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Blockchain for secure e-health data in smart cities

include diverse optimizing approaches. Similarly, in the chosen-plaintext attack (CPA), known ciphertext
case of HFR, the proposed STI-TSA-based optimization attack (KCA), and known-plaintext attack (KPA) with
obtained a high value of 0.95 when the data were 30%. respect to key breaking time. CCA is an attack model
In contrast, lower HFR values were achieved when data for cryptanalysis where the cryptanalyst can gather
were at 10% and 20%. However, for all data variations, information by obtaining the decryptions of chosen
the proposed STI-TSA-based optimization attained high ciphertexts. CPA is an attack model for cryptanalysis
HFR over STO, TSA, PFO, SBOA, BA, EHO-OBL, that presumes that the attacker can obtain the cipher
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and BFL-PSO. 35 texts for arbitrary plaintexts. The goal of the attack
As required, the MD is low for the proposed STI- is to gain information that reduces the security of
TSA-based optimization over STO, TSA, PFO, SBOA, the encryption scheme. KPA is an attack model for
BA, EHO-OBL, and BFL-PSO. A significantly low cryptanalysis where the attacker has access to both
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MD value (approximately 0.3) was obtained when data the plaintext (called a crib) and its encrypted version
were at 30%, whereas extant optimization approaches (cipher text). KCA is an attack model for cryptanalysis
obtained high MD values. Thus, with its balanced where the attacker is assumed to have access only to a
approach, STI-TSA delivers superior performance. set of ciphertexts.
A message tampering attack (MTA) entails
8.3. Ablation study the harmful alteration of information, whereas an
Table 6 presents the ablation study for validating the eavesdropping attack (EDA) refers to the unauthorized
enhancement of the proposed STI-TSA with improved real-time interception of private communication
ARM, compared to both the version without ARM and through modern hacking technologies. Attack analysis
the version with traditional ARM. After modifying the reflects the level of protection against these threats –
existing ARM, we achieved better performance using lower values indicate that the attacker takes more time
the improved ARM. In Table 6, the proposed STI-TSA to decrypt the sanitized data. For all data variations, the
with improved ARM shows a high IPR of 0.958626, proposed STI-TSA with improved ARM has attained
whereas the versions without ARM and with traditional lower values over extant STO, TSA, PFO, SBOA,
ARM show lower IPR. The improved ARM could mine BA, EHO-OBL, and BFL-PSO. This shows that the
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the rules quicker with large datasets and create more hacker needs more time to decrypt the sanitized data.
meaningful and precise rules. The improved ARM could Table 7 presents the results of CCA, where the
identify complicated and subtle associations in the data proposed STI-TSA with improved ARM attained
and manage data variations over time. This is evident a lower value of 0.227 at 30% data, compared to
from the HFR, where the proposed STI-TSA with the relatively higher values for STO, TSA, PFO, SBOA,
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improved ARM reaches a value of 0.8645, compared to BA, EHO-OBL, and BFL-PSO, which are 0.294249,
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0.792064 and 0.813284 for the versions without ARM 0.286082, 0.292351, 0.290481, 0.292558, 0.323516,
and with traditional ARM, respectively. The MD metric and 0.304436, respectively. Moreover, the 30% data
using the proposed STI-TSA with improved ARM is shows lower attack values compared to data variations
lower (around 0.317), whereas the versions without ARM of 10% and 20%. For KCA, the proposed STI-TSA with
and with traditional ARM exhibit higher MD values. improved ARM achieved a value of 0.218, while for
KPA, it obtained a value of 0.171256. In regards to CPA,
8.4. Attack analysis the proposed STI-TSA with improved ARM attains a
Table 7 presents an analysis of various attack low value of 0.21335. Moreover, for MTA and EDA,
types, namely, chosen ciphertext attack (CCA), the proposed STI-TSA with improved ARM achieved

Table 6. Ablation analysis using Siberian Tiger Integrated Tuna Swarm algorithm with improved
association rule mining over conventional works
Metrics Proposed without Proposed with Siberian Tiger Integrated Tuna
association rule conventional association Swarm algorithm with improved
mining rule mining association rule mining
Information preservation ratio 0.912531 0.928175 0.958626
Hiding failure rate 0.792064 0.813284 0.86452
Modification degree 0.427843 0.410396 0.317007

Volume 22 Issue 1 (2025) 161 doi: 10.36922/AJWEP025040017