Dario Javier Catagua Zambrano
Universidad
Técnica de Manabí
Portoviejo, Ecuador.
Denise Soraya Vera Navarrete
Universidad Técnica de Manabí
Portoviejo, Ecuador.
DOI: https://doi.org/10.56124/encriptar.v9i17.007
Resumen
Este
artículo describe cómo Ecuador se posiciona como el tercer país latinoamericano
con mayor incidencia de ciberdelincuencia, un problema exacerbado por la rápida
transformación digital y un marco legal obsoleto. Además, este estudio realiza
un análisis comparativo del rendimiento de herramientas forenses digitales
potenciadas con inteligencia artificial (IA)—Autopsy, Magnet AXIOM y Belkasoft
Evidence X—con el objetivo de identificar soluciones para fortalecer las
investigaciones digitales en el país. La metodología adoptada fue mixta,
combinando el procesamiento técnico de una imagen forense estandarizada (ntfs1-gen1.E01)
con una encuesta dirigida a expertos, académicos y profesionales del sector.
Los resultados técnicos mostraron que Magnet AXIOM, gracias a su IA nativa
integrada, procesó la evidencia en 50 segundos, demostrando excelencia en
velocidad y automatización. Belkasoft Evidence X sobresalió en la recuperación
de evidencia, identificando 74 elementos multimedia mediante sus filtros
semánticos visuales e interfaz intuitiva. Autopsy, aunque notablemente más
lento y dependiente de la instalación manual de plugins externos para emular
funcionalidades de IA, se confirmó como una opción viable para instituciones
con limitaciones presupuestarias. La encuesta reveló una brecha formativa
crítica: el 75% de los profesionales utiliza estas herramientas solo "ocasionalmente",
lo que destaca una desconexión entre el potencial tecnológico y la práctica
común. Se concluye que la implementación de estas tecnologías debe ir
acompañada de programas masivos de capacitación especializada y una
actualización integral del marco legal ecuatoriano, el cual debe tipificar los
delitos digitales modernos y establecer protocolos para validar legalmente las
evidencias obtenidas mediante IA.
Palabras
clave:
forensia digital, inteligencia artificial, ciberdelincuencia, herramientas
digitales, investigación digital.
Comparative analysis of AI-powered digital forensics tools in the
context of cybercrime in Ecuador.
ABSTRACT
This article describes how Ecuador
ranks as the third Latin American country with the highest incidence of
cybercrime, a problem exacerbated by rapid digital transformation and an
outdated legal framework. Furthermore, this study conducts a comparative
analysis of the performance of digital forensic tools enhanced with artificial
intelligence (AI)—Autopsy, Magnet AXIOM, and Belkasoft Evidence X—aiming to
identify solutions to strengthen digital investigations in the country. The
methodology adopted was mixed, combining the technical processing of a
standardized forensic image (ntfs1-gen1.E01) with a survey targeting experts,
academics, and industry professionals. The technical results showed that Magnet
AXIOM, thanks to its integrated native AI, processed the evidence in 50
seconds, demonstrating excellence in speed and automation. Belkasoft
Evidence X excelled in evidence recovery, identifying 74 multimedia items
through its visual semantic filters and intuitive interface. Autopsy, although
noticeably slower and reliant on the manual installation of external plugins to
emulate AI functionalities, was confirmed as a viable option for institutions
with budget constraints. The survey revealed a critical training gap: 75% of
professionals use these tools only "sometimes," highlighting a
disconnect between technological potential and common practice. It is concluded
that the implementation of these technologies must be accompanied by massive specialized training programs and a comprehensive
update of the Ecuadorian legal framework, which should criminalize modern
digital crimes and establish protocols to legally validate evidence obtained
through AI.
Keywords: digital forensics,
artificial intelligence, cybercrime, digital tools, digital investigation.
