how can you make sure that you manipulate so that you are looking for your independent-dependent variable correlation. Try to spruce that part up just a little as you have a lot of variables and external factors in the experiment, but do not offer a high level of manipulation to find what you want. Or do you not want much researcher interference for other reasons? Break the measurement into operationalization steps 1 and 2 . Operationalizing is a concept that involves a series of steps: 1. Define the construct you want to measure. 2. Determine the content of the measure (instrument or questionnaire) that measures the concept.

Topic

Is the usage of quantum computing technology potentially dangerous for the cybersecurity industry's present encryption techniques in self-driving cars?

Economic Impact: If the self-driving cars are compromised with cyberattacks with quantum technology, then there will be fall of self-driving cars in automotive industries due to less security.

Theoretical Framework:

Independent Variables Moderating Variable Dependent Variable

Independent Variables: Policies and Compliances laws necessary to regulate the responsible use of quantum computing technology and also our current conventional computing technology.

Moderating Variable: ECM or Electronic control Module, quantum computers have the ability to target electronic control modules (ECMs) in automobiles. The existing encryption algorithms used to safeguard ECMs may be broken by quantum computers, allowing attackers to take over vehicles and make them malfunction. So Automotive industries need to develop a more secure and advanced ECM that can resist quantum attacks.

Dependent Variable: Encryption currently is vulnerable to quantum technology. It directly depends on the independent variable where encryption can be made stronger if the policies and compliances laws are also developed as strong and secure with respect to time, as there is a race for this quantum technology.

Mediating Variable: Time take to implement best practices, laws, security firewalls, better encryption before the quantum technology is at its potential.

Hypothesis:

Hypothesis 1: Quantum computing could make self-driving cars less safe because it could be used to hack them.

Hypothesis 2: To make self-driving cars safer, we need to develop new encryption methods that cannot be hacked by quantum computers.

Scope of Research

Identify the Best Practices and security policies, laws and compliances that can be adopted so that the vulnerabilities are minimized.

To provide awareness to general public on the threat of leap in quantum computing technology, explore for more compliances, policies and laws to make it more secure.

Research Strategy

This is an exploratory research because we researching a new and emerging technology and their potential impact when they are fully developed. And also take surveys and interviews with industrial experts and SME on how it can be impactful and what is the counter measures. This approach is chosen to comprehensively address the multifaceted nature of the research question, combining the strengths of qualitative insights and quantitative analysis.

Theory Triangulation utilizing existing theories from both quantum computing and cybersecurity to provide a comprehensive understanding of the research problem.

By employing a mixed-methods approach and triangulation techniques, this research aims to provide a holistic understanding of the potential impact of quantum computing on self-driving car cybersecurity, offering valuable insights for industry stakeholders and policymakers

Data Collection Instrumental

Quantitative data:

Web scraping using PowerBi built in console and to create dashboard for better concept visualization data about self-driving cars and their Standard AES encryption

Types of RSA encryption in current technology and their keys.

Observation like experimental videos on the quantum computing technology

Qualitative Data

Conducting Survey to know better level of understanding among a group audience

Interviews with industrial experts and Subject Matter Experts

Document Analysis, going through existing data and papers and research works by industries and academics.

Data Collection Procedure

The steps in the data collection process are as follows:

Gather the data. After pilot testing and revision of the data collection tools, the researcher can start gathering data. This may entail conducting interviews, questionnaires, or participant observation.

Data preparation and cleaning. Data needs to be cleaned up and prepared for analysis after it has been gathered. This could entail classifying the data and purging it of any faulty or incomplete information.

Planned Data Analysis

Knowing vulnerabilities in current encryption through surveys.

Find out what is the better security encryption against quantum Computer

Quantitative data will be analyzed using statistical techniques to identify trends and patterns.

Qualitative data from interviews will be analyzed using thematic analysis.

Simulations will provide practical insights into the potential vulnerabilities.

Research Setting

The research will be conducted in a controlled academic and experimental setting, involving simulations and expert interviews.

Research Interface

Correlational research interface

Drawing conclusion from the surveys, interviews, document analysis on the threats of security in the self-driving cars against the quantum computer and how these know vulnerabilities can be avoided and effective firewalls and Counter measures has to be updated with best security policies and following the best practice.

Time Horizon

The research will be conducted until semester exam, allowing sufficient time for data collection, analysis, and synthesis of findings.

Research Design

Explanatory Design in which our Independent variable is Policies, Compliances and laws and the Dependent variable is Encryption.

Quantifying dependent variable which is Encryption

The dependent variable can be quantified currently by the key size, the larger the key size means stronger the algorithm is such as AES 256 encryption where in short text keys are expanded to large series of numbers

in multiple rounds making it harder to break .

In order to test the hypothesis cause and effect relationship is established.

Based on our Hypothesis 1

For Example a potential experiment if the encryption fails in the cars and quantum technology has almost hacked the hardware but if the policies and compliances where strict or more broader like involving physical access of key or a Onetime Generation of password (OTP) is enforced where a second intervention is needed to access data even when the hardware has been compromised.

