Information Policy News

Cyber Law and Cybercrimes

2 mins 4 mths

The User Datagram Protocol (UDP) is a lightweight communication protocol widely used in networking for its speed and simplicity. 

Unlike TCP, UDP is connectionless, meaning it transmits data without establishing a formal connection, making it highly efficient for applications requiring low-latency communication. However, its lack of built-in error recovery and acknowledgment mechanisms introduces risks in sensitive environments, necessitating effective risk management strategies. In risk […]

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5 mins 4 mths

Identity Security Ecosystem in Cyber Risk Management

In today’s digital era, organizations face an ever-evolving landscape of cyber threats. With data breaches, ransomware, and insider threats becoming more sophisticated, securing the identity of users, systems, and devices has emerged as a cornerstone of effective cyber risk management. The identity security ecosystem provides […]

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2 mins 4 mths

Cyber Threat Intelligence (CTI) is the process of collecting, analyzing, and disseminating information about potential or existing threats to an organization’s cybersecurity. 

It helps organizations understand, anticipate, and mitigate risks associated with cyberattacks. CTI provides actionable insights into the tactics, techniques, and procedures (TTPs) of cyber adversaries, enabling organizations to strengthen their defenses proactively. The core of CTI lies in data collection and analysis. This data is […]

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4 mins 9 mths

Privileged Access Management (PAM) is a critical component in the overarching strategy of cyber risk management.

In today’s digital landscape, where cyber threats are increasingly sophisticated and frequent, the security of sensitive information and critical systems hinges significantly on how well privileged access is managed. Here’s why PAM is indispensable in mitigating cyber risks: Understanding Privileged Access Management Privileged access refers […]

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3 mins 9 mths

Risk-based authentication (RBA) and multi-factor authentication (MFA) are two advanced security measures used to enhance the protection of user accounts and sensitive data, each with distinct mechanisms and benefits.

Risk-Based Authentication (RBA): RBA dynamically adjusts the level of authentication required based on the risk profile of a particular login attempt. It evaluates various factors such as the user’s IP address, geolocation, device type, and login behavior patterns. If a login attempt is deemed suspicious—such […]

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3 mins 9 mths

Metadata, often described as “data about data,” plays a crucial role in data risk management by providing essential information that enhances the understanding, usability, and protection of data.

Effective data risk management relies on a comprehensive grasp of the data landscape, and metadata is central to this process. First, metadata enhances data governance by enabling organizations to catalog their data assets. This cataloging helps in identifying the origin, lineage, and transformation of data. […]

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3 mins 9 mths

Cybersecurity risk assessment is a critical process that helps organizations identify, evaluate, and mitigate the risks associated with their digital assets.

It involves a systematic approach to understanding the potential threats to information systems and the vulnerabilities that could be exploited by those threats. The first step in a cybersecurity risk assessment is to identify all valuable assets within the organization. This includes hardware, software, data, […]

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2 mins 9 mths

Simulations in anti-money laundering (AML) are a critical tool for financial institutions and regulatory bodies to combat financial crime effectively.

These simulations replicate various money laundering scenarios, enabling organizations to understand how illicit activities might be conducted and identify weaknesses in their existing AML controls. One of the primary benefits of simulations is the ability to test and improve detection systems. By simulating money laundering […]

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3 mins 9 mths

AI risk management and governance are critical for ensuring the safe and ethical deployment of artificial intelligence technologies.

As AI systems become more integrated into various aspects of society, they pose potential risks that need to be managed through comprehensive governance frameworks. Risk management involves identifying, assessing, and mitigating risks associated with AI. This includes technical risks such as system failures, biases, and […]

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