Evaluation of DoS attacks on Commercial Wi-Fi-Based UAVs

One of the biggest challenges for the use of Unmanned Aerial Vehicles (UAVs) in large-scale real-world applications is security.  However, most of research projects related to robotics does not discuss security issues, moving on directly to studying classical problems (i.e., perception, control, planning). This paper evaluates the effects of availability issues (Denial of Service attacks) in two commonly used commercially available UAVs (AR.Drone 2.0 and 3DR SOLO). Denial of Service (DoS) attacks are made while the vehicles are navigating, simulating common conditions found both by the general public and in a research scenario. Experiments show how effective such attacks are and demonstrate actual security breaches that create specific vulnerabilities. The results indicate that both studied UAVs are susceptible to several types of DoS attacks which can critically influence the performance of UAVs during navigation, including a decrease in camera functionality, drops in telemetry feedback and lack of response to remote control commands. We also present a tool that can be used as a failsafe mechanism to alert the user when a drone is reaching out a determined flight limit range, avoiding availability issues

Detection and control of small civilian UAVs

With the increasing proliferation of small civilian Unmanned Aerial Vehicles (UAVs), the threat to critical infrastructure (CI) security and privacy is now widely recognised and must be addressed. These devices are easily available at a low cost, with their usage largely unrestricted allowing users to have no accountability. Further, current implementations of UAVs have little to no security measures applied to their control interfaces. To combat the threat raised by small UAVs, being aware of their presence is required, a task that can be challenging and often requires customised hardware. This thesis aimed to address the threats posed by the Parrot AR Drone v2, by presenting a data link signature detection method which provides the characteristics needed to implement a mitigation method, capable of stopping a UAVs movement and video stream. These methods were developed using an experimental procedure and are packaged as a group of Python scripts. A suitable detection method was developed, capable of detecting and identifying a Parrot AR Drone v2 within WiFi operational range. A successful method of disabling the controls and video of a Parrot AR Drone in the air was implemented, with collection of video and control commands also achieved, for after-the-event reconstruction of the video stream. Real-time video monitoring is achievable, however it is deemed detrimental to the flight stability of the Parrot, reducing the effectiveness of monitoring the behaviour of an unidentified Parrot AR Drone v2. Additionally, implementing a range of mitigations for continued monitoring of Parrot AR Drones proved ineffectual, given that the mitigations applied were found to be non-persistent, with the mitigations reverting after control is returned to the controller. While the ability to actively monitor and manipulate Parrot AR Drones was successful, it was not to the degree believed possible during initial research

Security Analysis and Evaluation of Smart Toys

During the last years, interconnectivity and merging the physical and digital technological dimensions have become a topic attracting the interest of the modern world. Internet of Things (IoT) is rapidly evolving as it manages to transform physical devices into communicating agents which can consecutively create complete interconnected systems. A sub-category of the IoT technology is smart toys, which are devices with networking capabilities, created for and used in play. Smart toys’ targeting group is usually children and they attempt to provide a higher level of entertainment and education by offering an enhanced and more interactive experience. Due to the nature and technical limitations of IoT devices, security experts have expressed concerns over the effectiveness and security level of smart devices. The importance of securing IoT devices has an increased weight when it pertains to smart toys, since sensitive information of children and teenagers can potentially be compromised. Furthermore, various security analyses on smart toys have discovered a worryingly high number of important security flaws. The master thesis focuses on the topic of smart toys’ security by first presenting and analyzing the necessary literature background. Furthermore, it presents a case study where a smart toy is selected and analyzed statically and dynamically utilizing a Raspberry Pi. The aim of this thesis is to examine and apply methods of analysis used in the relevant literature, in order to identify security flaws in the examined smart toy. The smart toy is a fitness band whose target consumers involve children and teenagers. The fitness band is communicating through Bluetooth with a mobile device and is accompanied by a mobile application. The mobile application has been installed and tested on an Android device. Finally, the analyses as well as their emerged results are presented and described in detail. Several security risks have been identified indicating that developers must increase their efforts in ensuring the optimal level of security in smart toys. Furthermore, several solutions that could minimize security risks and are related to our findings are suggested, along with potentially interesting topics for future work and further research

Internet of Things Security Case Studies and Internet of Things Core Service Comparions

This culminating project conducted an analysis of IoT security breach case studies. The analysis identified numerous vulnerable points: software failure, node tampering attack, eavesdropping, code injection, unauthorized access, social engineering attack, hardware exploitation, and node insertion. It therefor seems that even with the proper tests conducted on vulnerabilities to discover solutions, regular end users are unable to apply patches or other technical solutions to protect themselves. This project solely focuses on analyzing of comprehensive IoT security services that come with devices connected to home network. The devices are those provided by the big three: Amazon, Google, and Microsoft, on the communication between platform and devices, how they are protected, and how costs vary depending on different situations. Also, performance differences were analyzed among different solutions based on three different scenarios with different number of settings to give a deeper insight to users. There are comparisons throughout the paper, but it is to help normal users make better choices depending on their different situations and purpose of usage

Risk driven models & security framework for drone operation in GNSS-denied environments