1. Introduction
The situation of cybercrime in Ecuador is experiencing
alarming growth, positioning the country as the third with the highest
incidence in Latin America, only behind Mexico and Bolivia (Saltos Salgado et al., 2021), (Del Pozo Carrasco et al., 2024). This phenomenon, aggravated by the accelerated
digital transformation during the pandemic, is predominantly evidenced in
electronic fraud, ransomware, phishing, and identity theft, critically
affecting the financial sector and government institutions. Consequently,
Ecuador ranks 119th out of 182 countries in terms of vulnerabilities to
cyberattacks (Ponce Tubay, 2024), (Hernández Alvarado et al., 2024). Faced with this reality, the investigative and
judicial response is hampered by a legal framework that experts describe as
obsolete and fragmented. The Organic Comprehensive Penal Code (COIP) exhibits
problems similar to those identified in other
countries in the region, such as in Colombia, where low effectiveness in the
application of its specialized law against cybercrime has been reported (Rincón, J., Quijano, et al., 2022). In the Ecuadorian
context, this translates into a lack of a specific section in the COIP for
these offenses, and sanctions that may not be proportionate to the damage
caused.
The inability of traditional digital forensic methods
to process the volume, speed, and heterogeneity of digital data generated in
these incidents aggravates the problem. Investigations become slow, prone to
human error, and frequently inadequate for examining evidence from diverse
sources like the cloud, IoT devices, and social networks (Jarrett & Choo, 2021), (Dunsin et al., 2024). This technological gap between criminals and
investigators highlights the urgent need to adopt advanced solutions based on
Artificial Intelligence (AI) and Machine Learning (ML) to automate tasks,
correlate massive evidence, and detect complex patterns that conventional human
analysis misses (Adam & Varol, 2020).
The integration of AI into digital forensics through
methods ranging from Deep Learning (DL) for malware identification (Qureshi et al., 2024) and image forgery detection to
ontological engineering for automated reasoning, promises to revolutionize the
field. Tools compared in practical studies, such as Magnet AXIOM, Autopsy, and Belkasoft Evidence, demonstrate significant advances in
evidence recovery and analysis (Sunardi et al., 2022). However, this automation introduces critical
challenges of transparency and trust. "Black box" models make it
difficult to interpret decisions, compromising the admissibility of digital
evidence in court and the fundamental right to a fair legal process (Khalid et al., 2024), (Stoykova, 2024).
This latter aspect highlights an essential tension:
the need for investigative efficiency versus the obligation to guarantee
procedural rights. Emerging concepts such as the "right to procedural
accuracy" and Explainable AI (XAI) frameworks seek to balance this
equation, proposing governance that ensures digital evidence generated or
processed by AI is auditable, understandable, and contestable by the defense.
This need for transparency is crucial even in contexts of international
cooperation and cloud search orders, where AI-assisted protocols, like the
CDRP, aim to resolve forensic disputes between providers and clients without
direct human intervention (Alashjaee, 2024).
In the Ecuadorian context, this problem intensifies.
Research reveals a lack of specific regulations for the use of digital
forensics even in government audits (Caraguay Ramírez, 2020), insufficient training of judicial operators, and a
critical disconnect between academia and forensic professionals in practice (Hargreaves et al., 2024). The disparity in the legal classification of
cybercrimes, a problem also observed in Mexico (Alcalá Casillas, M. G., & Melendez Ehrenzweig, M.
Á., 2023), and the need for a unified federal law, contrast
with the sophistication of cybercriminals, whose criminological profile is
characterized by a lack of empathy, high technical capacity, and adaptability (Díaz Samper et al., 2024).
Therefore, this research is proposed as a response to
this urgent need. The general objective of this work is to compare and analyze
the technical performance and suitability within the Ecuadorian legal framework
of a selected set of AI-powered digital forensic tools. The central
contribution of this article lies in generating a contextualized comparative
analysis for Ecuador's reality, integrating technical, legal, and ethical
dimensions. As a concrete product, it seeks to propose an evaluation framework
or protocol that allows judicial and police institutions to select and
implement these tools in an informed manner, ensuring their use is both
effective and respectful of fundamental rights.
