Hi!

After having made the basic presentation of the research, it is time to prepare the organization of resources and other elements to carry it out.

Research project title and Introduction

Research project title:

• Improved Android device unlocking methods

Introduction:

• Today, mobile devices contain a wealth of information about the people who use them, and these devices are well protected by gesture locks, complex passwords, fingerprints, and the ability to encrypt data so that it cannot be accessed in any way without first authenticating. The problem is that the tools that ordinary citizens use to preserve their privacy are also used by criminals to protect their data from investigators and law enforcement. Ensuring that law enforcement can unlock the mobile devices of criminals of all kinds, including sex offenders, traffickers, and terrorists, can be the difference between a conviction and a dangerous criminal at large who may commit an attack, sexually assault an adult or minor, or any other heinous crime. This project aims to develop a system based on complex calculations, learning systems and artificial intelligence that guarantees an unlocking rate close to 100% through non-invasive methods that preserve the integrity of the devices and the data they contain.

Define the global objectives and the work plan

General objectives:

General Objectives:

• Develop advanced algorithms based on artificial intelligence and machine learning for unlocking Android mobile devices.
• Improve the success rate in unlocking Android mobile devices using non-invasive methods that preserve the integrity of the devices and the data they contain.

Specific Objectives:

• Analyze and evaluate current Android mobile device unlocking methods used in forensic investigations.
• Design and develop new machine learning algorithms that can be adapted to different models and versions of Android devices.
• Implement artificial intelligence techniques to improve the accuracy and speed of unlocking algorithms.
• Conduct extensive testing of the developed algorithms in a controlled environment to assess their effectiveness and efficiency.
• Compare the results obtained with traditional unlocking methods to determine the improvements achieved.
• Document and publish research findings to contribute to knowledge in the field of security and computer forensics.

Working team:

In order to carry out this research, the following profiles will be needed in addition to the principal investigator.

• Principal investigator: Must be an expert in the area of ​​computer security, especially in the field of mobile device forensic investigation. Must have knowledge of academic research and experience in managing research projects.
• Artificial Intelligence (AI) and Machine Learning specialist profile: Must be an expert in Artificial Intelligence and machine learning techniques, who can design, implement and optimize the algorithms necessary for unlocking Android devices.
• Computer Security and Digital Forensics specialist profile: Must be an expert in computer security and digital forensics, who can apply cybersecurity principles and forensic analysis in unlocking devices without compromising the data or integrity of the devices.
• Programming expert profile (Software Engineer): Must be a developer with expertise in systems programming (Python, Java and GoLang) who can implement AI and Machine Learning algorithms, as well as the infrastructure necessary to test the unlocking methods on Android devices.
• Data expert profile (Data and Statistics Analyst): Must be an expert in data analysis, capable of interpreting test results and drawing valid conclusions, so must have knowledge of statistical techniques to analyze the results of successful tests and evaluate the improvement with respect to traditional methods, and must have the ability to generate clear and understandable reports, effectively presenting the findings, thus facilitating the work of forming scientific studies.
• Data Protection and Legal Aspects Specialist Profile: Must be an expert in data protection and legal aspects of cybersecurity, who can advise on the legality of access to devices and the ethical implications of the work. This profile is not considered important throughout the entire process, but is considered a profile that can be hired for specific consultations.

Work packages (WPs):

In this section, the work packages (WP) will be presented as a breakdown of the fundamental elements that will allow defining the steps necessary to complete the work.

The set of work packages that make up the research project is provided.

Each work package will contain:

• The objectives in the WP.
• The problem that is intended to be solved, including a preliminary approach.
• List of tasks that will lead to the fulfillment of the objective.
• The team members assigned to each task.
• Planned calendar.

NOTE: The work will be carried out on the specific objectives of the research.

Objective 1.0: Analyze and evaluate current Android mobile device unlocking methods used in forensic investigations.

• WP 1.1. Review with the team the different methods on which the research will be based and the tests carried out by the team.
  • The aim is to determine which working methods are most relevant, those that will provide the most value to the ongoing research.
  • The problema to solve is the understanding scope and relevance of existing metods and ensure research builds on prior knowledge.
  • The involvement of the entire team is required, except for the legal profile, which will only be contacted for specific questions.
  • Estimated time: three working days since everything has been previously reviewed.
• WP 1.2. Determine the methods that will be used.
  • In this section, once the most relevant methods have been determined, it is necessary to select those that will be used because they will provide the best performance.
  • The problema to solve is to chooese methotds that can maximize the project’s impact and ensure the applicability to a wide range of devices.
  • The involvement of the entire team is required, except for the legal profile, which will only be contacted for specific questions.
  • Estimated time: two working days since everything has been previously reviewed.
• WP 1.3. Determine the methods that need to be improved.
  • Mail goa lof this work package will review the methods that need improvement, determining the points where this improvement can be achieved.
    The problema to solve is the understanding of witch methods have weaknesses that could be addressed to improve unlocking success rates.
  • The involvement of the entire team is required, except for the legal profile, which will only be contacted for specific questions.
  • Estimated time: three working days since everything has been previously reviewed.