Flying machines in the air without human inhabitation has moved from abstracts to reality and the concept of unmanned aerial vehicles continues to evolve. Drones are popularly known to use GPS and other forms of GNSS for navigation, but this has unfortunately opened them up to spoofing and other forms of cybersecurity threats. The use of computer vision to find location through pre-stored satellite images has become a suggested solution but this gives rise to security challenges in the form of spoofing, tampering, denial of service and other forms of attacks. These security challenges are reviewed with appropriate requirements recommended. This research uses the STRIDE threat analysis model to analyse threats in drone operation in GNSS-denied environment. Other threat models were considered including DREAD and PASTA, but STRIDE is chosen because of its suitability and the complementary ability it serves to other analytical methods used in this work. Research work is taken further to divide the drone system into units based in similarities in functions and architecture. They are then subjected to Failure Mode and Effects Analysis (FMEA), and Fault Tree Analysis (FTA). The STRIDE threat model is used as base events for the FTA and an FMEA is conducted based on adaptations from IEC 62443-1-1, Network and System Security- Terminology, concepts, and models and IEC 62443-3-2, security risk assessment for system design. The FTA and FMEA are widely known for functional safety purposes but there is a divergent use for the tools where we consider cybersecurity vulnerabilities specifically, instead of faults. The IEC 62443 series has become synonymous with Industrial Automation and Control Systems. However, inspiration is drawn from that series for this work because, drones, as much as any technological gadget in play recently, falls under a growing umbrella of quickly evolving devices, known as Internet of Things (IoT). These IoT devices can be principally considered as part of Industrial Automation and Control Systems. Results from the analysis are used to recommend security standards & requirements that can be applied in drone operation in GNSS-denied environments. The framework recommended in this research is consistent with IEC 62443-3-3, System security requirements and security levels and has the following categorization from IEC 62443-1-1, identification, and authentication control, use control, system integrity, data confidentiality, restricted data flow, timely response to events and resource availability. The recommended framework is applicable and relevant to military, private and commercial drone deployment because the framework can be adapted and further tweaked to suit the context which it is intended for. Application of this framework in drone operation in GNSS denied environment will greatly improve upon the cyber resilience of the drone network system

A Survey of Security in UAVs and FANETs: Issues, Threats, Analysis of Attacks, and Solutions

Thanks to the rapidly developing technology, unmanned aerial vehicles (UAVs) are able to complete a number of tasks in cooperation with each other without need for human intervention. In recent years, UAVs, which are widely utilized in military missions, have begun to be deployed in civilian applications and mostly for commercial purposes. With their growing numbers and range of applications, UAVs are becoming more and more popular; on the other hand, they are also the target of various threats which can exploit various vulnerabilities of UAV systems in order to cause destructive effects. It is therefore critical that security is ensured for UAVs and the networks that provide communication between UAVs. In this survey, we aimed to present a comprehensive detailed approach to security by classifying possible attacks against UAVs and flying ad hoc networks (FANETs). We classified the security threats into four major categories that make up the basic structure of UAVs; hardware attacks, software attacks, sensor attacks, and communication attacks. In addition, countermeasures against these attacks are presented in separate groups as prevention and detection. In particular, we focus on the security of FANETs, which face significant security challenges due to their characteristics and are also vulnerable to insider attacks. Therefore, this survey presents a review of the security fundamentals for FANETs, and also four different routing attacks against FANETs are simulated with realistic parameters and then analyzed. Finally, limitations and open issues are also discussed to direct future wor

Discrete Moving Target Defense Application and Benchmarking in Software-Defined Networking

Moving Target Defense is a technique focused on disrupting certain phases of a cyber-attack. The static nature of the existing networks gives the adversaries an adequate amount of time to gather enough data concerning the target and succeed in mounting an attack. The random host address mutation is a well-known MTD technique that hides the actual IP address from external scanners. When the host establishes a session of transmitting or receiving data, due to mutation interval, the session is interrupted, leading to the host’s unavailability. Moving the network configuration creates overhead on the controller and additional switching costs resulting in latency, poor performance, packet loss, and jitter. In this dissertation, we proposed a novel discrete MTD technique in software-defined networking (SDN) to individualize the mutation interval for each host. The host IP address is changed at different intervals to avoid the termination of the existing sessions and to increase complexity in understanding mutation intervals for the attacker. We use the flow statistics of each host to determine if the host is in a session of transmitting or receiving data. Individualizing the mutation interval of each host enhances the defender game strategy making it complex in determining the pattern of mutation interval. Since the mutation of the host address is achieved using a pool of virtual (temporary) host addresses, a subnet game strategy is introduced to increase complexity in determining the network topology. A benchmarking framework is developed to measure the performance, scalability, and reliability of the MTD network with the traditional network. The analysis shows the discrete MTD network outperforms the random MTD network in all tests

Drone Base Station Trajectory Management for Optimal Scheduling in LTE-Based Sparse Delay-Sensitive M2M Networks

Providing connectivity in areas out of reach of the cellular infrastructure is a very active area of research. This connectivity is particularly needed in case of the deployment of machine type communication devices (MTCDs) for critical purposes such as homeland security. In such applications, MTCDs are deployed in areas that are hard to reach using regular communications infrastructure while the collected data is timely critical. Drone-supported communications constitute a new trend in complementing the reach of the terrestrial communication infrastructure. In this study, drones are used as base stations to provide real-time communication services to gather critical data out of a group of MTCDs that are sparsely deployed in a marine environment. Studying different communication technologies as LTE, WiFi, LPWAN and Free-Space Optical communication (FSOC) incorporated with the drone communications was important in the first phase of this research to identify the best candidate for addressing this need. We have determined the cellular technology, and particularly LTE, to be the most suitable candidate to support such applications. In this case, an LTE base station would be mounted on the drone which will help communicate with the different MTCDs to transmit their data to the network backhaul. We then formulate the problem model mathematically and devise the trajectory planning and scheduling algorithm that decides the drone path and the resulting scheduling. Based on this formulation, we decided to compare between an Ant Colony Optimization (ACO) based technique that optimizes the drone movement among the sparsely-deployed MTCDs and a Genetic Algorithm (GA) based solution that achieves the same purpose. This optimization is based on minimizing the energy cost of the drone movement while ensuring the data transmission deadline missing is minimized. We present the results of several simulation experiments that validate the different performance aspects of the technique