Al-Mustansiriyah Journal of Science

Background: Phishing is a common cybercrime attack, and
it is also considered a social crime that has been going on for more than two
decades. Phishing aims to trick users into revealing their private information,
including banking information, passwords, and account credentials. Phishing
remains a real threat and usually occurs via instant messages, email, or phone
calls. Objective: Used shape analysis on the system to uncover the most important
features that contribute to phishing detection. A set of key features was
identified. Many phishing detection methods have been used recently, but they
do not provide a complete understanding of the impact of different features on
predictions. Methods: Several machine learning strategies based on SHAP
(Shappley Additive Explanations) were applied, which enhanced the classification
model. This paper proposes a fast model based on a set of contemporary
machine learning techniques. Results: Experiments showed that the proposed
model achieved a maximum accuracy of 99.1% for K-NN and 98.5% for XGBoost
on the Phishing_Legitimate_full dataset. K-NN has demonstrated superior
performance and interpretability, which is critical for security-critical
applications. Conclusions: The results highlight the balance between predictive
performance and interpretability. This provides valuable transparency
into the decision-making process. This makes it a more practical choice for
real-world phishing detection systems, where reliability and interpretability are
critical.

Background: This study investigates the existence and
uniqueness of solutions for a class of nonlinear fractional differential systems
governed by Caputo derivatives. Such systems are effective in modeling
dynamic processes with hereditary behaviors and anomalous responses, which
are commonly observed in socio-economic, biological, and engineering contexts.
Traditional integer-order differential models fail to capture these features, motivating
the use of fractional-order formulations. Objective: The primary goal
is to establish rigorous mathematical conditions ensuring the well-posedness of
nonlinear fractional systems involving coupled variables. By proving existence
and uniqueness, the study provides a solid theoretical foundation for analysis,
simulation, and application of fractional-order models to complex systems with
hereditary dynamics. Methods: The fractional differential system is transformed
into an equivalent integral formulation using Riemann–Liouville fractional
integral operators. Within a Banach space, two operators are defined:
one is continuous and compact, while the other is contractive. The existence of
solutions is established via Krasnoselskii’s fixed point theorem, and the boundedness
and Lipschitz continuity of the nonlinear terms ensure uniqueness through
Banach’s contraction principle. The system admits a unique solution confined
to a closed, invariant subset of the function space, providing a rigorous framework
for analytical and numerical investigations. Results: Analytical results
confirm that the proposed fractional-order system satisfies conditions for existence
and uniqueness of solutions. The integral representation demonstrates
the well-posedness of the model and validates its ability to capture hereditary
dynamics accurately. Operator-based analysis ensures stability and supports
convergence of numerical methods, making the model practically applicable for
simulations of socio-economic and biological processes. Conclusions: This
work establishes a rigorous theoretical foundation for nonlinear fractional differential
systems with Caputo derivatives. By addressing existence, uniqueness,
and stability, it provides a reliable framework for modeling systems where past
states influence current behavior. The findings facilitate both analytical and
numerical studies of fractional-order dynamics, expanding the applicability of
fractional calculus in diverse fields, including economics, population dynamics,
control theory, and material science.

Background: The regular use of connected devices on the
internet by users of social media generates a large quantity of multimedia data
every second, and the data concerned may be of a variable nature, such as text
data, color images, video, and audio. We can confirm that online security is
becoming an area that is increasingly being explored by researchers around the
world to guarantee and ensure the authenticity and confidentiality of exchanged
data. Objective: The goal of this article is to introduce a new dynamic cryptosystem
for encrypting color images, using elliptic curves and chaotic functions.
Methods: This new system serves to generate the coefficients of the
curve, create the encryption keys, and create the prime number of the curve.
The new system utilizes the length of the encryption keys, which encompasses
all points on the curve and relates to the discrete logarithm problem of elliptic
curves, thereby justifying the difficulty in uncovering hidden information.
Results: The results were obtained with the assistance of several analyses, including
histogram analysis, correlation coefficient analysis, differential attack
analysis, and key space analysis. The results obtained confirm the robustness
and reliability of the proposed cryptographic system. Conclusions: By combining
the two systems (elliptic curves and chaotic functions), we obtain a new
hybrid system capable of operating with reduced encryption key lengths and
random values, which makes our new system sensitive to initial conditions

Background: Titanium dioxide nanoparticles (TiO2 NPs)
have widespread use in industrial and biological fields owing to their distinctive
physicochemical characteristics. Nonetheless, their growing prevalence raises
concerns over their possible toxicological impacts, especially on the functionality
of essential organs. Objective: The present work examines the subacute toxicity
of TiO2 nanoparticles on hepatic and renal function and modifications in the
lipid profile in a mouse model. Methods: Forty-eight adult female albino mice
were divided randomly into three groups (n=16 each). Two groups were treated
intraperitoneally with TiO2 NPs at 100 mg/kg and 400 mg/kg, respectively,
while the control group was treated with distilled water. The animals were
sacrificed after 7 and 21 days of treatment. Serum levels of urea, creatinine,
aspartate aminotransferase (AST), alanine aminotransferase (ALT), and lipid
profile parameters (cholesterol, HDL, LDL) were estimated. Results: Both
treated groups showed significant rises in urea, creatinine, AST, and ALT
levels (p<0.0001) compared to the control. These were more pronounced at
higher concentrations and longer exposure durations. Cholesterol level fell
after 21 days, with significant drops in HDL and rises in LDL (p<0.0001).
Conclusions: TiO2 NPs induce dose- and time-related alteration of liver and
kidney function, and lipid metabolism in mice. These findings highlight that
further toxicological research on nanoparticle exposure in environmental and
biomedical applications is needed.

Background: Alzheimer’s disease (AD) shows distinct differences
between women and men in prevalence, disease progression, and therapeutic
response. Women express a greater risk of AD onset, influenced by
increased longevity and hormonal factors, and typically experience faster cognitive
decline along with heightened susceptibility to AD-associated depression
and anxiety. Current therapies—primarily cholinesterase inhibitors and
memantine—offer only symptomatic relief without modifying disease progression.
Objective: To review sex-specific differences in Alzheimer’s disease
and evaluate the current understanding of therapeutic response variations between
men and women, with an emphasis on identifying opportunities for sextailored
interventions. Methods: A narrative review of the literature on AD
prevalence, progression, and treatment outcomes across sexes was conducted.
Particular attention was given to pharmacological therapies (cholinesterase inhibitors,
memantine), lifestyle factors, and sex-specific risk determinants such
as cardiovascular health and hormonal fluctuations. Results: Evidence suggests
that women are more vulnerable to AD onset and progression compared to
men. Limited studies indicate potential therapeutic advantages of specific medications
for women, though robust, sex-stratified clinical trials remain lacking.
Non-pharmacological strategies, including lifestyle adjustments in diet, exercise,
and cognitive engagement, show promise in alleviating symptoms for both
sexes. Conclusions: Sex differences significantly influence AD onset, clinical
course, and therapeutic response. While current treatment remains largely
non-disease-modifying, emerging sex-specific findings underscore the need for
personalised medicine approaches. Further research is required to clarify sexspecific
mechanisms, optimise therapeutic strategies, and address disparities in
care access, ultimately improving management of AD in both women and men.