Objective 2.0: Design and develop new machine learning algorithms that can be adapted to different models and versions of Android devices.

• WP 2.1. Research and design initial algorithm frameworks.
  • The main objective is to design the initial frameworks for the machine learning algorithms to be used and to adapt them to different models.
  • The problem to be solved is to determine the best machine learning approach to perform best with the different working models on the devices. To do this, different machine learning techniques will be explored and the most appropriate one will be selected.
  • For this part, the team members will be the AI ​​and machine learning specialist, Software Engineer.
  • Estimated time: Five business days.
• WP 2.2. Develop machine learning algorithms.
  • The objective of this WP is to implement the algorithms based on the chosen frameworks.
  • The problems to be solved in this section are to try to translate the algorithm design that has been made into functional code applicable to the models treated for unlocking Android devices. This will be done by writing the machine learning code in the selected languages.
  • The members assigned to this WP are the AI ​​and machine learning specialist, Software Engineer.
  • Estimated time: Seven working days.
• WP 2.3: Algorithm refinement.
  • The main objective of this WP is to perform exhaustive tests to validate the effectiveness of the selected and developed algorithms, as well as their refinement to achieve greater accuracy. The second objective in this regard would be to improve their speed if possible. .
  • The problem to be solved is to ensure that the machine learning algorithms work as well as possible and, if possible, that they are reusable on different models for unlocking Android devices.
  • The tasks to be performed are to run the algorithms in test environments to collect performance information and refine the algorithms if necessary.
  • The team members who will be assigned to this WP are the AI ​​and Machine Learning Specialist, Software Engineer, Forensic Expert.
  • Estimated time: Seven business days.

Objective: 3.0: Implement artificial intelligence techniques to improve the accuracy and speed of unlocking algorithms.

• WP 3.1: Integration of AI techniques into existing unlocking methods.
• The main objective is to improve unlocking methods by integrating AI techniques to improve accuracy, and if possible speed.
• The problem to be solved is to find the best AI techniques to add to existing methods to make them optimal.
• The tasks contemplated are to review the appropriate AI techniques for optimization and modify the algorithms incorporating improvements in AI for optimization.
• The team members assigned to this WP should be the AI ​​and machine learning specialist and the forensic expert.
• Estimated time: Five business days.
• WP 3.2: Optimizing AI-enhanced algorithms.
• The main goal is to ensure that AI-enhanced algorithms are more accurate than traditional methods and faster if possible, or at least do not degrade their performance.
• The problem to be solved is to improve the probability of unlocking the terminals and if possible minimize the time needed to unlock the device.
• The tasks to be performed will be to use performance benchmarks to compare improved algorithms and to refine the algorithms.
• The team members assigned to this WP are the AI ​​and Machine Learning Specialist, Software Engineer.
• Estimated time: six business days.

Objective 4.0: Conduct extensive testing of the developed algorithms in a controlled environment to assess their effectiveness and efficiency.

• WP 4.1: Set up a controlled test environment.
• The goal of this WP is to create an environment in which the developed algorithms can be tested, observed, and measured for performance.
• The problem to be solved is to ensure that the test environment built is representative of real-world scenarios while maintaining control over the variables applicable to this investigation.
• The tasks to be performed in this WP are to select a variety of Android devices to perform testing as well as to set up the infrastructure necessary for testing.
• The team members assigned to this part are the software engineer and the forensic expert.
• Estimated time: Four business days.
• WP 4.2: Conduct initial testing of algorithms.
• The goal of this section will be to test the algorithms developed and improved with AI in the controlled environment.
• The problem to be solved is to verify that the algorithms work correctly and there are no false positives, execution failures, or other distortions.
• The tasks of this WP are to run each algorithm a certain number of times in the test environment to record and analyze its performance data.
• The team members assigned to this WP are the AI ​​and Machine Learning Specialist, Software Engineer, Forensic Expert.
• Estimated time: Six business days.
• WP 4.3: Analyze test results and optimize algorithms.
• The goal of this part is to use the data previously collected in the tests to analyze the effectiveness of the algorithms. Based on this, the necessary adjustments will be made.
• The problem to be solved is to understand the reasons why failures or inefficiencies occur and to improve the algorithms.
• The tasks that fall within this section are to analyze the test results and refine the algorithms based on the results of these tests.
• The team members assigned to this WP are the data expert, the AI ​​and machine learning specialist, and the forensic analysis expert.
• Estimated time: Five business days.

