Authors :
Roche M.P; Amarasinghe M. A. W. D; Mahawatta A.I; Vishan Jayasinghearachchci; Jayasinghe L.V.S
Volume/Issue :
Volume 7 - 2022, Issue 10 - October
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3TS1o6B
DOI :
https://doi.org/10.5281/zenodo.7332566
Abstract :
Exploit of one’s identity is a major threat the
world faces, especially in Sri Lanka, where countless fake
documents are forged which is very identical to the
legitimate documents issued by the government authorities
to recognize every individual. Per literature, the existing
system is such that the documents are stored within a
database hosted by the government, but there is no direct
way of comparing every document presented by the person
to validate the legitimacy of the documents, which gives the
requirement for blockchain such that every issued
document can be hashed and stored, allowing to spot fake
or unauthorized documents by rehashing and checking
against the existing hash stored in the blockchain, as
foreign blockchain solutions are not economically feasible
in Sri Lanka, a blockchain needs to be developed locally
with multi-threaded asynchronous support for faster
transaction processing, and non-blocking communication
between blockchain nodes. In Sri Lanka, automated
criminal detection is not much popular and authorities'
procedures for identifying offenders are time-consuming.
Using an automated approach to identify a wanted
individual might be preferable to present practices.
Current processes and techniques, such as acquiring
records from eyewitnesses, are untrustworthy. Analyzing
people's faces, behaviors, and threatening voices in CCTV
camera footage is time-consuming. The proposed system
can be able to register civilians, detect unusual behaviors,
such as fights and criminals waving dangerous weapons in
public, criminal face identification, which has the power of
recognizing criminal faces at various stages of age, and
recognition of the situation depending on the voice tracks
extracted by CCTV footage. It summarizes whether the
situation is threatening or not. In this research, we have
proposed a desktop application for criminal identification
with a higher accuracy level
Keywords :
Hash, Blockchain, Unusual Behavior, Face Recognition, Criminal Identification.
Exploit of one’s identity is a major threat the
world faces, especially in Sri Lanka, where countless fake
documents are forged which is very identical to the
legitimate documents issued by the government authorities
to recognize every individual. Per literature, the existing
system is such that the documents are stored within a
database hosted by the government, but there is no direct
way of comparing every document presented by the person
to validate the legitimacy of the documents, which gives the
requirement for blockchain such that every issued
document can be hashed and stored, allowing to spot fake
or unauthorized documents by rehashing and checking
against the existing hash stored in the blockchain, as
foreign blockchain solutions are not economically feasible
in Sri Lanka, a blockchain needs to be developed locally
with multi-threaded asynchronous support for faster
transaction processing, and non-blocking communication
between blockchain nodes. In Sri Lanka, automated
criminal detection is not much popular and authorities'
procedures for identifying offenders are time-consuming.
Using an automated approach to identify a wanted
individual might be preferable to present practices.
Current processes and techniques, such as acquiring
records from eyewitnesses, are untrustworthy. Analyzing
people's faces, behaviors, and threatening voices in CCTV
camera footage is time-consuming. The proposed system
can be able to register civilians, detect unusual behaviors,
such as fights and criminals waving dangerous weapons in
public, criminal face identification, which has the power of
recognizing criminal faces at various stages of age, and
recognition of the situation depending on the voice tracks
extracted by CCTV footage. It summarizes whether the
situation is threatening or not. In this research, we have
proposed a desktop application for criminal identification
with a higher accuracy level
Keywords :
Hash, Blockchain, Unusual Behavior, Face Recognition, Criminal Identification.
