Cybersecurity has become one of the most critical concerns for organizations as digital transformation, cloud computing, remote work, and internet-based business operations continue to expand globally. Despite significant investments in advanced security technologies, human error remains one of the leading causes of cybersecurity incidents, making employee awareness and compliance with organizational security policies essential for protecting information assets. Cybersecurity awareness refers to the knowledge and understanding employees possess regarding cyber threats, safe online practices, organizational security policies, and responsible digital behavior. Employee compliance behavior involves the extent to which employees follow established cybersecurity guidelines such as creating strong passwords, enabling multi-factor authentication, identifying phishing emails, handling sensitive information securely, updating software regularly, and reporting suspicious activities promptly. Organizations increasingly implement cybersecurity awareness training, simulated phishing exercises, security awareness campaigns, and policy enforcement programs to reduce cyber risks and strengthen organizational resilience. The primary objective of this study is to examine the relationship between cybersecurity awareness and employee compliance behavior by evaluating how awareness programs influence employees adherence to cybersecurity policies and best practices. The research also investigates the effectiveness of cybersecurity training, password management practices, phishing awareness, and organizational security culture in improving compliance behavior. A descriptive research design was adopted for the study. Primary information was obtained through structured responses collected from employees, while secondary information was gathered from peer-reviewed journals, books, industry reports, government publications, and authentic cybersecurity databases. Percentage analysis and graphical techniques were employed to analyze and interpret the collected information. The findings indicate that higher cybersecurity awareness significantly improves employee compliance with organizational security policies, reduces risky online behavior, enhances phishing detection capabilities, and minimizes the likelihood of cyber incidents. However, challenges such as insufficient training, employee negligence, lack of continuous awareness programs, and evolving cyber threats continue to affect organizational cybersecurity. The study concludes that continuous cybersecurity education, regular policy updates, practical security training, and a strong security culture are essential for improving employee compliance behavior and strengthening organizational cybersecurity resilience. Keywords: Cybersecurity Awareness, Employee Compliance, Information Security, Cyber Threats, Phishing, Password Security, Multi-Factor Authentication.
Gade Venumadhav, A. Shaik, Pavani Mudem· International Journal of AI...· 0 citations
This study, titled "Algorithmic Trading and Its Effect on Market Efficiency," evaluates algorithmic strategy shares, order execution slippage, exchange liquidity compression, and financial feasibility of automated execution systems in modern securities markets. Financial exchanges experience rapid electronification, where high-frequency trading (HFT) and statistical arbitrage account for 70% of total order flow. A five-year project lifecycle (2021- 2025) of an institutional algorithmic trading platform is evaluated using capital budgeting parameters: Net Present Value (NPV), Internal Rate of Return (IRR), Payback Period (PBP), and Benefit-Cost Ratio (BCR). Quantitative analysis indicates that statistical arbitrage represents 40% and HFT market making accounts for 30% of algorithmic trading volume. Deploying AI algorithmic co-location reduces order execution slippage to 1.1 basis points (bps) compared to 24.5 bps under manual floor trading. Higher execution speed drives daily exchange trading volume to 185,000 Crores while compressing average bid-ask spreads to 1.2 bps, raising algorithmic market share to 84.5% and driving the market variance ratio to 1.01 (indicating strong random-walk efficiency) by 2025. The financial model yields a positive NPV of 284.5 Crores and an IRR of 38.6%, far exceeding the 10% discount hurdle rate. The study concludes that investing in algorithmic trading platforms is highly viable, enhancing price discovery, market liquidity, and trading cost efficiency.
Suru Prem Sai, Pavani Mudem, T. Meghana· American Journal of AI Cyber...· 0 citations
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