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Buzzword buster

    1. APT (Advanced Persistent Threat): A prolonged and targeted cyber attack in which an intruder gains access to a network and remains undetected for an extended period.
    2. Blockchain Security: Security measures and protocols applied to blockchain technologies to protect data integrity and prevent unauthorized access or modifications.
    3. BOTNET: Robot Network collection of compromised machines, IOT devices that can be controlled centrally by command and control servers. Often used by criminals to sell Malware As A Service like Denial of service as a service.
    4. Data Breach: An incident where information is stolen or taken from a system without the knowledge or authorization of the system's owner. It can involve sensitive, protected, or confidential data being copied, transmitted, viewed, or used by an unauthorized individual.
    5. DDoS (Distributed Denial of Service): An attack where multiple compromised systems, often infected with a Trojan, are used to target a single system causing a denial of service for users of the targeted system.
    6. Encryption: The process of converting information or data into a code, especially to prevent unauthorized access.
    7. Endpoint Protection: Security solutions that protect endpoints or entry points of end-user devices such as desktops, laptops, and mobile devices from being exploited by malicious actors.
    8. Exploit: A piece of software, a chunk of data, or a sequence of commands that takes advantage of a bug or vulnerability to cause unintended or unanticipated behavior to occur on computer software, hardware, or something electronic (usually computer-related).
    9. IAM (Identity and Access Management): A framework of policies and technologies for ensuring that the right individuals have the appropriate access to technology resources.
    10. IoT (Internet of Things) Security: Practices and technologies used to secure devices and networks connected to the Internet of Things, ensuring the confidentiality, integrity, and availability of data.
    11. Machine Learning in Cybersecurity: The application of machine learning algorithms to detect and respond to threats by analyzing patterns and learning from data to make predictions or decisions without being explicitly programmed.
    12. Malware: Malicious software designed to cause damage to a computer, server, client, or computer network. It includes viruses, worms, trojans, ransomware, spyware, adware, and more.
    13. Pen Testing (Penetration Testing): A simulated cyber attack against your computer system to check for exploitable vulnerabilities. It's often referred to as ethical hacking.
    14. Phishing: A technique used by cybercriminals to deceive individuals into providing sensitive information, such as passwords or credit card numbers, often through emails that appear to be from legitimate sources.
    15. Red Team/Blue Team Exercises: A cybersecurity training exercise where one group of security professionals (Red Team) attacks an organization's security defenses, and another group (Blue Team) defends against the attack.
    16. Ransomware: Malicious software that encrypts a victim's data and demands payment, usually in cryptocurrency, to restore access to the data.
    17. SOC (Security Operations Center): A centralized unit that deals with security issues on an organizational and technical level. It continuously monitors and improves an organization's security posture while preventing, detecting, analyzing, and responding to cybersecurity incidents.
    18. SOC 2 Compliance: A set of criteria developed by the American Institute of CPAs (AICPA) for managing customer data based on five "trust service principles"—security, availability, processing integrity, confidentiality, and privacy.
    19. SIEM (Security Information and Event Management): A solution that provides real-time analysis of security alerts generated by applications and network hardware. SIEMs combine SIM (security information management) and SEM (security event management) functions.
    20. Threat Intelligence: Information about current or potential attacks against an organization. This data is used to prepare, prevent, and identify cyber threats looking to take advantage of valuable resources.
    21. Zero Trust: A security framework that assumes no one, inside or outside the organization, can be trusted by default. It requires verification for anyone attempting to access resources.