This research is based on the analysis of several
fundamental studies published between 2020 and 2025, covering topics from
technical proposals for automation and big data analysis to in-depth legal (du Toit, 2022), (Álvarez-Valenzuela & Hevia Angulo, 2020), criminological, and situational crime prevention
strategy analyses. This work aims to
comparatively examine AI-based digital forensic analysis tools, focusing on
their application in the Ecuadorian context, considering technical and legal
aspects. By evaluating Autopsy, Magnet AXIOM, and Belkasoft
Evidence X, it seeks to identify their strengths and weaknesses and propose
ways to strengthen the regulatory and technical framework in Ecuador, thereby
contributing to a more robust cybersecurity system tailored to the country's
needs.
2. Methodology
The purpose of this research is to evaluate the
performance of digital forensic tools that integrate artificial intelligence
and data analysis for the detection, tracking, and analysis of cybercrimes
within the Ecuadorian context. The tools selected for this study are Autopsy,
Magnet AXIOM, and Belkasoft Evidence X. The
primary objective is to determine their effectiveness in identifying,
recovering, and presenting digital evidence in real cases, ensuring the results
are admissible in judicial proceedings, in accordance with current Ecuadorian
regulations.
The methodological approach is based on an
experimental design that includes the simulation of representative cybercrime
scenarios, such as phishing attacks, malware, and unauthorized access. These
scenarios were carried out in controlled environments with replicable datasets
to evaluate the tools' performance. The evaluation criteria encompass data
recovery capability, processing efficiency, usability for forensic experts, and
compatibility with the Ecuadorian regulatory framework, ensuring that the
procedures and results meet legal requirements for application in judicial
processes.
Furthermore, questions were created using a Google
Forms questionnaire, which helped identify many aspects of the research during
the use and testing of forensic tools in the field of computer forensics.
2.1. Tool Access and
Licensing
One of the main
methodological challenges was acquiring licenses for the forensic tools with
advanced AI capabilities, specifically Magnet AXIOM and Belkasoft
Evidence X, due to their commercial nature and high cost. To overcome this
barrier, the developers and official distributors of both tools were formally
contacted via email to request temporary evaluation licenses for academic and
research purposes. After a review and verification process of the request, demo
licenses valid for 30 days were obtained for each tool, allowing the controlled
tests to be conducted within a limited timeframe. This process required
rigorous planning of the experimental activities to maximize the use of the
license period.
2.2. Information Collection
Techniques
Data collection included a
comprehensive review of technical manuals, user guides, and case studies on the
use of Autopsy, Magnet AXIOM, and Belkasoft Evidence X in forensic analysis. Reliable sources
were consulted, such as specialized cybersecurity forums, the official websites
of the tools, and reports from forensic laboratories. Additionally, data from
real cybercrime cases in Ecuador were collected, using public reports from the
State Attorney General's Office and other verified sources. This approach allowed
for contrasting theoretical information with the practical needs of experts in
the local context.
2.3. Tools and Services
For the execution of this
research, Autopsy, Magnet AXIOM, and Belkasoft
Evidence X were used as the primary tools. To conduct tests for each one and
compare them, a table is presented below detailing the specifics of each tool.
Table 1. Tool
and Service Characteristics
|
Characteristic |
Autopsy |
Magnet AXIOM |
Belkasoft Evidence X |
|
License |
Open Source |
Proprietary |
Proprietary |
|
AI Integration |
Requires external plugins |
Advanced native integration |
AI functions for classification |
|
Compatibility |
Multiple
OS (Windows, Linux, macOS) |
Windows |
Multiple SO |
|
Interface |
Less intuitive |
Intuitive and robust |
Easy to use |
Note: Data obtained through
experimental testing conducted by the autor Catagua, D. (2025).
Subsequently, each tool was detailed. A forensic image
containing some anomalous files was used to identify them.
