The current era extensively utilizes the Internet, which uses data. Due to the apparent open-access Internet service, this data is highly vulnerable to attacks. Data privacy is affected by Web-based attacks. This Systematic Literature Review (SLR) focuses on two Web-based attacks: Man-In-The-Middle and session hijacking. It reviews about 30 studies from the years 2016–2023 that have been selected utilizing a proper study selection procedure. This SLR comprises three research questions. The first describes the overall trends in Man-In-The-Middle attacks and session hijacking studies. It shows that 7 articles were published in 2018, and the trend is decreasing to 4 articles by 2021. Moreover, 73% articles are published in conference venues, and India is the top contributor in this domain. Lastly, this question elaborated that IEEE is the top contributor as a publisher. The second addresses the sorts of attacks used by Man-In-The-Middle attacks and session hijacking on Transmission Control Protocol / Internet Protocol (TCP/IP). This demonstrates that Man-In-The-Middle attacks invade all layers and session hijacking attacks on only two, that is, the application and network layer. The third research question discusses the solutions provided by different studies to deal with Man-In-The-Middle attacks and session hijacking. In conclusion, this analysis highlights the need for stronger cybersecurity measures against Man-in-the-Middle and session hijacking assaults in the Internet era by revealing evolving trends, contributors, and solutions in data privacy.

Sharpless asymmetric dihydroxylation is an important reaction in the enantioselective synthesis of chiral vicinal diols that involves the treatment of alkene with osmium tetroxide along with optically active quinine ligand. Sharpless introduced this methodology after considering the importance of enantioselectivity in the total synthesis of medicinally important compounds. Vicinal diols, produced as a result of this reaction, act as intermediates in the synthesis of different naturally occurring compounds. Hence, Sharpless asymmetric dihydroxylation plays an important role in synthetic organic chemistry due to its undeniable contribution to the synthesis of biologically active organic compounds. This review emphasizes the significance of Sharpless asymmetric dihydroxylation in the total synthesis of various natural products, published since 2020.

Today the Web has become an essential part of people’s life. Everyone has the right to access websites, including seniors and disabled people. Government websites contain public information for the whole society, but affect mostly disabled people. In this paper, we have analyzed the accessibility and usability issues of selected top 60 government websites of Pakistan and China. We analyzed all websites’ loading time, page size, mobile friendliness, broken links, HTML5 and ARIA, Web Content Accessibility Guidelines (WCAG) 2.0 (Level A, Level AA, Level AAA) conformance, and contrast errors through online accessible testing tools and human inspections. We designed an interactive evaluation framework for Web accessibility and usability, which is used to evaluate both countries’ government websites. According to the evaluation 22 out of 30 Chinese government websites have less than about 50% of the accessibility issues, while Pakistan in contrast only 12 out of 30 government websites have less than about 50% of accessibility issues. The Chinese government websites are much better than Pakistani government websites with respect to accessibility and usability features. The all-inclusive results indicate that Pakistan government websites have poor conformance levels to meet WCAG standards. We gave some valuable recommendations, which will be helpful for web designers, developers and also web users particularly disabled people performance in the newest Artificial Intelligence (AI) area in a decent way.

It is increasingly difficult to manage the user identities (IDs) of rapidly developing and numerous types of online web-based applications in the present era. An innovative ID management system is required for managing the user IDs. The OpenID lightweight protocol is a better solution to manage the user IDs. In an OpenID communication environment, OpenID URL is not secured in a session hijacking situation because in other existing OpenID communication methods such double factor authentication has more chances of valid user session hijacked. The proposed communication protocol secures the OpenID URL with the help of additional innovative parameters such as Special Alphanumeric String (SAS) and Special Security PIN (SSP). The anticipated triple authentication protocol authenticated client unique OpenID URL at OpenID Provider (OP) side once and SAS and SSP field at Relying Party (RP) side. The anticipated protocol provides unique Single-Sign-On (SSO) services to OpenID users. The experimental website is tested by experts of web developers for avoiding session hijacking situation in the presence of hackers. The findings demonstrated that Dense Authentication Authorization and Accounting (DAAA) protocol minimizes the risk of a session hijacking in OpenID communication environment.

With the rapid proliferation of user-generated content across internet-based platforms, sentiment analysis has become an essential tool for understanding public opinion. However, sentiment analysis on code-mixed, low-resource languages presents significant challenges due to limited annotated data, linguistic complexity, and resource constraints. This systematic literature review (SLR) comprehensively examines recent developments in sentiment analysis for code-mixed and low-resource languages, with a focus on studies published between 2017 and 2025. The review investigates a wide range of approaches, including deep learning models, transfer learning strategies, and pre-trained language models, evaluating their effectiveness in low-resource and code-mixed contexts. Findings indicate that transfer learning and transformer-based architectures are increasingly preferred due to their superior performance and reduced reliance on large annotated datasets. Social media is identified as the dominant data source, followed by reviews from e-commerce and entertainment domains. Despite these advancements, significant challenges persist, including the scarcity of high-quality labeled data, high computational costs, and limited generalization across languages and domains. This review not only synthesizes current methodologies and applications but also proposes a conceptual framework for future research. It offers actionable insights for scholars seeking to develop efficient, scalable sentiment analysis systems tailored to code-mixed and low-resource language scenarios.