Authors :
Abhishek Gunje; Shweta Pataskar; Pranali Rane; P.P.Vaidya
Volume/Issue :
Volume 9 - 2024, Issue 4 - April
Google Scholar :
https://tinyurl.com/bdzn6feu
Scribd :
https://tinyurl.com/3shzcjrm
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24APR007
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
This research project presents a
comprehensive strategy aimed at mitigating the
pervasive threat of human trafficking through the
innovative application of machine learning
methodologies. The primary objective revolves
around the development and deployment of
sophisticated algorithms to identify and intercept
human trafficking- related communications.
Leveraging the power of Support Vector Machine
(SVM) classification, the system meticulously
scrutinizes textual data streams, flagging messages
indicative of trafficking activities for further
investigation. Moreover, our approach extends
beyond mere message analysis by incorporating
cutting-edge Utilize Convolutional Neural Network
(CNN) models for performing facial recognition,
age estimation, and gender identification. By
harnessing the rich visual information embedded in
images and videos, the system enhances its
capability to identify potential victims and
perpetrators with unprecedented accuracy and
efficiency. A pivotal component of our solution is the
seamless integration of an alert mechanism
facilitated by a Simple Mail Transfer Protocol
(SMTP) server. This critical feature ensures that
pertinent authorities are promptly notified upon
the detection of suspicious activities, enabling swift
and decisive intervention. Through this amalgamation
of advanced technological frameworks, our research
endeavors to empower law enforcement agencies and
humanitarian organizations in their tireless efforts to
combat the heinous crime of human trafficking. In
essence, this research represents a significant
stride towards the realization of a technologically
fortified defense against the exploitation of
vulnerable individuals. By amalgamating state-of-the-
art machine learning techniques with real-time
alert systems, we aspire to create a formidable
deterrent against the perpetrators of this egregious
crime, thereby Ensuring the protection of human
dignity and advocating for social justice.
Keywords :
SVM, Convolutional Neural Network, SMTP, Classification
This research project presents a
comprehensive strategy aimed at mitigating the
pervasive threat of human trafficking through the
innovative application of machine learning
methodologies. The primary objective revolves
around the development and deployment of
sophisticated algorithms to identify and intercept
human trafficking- related communications.
Leveraging the power of Support Vector Machine
(SVM) classification, the system meticulously
scrutinizes textual data streams, flagging messages
indicative of trafficking activities for further
investigation. Moreover, our approach extends
beyond mere message analysis by incorporating
cutting-edge Utilize Convolutional Neural Network
(CNN) models for performing facial recognition,
age estimation, and gender identification. By
harnessing the rich visual information embedded in
images and videos, the system enhances its
capability to identify potential victims and
perpetrators with unprecedented accuracy and
efficiency. A pivotal component of our solution is the
seamless integration of an alert mechanism
facilitated by a Simple Mail Transfer Protocol
(SMTP) server. This critical feature ensures that
pertinent authorities are promptly notified upon
the detection of suspicious activities, enabling swift
and decisive intervention. Through this amalgamation
of advanced technological frameworks, our research
endeavors to empower law enforcement agencies and
humanitarian organizations in their tireless efforts to
combat the heinous crime of human trafficking. In
essence, this research represents a significant
stride towards the realization of a technologically
fortified defense against the exploitation of
vulnerable individuals. By amalgamating state-of-the-
art machine learning techniques with real-time
alert systems, we aspire to create a formidable
deterrent against the perpetrators of this egregious
crime, thereby Ensuring the protection of human
dignity and advocating for social justice.
Keywords :
SVM, Convolutional Neural Network, SMTP, Classification