The forensic tool Autopsy is an open-source
platform for digital forensic analysis, with artificial intelligence modules
that automate the detection of suspicious files and anomalous patterns. Magnet
AXIOM is a comprehensive tool for digital forensic analysis that
combines the acquisition and analysis of data from mobile devices, computers,
and the cloud, with advanced artificial intelligence capabilities to
efficiently identify and correlate digital evidence. On the other hand, Belkasoft Evidence X is forensic
software specialized in the acquisition, analysis, and review of digital
evidence, with support for multiple data types—including images, videos,
messages, and documents—optimized for complex investigations with a focus on
usability and generating clear reports.
Test environments were
designed to replicate phishing, malware, and unauthorized access scenarios,
evaluating the capability of each tool to detect and analyze digital evidence.
2.4. Surveyed Experts and Academics
A survey was conducted among 20 professionals,
including cybersecurity experts and university professors, selected for their
experience and knowledge in digital forensics and cybersecurity. The
inclusion criteria considered were:
§
Experience
in computer forensics or university teaching in areas related to cybersecurity.
§
Participation
in investigations or expert reports related to cybercrime in Ecuador.
The respondent group consisted of professors from the
Technical University of Manabí, with profiles such as systems engineers, IT
auditors, IT managers, IT engineers, and masters in data
science, as well as experts from the National Police and criminalistics
units. This composition aimed to create a comprehensive overview integrating
technical, legal, and educational perspectives.
It should be noted that while the involvement of
academics benefits the analysis from a formative and theoretical focus, the
sample shows a significant density in this area. Therefore, the findings
derived from the survey should be interpreted considering that the perspective
of professionals working exclusively in digital forensics within the public or
private sector might be underrepresented.
Participation in the survey, conducted via a Google
Form, was optional and collaborative, allowing for the collection of valuable
information about the level of confidence and usage of forensic tools among the
consulted professionals.
2.5. Configuration
and Initial Testing
Data from
simulated and real cases such as phishing emails, logs, compromised files, and
incident reports was collected. This data was processed and normalized during
analysis using tools that integrate artificial intelligence to identify any
anomaly attacks and vulnerabilities.
Tools including
Autopsy, Magnet AXIOM, and Belkasoft Evidence X were
installed and configured to proceed with forensic protocols and ensure evidence
integrity. This process included: creating forensic images, hashing to verify
data, timeline analysis, and automated correlation of indicators of compromise.
In the tool
comparison, results showed that AXIOM was consistently faster in processing
traditional storage; Belkasoft demonstrated clear
advantages in memory analysis, while Autopsy proved viable for limited budgets.
Finally, reports
containing findings were prepared in compliance with forensic standards for
presentation in judicial proceedings. These included complete chain of custody
documentation, technically accurate explanations adapted to legal language,
annexes with certified digital evidence (hashes, metadata), and conclusions
regarding the identified attack origin.
2.6. Data Processing and Analysis
The forensic
analysis was conducted through controlled tests using Magnet AXIOM, Autopsy,
and Belkasoft Evidence X tools. The data was obtained
from the following website: https://digitalcorpora.s3.amazonaws.com/s3_browser.html#corpora/drives/nps-2009-ntfs1/, (DigitalCorpora), where a
forensic image in .E01 format (492 MB, NTFS file system) was used. The executed
technical procedures can therefore be described, supported by key visual
evidence:
Table 2. Configuration and Processing Results of the Forensic
Image
|
Parameter |
Magnet AXIOM |
Autopsy |
Belkasoft Evidence X |
|
Case Configuration |
Unique
identifier: Case-01. Activation of all native AI modules (image
classification, content detection, chat analysis). |
Standard
image load. Required manual search and installation of the deepfake_photo plugin for basic AI capabilities. |
Automated
case setup. Activation of preconfigured visual semantic filters (nudity,
weapons, faces detection). |
|
Processing and Analysis |
Automated analysis with hashing (MD5/SHA-1) for
integrity verification. Execution of keyword searches (e.g.,
"confidential", "hacking"). Use of timeline for event
correlation. |
Sequential modular processing. Metadata analysis
and file recovery using the PhotoRec tool,
requiring manual intervention for classification. |
Automated sequential process. Comprehensive
artifact analysis with a focus on efficient recovery and visual filtering. |
|
Execution Time |
50 seconds (Fastest) |
2 minutes 10 seconds. |
2 minutes 42 seconds. |
|
Recovered Evidence |
46 images automatically classified by content and
case relevance. |
Basic file recovery. Classification depended on
correct user configuration. |
74 graphic items and 6 documents identified, with
a clear visual presentation. |
|
User Intervention |
Minimal. Guided
and automated workflow. |
High. Less
intuitive tree navigation and need for manual plugin configuration. |
Moderate. Interactive dashboard that facilitates results exploration. |
Note: Data obtained through experimental testing conducted
by the autor Catagua, D.
