our experimental results, we demonstrate that the proposed system can effectively detect malware on the Android platform.

Towards an integrated defense system for cyber security situation awareness experiment

In this paper, an implemented defense system is demonstrated to carry out cyber security situation awareness. The developed system consists of distributed passive and active network sensors designed to effectively capture suspicious information associated with cyber threats, effective detection schemes to accurately distinguish attacks, and network actors to rapidly mitigate attacks. Based on the collected data from network sensors, image-based and signals-based detection schemes are implemented to detect attacks. To further mitigate attacks, deployed dynamic firewalls on hosts dynamically update detection information reported from the detection schemes and block attacks. The experimental results show the effectiveness of the proposed system. A future plan to design an effective defense system is also discussed based on system theory.

On simulation studies of jamming threats against LTE networks

In this paper, we investigate the impact of jamming threats on the performance of LTE networks. First, we develop a three dimensional theoretical space to explore various jamming attacks. Next, we construct a set of attack scenarios by utilizing the dimensions of this space. To observe the impact on LTE network performance, we use ns-3 to implement the scenarios and to evaluate the attacks based on standard network metrics. The results demonstrate that our investigated jamming attacks can introduce significant performance degradation into LTE networks.

Scheduling methods for unmanned aerial vehicle based delivery systems

The recent Federal Aviation Administration (FAA) approval of Unmanned Aerial Vehicle (UAV) testing will transform our daily lives. Because of the inherent flexibility, ease of use, and low cost to operate; UAV-based delivery systems will become tremendously popular in the near future. In this paper, we address the issue of cyber-physical scheduling of UAV resources in order to achieve an efficient delivery service. Particularly, to reduce the overall delivery time, we develop a weight-based scheduling scheme, which considers the priority and delivery distance of service requests. To maximize the probability of effectively handling service requests with a limited number of UAVs, we first formalize the problem as an optimization problem and then use a dynamic programming approach to solve the problem. Through a simulation study, our data shows that the service delivery delay and the probability of successfully handling UAV services requests can be significantly improved upon in comparison with existing baseline schemes.