Manipulation

Policies and Compliances has to be in accordance to SAE autonomous driving Level 5 so that that if encryption is failed but if the policies & compliance regulation is enforced and access remains restriction due different levels of protection such as another factor requirement, can still protect sensitive data like Onetimepassword or physical key on board to share data requirement.

Treatment

If the Policies and Compliances are defined to the highest strict adherence and regulation to access of data and there sharing to prevent wrong or ill usage of data for monetary gains can be still prevented based on how the risk is analyzed and resulting compliance regulation should be enforced on the data present onboard of a car.

Based on our Hypothesis 2

Manipulation

We can strengthen the encryption by increasing the key size or by having a cluster of AES 256 keys so it becomes harder to break the logic.

Hybrid Encryption: Implement hybrid encryption schemes that combine classical and post-quantum cryptographic algorithms. This approach can provide a higher level of security by mitigating quantum threats while maintaining compatibility with existing systems.

Treatment:

To develop new encryption methods that cannot be hacked by quantum computers, we need to use post-quantum cryptography (PQC). PQC is a type of cryptography that is designed to be resistant to attacks from quantum computers. There are a number of different PQC algorithms that have been developed, and researchers are still working on developing new and improved algorithms.

Field Experiment:

One way to test the effectiveness of PQC algorithms is to conduct a field experiment. In a field experiment, self-driving cars would be equipped with PQC encryption algorithms and then deployed in a real-world environment. Researchers would then monitor the cars for signs of attack.

Variables and External Factors:

There are a number of variables that would need to be considered when designing a field experiment to test the effectiveness of PQC algorithms in self-driving cars. These variables include:

• The type of PQC algorithm used
• The hardware and software used in the self-driving cars
• The environment in which the self-driving cars are deployed
• The types of attacks that are being tested against

External factors that could affect the results of the field experiment include:

• The availability of quantum computers
• The skills and resources of attackers
• The regulatory environment

Survey and Interview with SMEs:

Another way to gather information about the potential threat of quantum computing to self-driving cars is to conduct a survey and interview with subject matter experts (SMEs). SMEs are individuals who have expertise in quantum computing, cryptography, or self-driving cars.

Survey questions could include:

• How likely do you think it is that quantum computers will be used to hack self-driving cars in the next 5 years?
• What are the biggest challenges to developing PQC algorithms that are effective and efficient?
• What are the most promising PQC algorithms for self-driving cars?

Interview questions could include:

• What are your thoughts on the potential threat of quantum computing to self-driving cars?
• What are the biggest challenges that the self-driving car industry needs to address in order to protect against quantum computing attacks?
• What are your recommendations for developing and deploying PQC algorithms in self-driving cars?

By conducting a field experiment and surveying and interviewing SMEs, we can gather valuable information about the potential threat of quantum computing to self-driving cars and identify strategies for developing and deploying PQC algorithms to protect against these threats.

Measurement & Measure

Measuring the effect of Independent variable on the dependent variable.

The independent variable which is policies, laws and compliances and the dependent variable which is encryption.

Based on our Hypothesis 1, there are a few approaches to gauge the impact of laws, regulations, and compliances with the present encryption in self-driving cars when they are breached by a quantum computer.

• Counting the number of successful hacks is one method. This could be accomplished through the use of simulations or by studying actual data from hacking occurrences. For instance, a business may track the number of successful hacks of its fleet of self-driving cars over time.
• Assessing the severity of attacks is a different way to gauge the impact of encryption. This could be accomplished by evaluating the harm brought on by the hacks, including the quantity of injuries or fatalities, the degree of property damage, and the financial losses that were sustained. A government agency, for instance, might track the number and severity of self-driving car hacks over time in their nation.
• In addition, the impact of encryption on public confidence in autonomous vehicles might be examined. This could be achieved by conducting surveys or by examining the sentiment on social media. After a significant hacking incident, a corporation may, for instance, gauge the proportion of people who say they trust self-driving cars.

The impact of quantum computer hacking on self-driving cars could be impacted by various forms of policies, laws, and compliances, as shown by the following specific examples:

• Strong encryption is a requirement for self-driving automobiles under the following laws: These regulations may aid in lowering both the frequency and seriousness of successful hacks. For instance, a government agency may mandate that all autonomous vehicles be outfitted with encryption that is impervious to quantum computing.
• Laws that make self-driving car operators and manufacturers accountable for hacks: Manufacturers and operators may be encouraged by these laws to use robust encryption and other security measures. A government body may, for instance, enact legislation that makes operators and makers of self-driving cars responsible for any harm brought on by hacking.
• Compliance standards for self-driving cars: These standards may help to guarantee that the vehicles are operated in a secure and safe manner. For instance, a government body may mandate that a set of security standards, including encryption requirements, be followed by all self-driving car manufacturers.

This shows how vital the independent variable can be to secure data through encryption which is the dependent variable.

Budget

No costs involved or kept at a minimum cost.

Research Ethics

Ethical considerations will be adhered to throughout the research, including obtaining informed consent from participants and ensuring the anonymity and confidentiality of their responses.