(2025).
2.7.
Detailed Description by Tool:
§ Magnet
AXIOM:
o
A new
case was configured with the identifier Caso-01.
o
The
forensic image ntfs1-gen1.E01 was loaded.
o
All integrated
AI functionalities for automatic image and chat classification, as well as
specific content detection, were activated.
o
A
search was executed using key terms related to the simulated case
("confidential", "hacking").
o
The
tool automatically calculated hashes (MD5/SHA-1) to ensure data integrity
throughout the process.
o
The
total analysis time was 50 seconds, making it the fastest tool.
o
46
images of evidentiary interest were automatically recovered and classified.
§ Autopsy:
o
The
process began with the standard loading of the forensic image.
o
To
emulate AI functionalities, it was necessary to manually search for, download,
and install the external deepfake_photo plugin.
o
The
interface, based on a navigation tree, proved less intuitive and required
greater manual intervention from the investigator.
o
File
recovery was supported by the PhotoRec tool, but the
classification of evidence depended almost entirely on the user's judgment and
effort.
o
The
processing time was 2 minutes and 10 seconds.
o
Preconfigured
visual semantic filters were utilized to detect categories of sensitive content
such as nudity, weapons, and faces.
o
The
analysis was sequential and comprehensive, examining a wide range of digital
artifacts.
o
The
tool presented the results in a visual and interactive dashboard, facilitating
data exploration.
o
The
processing time was 2 minutes and 42 seconds.
o
A
total of 74 graphic items and 6 documents relevant to the investigation were
identified.
2.8. Study Limitations:
o Variability in Real-World Scenarios: The
simulated cases did not replicate the full spectrum of advanced attacks
documented in the literature or reported in recent incidents.
o Tool Updates: The versions used may not include
the most modern artificial intelligence functionalities designed to counter evolving
threats.
o Access to Sensitive Data: Legal and ethical
restrictions prevented the use of evidence from ongoing legal proceedings,
leading to reliance on controlled simulations.
o Survey Sample Composition: The predominance of
academics in the sample of surveyed professionals may introduce a bias in the
results, as their experiences and needs may differ from those of professionals
who work exclusively and operationally in digital forensics within police
institutions, prosecutor's offices, or consulting firms. Future research should
expand the sample to more proportionally include profiles dedicated primarily
to forensic practice, in order to achieve a more
representative overview of the sector in Ecuador.
These limitations are documented to guide and enrich
future research, ideally in collaboration with public authorities that can
facilitate access to realistic data and a broader range of active professionals.
2.9. Ethical Considerations:
This study ensured
the privacy of the obtained data and removed personal information from the real
datasets. Survey participants consented to their responses being used for
scientific purposes. Furthermore, the protocols of the Organic Law on Personal
Data Protection (Ecuador) were respected, and practices that could compromise
external systems or networks during testing were avoided.
3. Results:
The evaluation of
Magnet AXIOM, Autopsy, and Belkasoft Evidence X was
conducted through controlled tests using a standardized forensic image in E01
format (492 MB, NTFS system).
The results are analyzed across two dimensions:
ü The quantifiable technical performance of each tool.
ü The preliminary findings from an exploratory survey on
the perception and usage of these technologies in the local context.
3.1. Comparative Analysis of Technical Performance:
Table 2 (presented
in section 3.6) shows the detailed results of the forensic image processing,
highlighting significant differences in speed, automation, and effectiveness.