Objective 5.0: Compare the results obtained with traditional unlocking methods to determine the improvements achieved.

• WP 5.1: Define evaluation criteria for comparison.
• The goal of this WP is to establish the criteria that will be used to compare new unlocking methods with the commonly used (traditional) methods.
• The problem to be solved in this section is to determine the metrics that will be most effective in demonstrating improvements. A lot of data has been collected so far, but the most interesting ones for us can now be seen.
• The tasks to be performed in this WP are to review the existing benchmarks for unlocking mobile devices and define the key performance indicators (KPIs) for comparison, which can be accuracy, success rate or speed.
• The team members assigned to this part will be the data expert, the lead investigator and the forensic expert.
• Estimated time: three business days.
• WP 5.2: Collect data on traditional unlocking methods.
• The goal is to collect data on traditional unlocking methods in terms of their success rates, false positives, crashes, or time efficiency to have a baseline for comparison.
• The problem to be solved is to make sure that enough data is collected to make a valid comparison of the data obtained with our models.
• The tasks to be performed are to test traditional unlocking methods on various devices within our lab and collect data on unlocking time, success rate, errors, etc.
• The team members assigned to the team should be the forensic expert and the software engineer.
• Estimated time: Two business days.
• WP 5.3: Comparison of new unlocking methods with the methods used so far.
• The objective of this WP is to analyze and compare the performance of the developed unlocking methods against traditional methods based on the established criteria.
• The problem to be solved is to validate whether the new methods outperform the traditional ones in terms of the KPIs established in another of the WPs.
• The tasks to be performed in this WP are to compare the performance metrics of the new methods against the traditional methods and then prepare a comparative report between the two.
• The team members assigned to this section are the data expert, the AI ​​and machine learning specialist, and the forensic expert.
• Estimated time: Five business days.

Objective 6.0: Document and publish research findings to contribute to knowledge in the field of security and computer forensics.

• WP 6.1: Prepare documentation related to the research findings, as well as documentation of the methodology.
• The objective of this WP is to document the research process, methods, results and conclusions derived from them. In addition, it is intended to ensure that the findings of the research project are communicated correctly.
• The problem to be solved is to organize all the research data into a coherent report, with a solid scientific basis that can be published and valued by the academic community.
• The tasks to be performed are the collection of all the data and analysis of the project, as well as writing detailed documentation of the methodology and results.
• The members assigned to this part are the principal investigator, the data expert and the forensic expert.
• Estimated time: Ten business days.
• WP 6.2: Review and refine documentation.
• The goal is to ensure that research documentation is as accurate, high-quality, and error-free as possible before presentation in scientific journals and conferences.
• The problem to be solved is to ensure that findings are presented clearly, accurately, completely, and above all, without errors.
• The tasks to be performed are to review documentation for clarity, accuracy, and completeness. Make necessary revisions based on team feedback.
• The team members who should be assigned to this WP are the principal investigator, the data expert, and the forensic expert.
• Estimated time: Five business days.
• WP 6.3: Publish and disseminate research results.
• The objective is to submit the research to academic journals, conferences or other platforms to share the research results with the scientific community.
• The problem to be solved is to identify the best means for publication and to ensure that the research reaches the appropriate audience.
• The tasks to be performed are to identify suitable journals or conferences for publication, present the research and the results presented at conference events most relevant to the research field.
• The team members assigned to this research are the Principal Investigator, as well as the Data Expert.
• Estimated time: Five business days.
• WP 6.4. Present at international conference.
• The objective is to present the research at an international conference in order to share the results of the research with the scientific community attending that event.
• The problem to be solved is to present the results at a specialized conference to ensure that the research reaches the appropriate audience.
• The tasks to be performed are to travel to the academic body that gives the conferences, spend two days acclimatizing to jet lag, present the research and the results at a conference event relevant to the field of research.
• The team members assigned to this research are the Principal Investigator, as well as the Data Expert.
• Estimated time: Seven calendar days (Travel and acclimatization days are included to overcome, at least in part, jet lag).

It is important to note that, when no member of the group is expressly mentioned, he or she will be making improvements to the procedures or preparing documentation associated with his or her functions.

As regards the principal investigator, he or she will be involved in all processes. If he or she is not expressly named, he or she will be carrying out tasks related to team or project management.

Table. Time relationship by WP

We continue with a second block of this module.
Best regards