The key technical findings are described below:
3.2. Key Technical Findings:
ü Speed and Automation: Magnet AXIOM demonstrated
overwhelming superiority in speed, processing the evidence in 50 seconds. Its
integrated native AI enabled a nearly fully automated workflow, minimizing investigator
intervention.
ü Recovery Effectiveness: Belkasoft
Evidence X excelled in evidence recovery capability, identifying 74 multimedia
items. Its powerful visual semantic filters and intuitive interface facilitated
the location and presentation of findings.
ü Viability for Limited Budgets: Autopsy confirmed
its robustness as an open-source tool. However, its reliance on manual plugin
installation to emulate AI functionalities and its less intuitive interface
resulted in a significantly slower process demanding greater technical
expertise.
To visualize the
significant difference in tool efficiency, Figure 1 compares the
processing times.
Figure 1. Comparison of the forensic image processing time (in
seconds)
3.3. Findings from an Exploratory
Survey of Professionals:
In a complementary
manner, a preliminary survey was conducted with 20 sector professionals
(experts, academics, and IT professionals) aiming to gain an initial
understanding of their familiarity with this type of tool. It is important to
note that, due to the limited sample size, these results should be interpreted
as initial trends and not as generalizations of the national situation.
The results,
summarized in Table 3, reveal valuable insights into the adoption context.
Table 3. Perception and Use of Digital Forensic Tools (n=20)
|
Aspect |
Results (%) |
|
Prior Knowledge |
35% were unfamiliar with them |
|
Perceived Usefulness |
63%
consider them "very useful" |
|
Selection Priority |
72% value “accuracy” over “legality” |
|
Frequency of use |
75%
use them “sometimes” |
Note: Data obtained through experimental testing conducted
by the author Catagua, D. (2025).
These findings
point to a potential disconnect between the technological potential and the
common practice within the surveyed professional circle. The low frequency of
use (75%) contrasts with the high perceived usefulness (63%), which could be
related to factors such as access to licenses, availability of specialized
training, or institutional routines.
Figure 2. It illustrates the perceptions and usage habits
identified through the survey.
Figure 2. Perceptions and patterns of use of AI forensic tools.
3.4. Correlation Between Technical
Evidence and Professional Perception:
Although the
survey data is preliminary, a coherence with the technical results is observed:
AI as
a Key Differentiator: The
high performance of Magnet AXIOM and Belkasoft
Evidence X, driven by integrated AI, aligns with the perception of 63% of
professionals who consider AI "very useful" for forensic processes.
Accuracy
Over Usability: Although
users value intuitive interfaces (Figure 2), the primary selection criterion is
accuracy (72%), reinforcing the importance of the technical robustness
demonstrated by the commercial tools.
The
Niche of Open-Source Tools: The
relevance of Autopsy in academic or budget-constrained environments is
contextualized by the low reported frequency of use, suggesting that cost
barriers may influence the adoption of more advanced tools.
4. Conclusions:
In conclusion, not
all the analyzed forensic tools offer the same performance. Magnet AXIOM stood
out for its speed and accuracy, making it ideal for urgent cases, while Belkasoft Evidence X demonstrated greater effectiveness in
analyzing photos and videos. For its part, Autopsy, although notably slower,
presents itself as an accessible option for teams with limited resources.
Furthermore, the
study revealed a critical problem: many of the surveyed professionals were
unfamiliar with or did not use these tools, reflecting an urgent need for
training in the digital forensics field. While artificial intelligence emerges
as a promising solution, its effective implementation first requires
professionals to acquire the necessary competencies to employ it adequately.
On the other hand,
it is essential for laws to stay updated with technological advancements. In
the case of Ecuador, it is imperative to modernize the legal framework,
particularly the COIP, to address digital crimes such as ransomware and
phishing. Without clear and adapted legislation, cybercriminals will maintain
operational advantages.
Finally, it is
recommended to train more experts in forensic tools and AI, foster alliances
between universities, governments, and businesses to strengthen security, and
additionally, update regulations using countries with greater experience, such
as Mexico, as a reference.
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