Week 1 CYBR 325

 

This week was my first refresher and introduction to real-world applications of artificial intelligence and machine learning in cybersecurity. Before researching the topic, I mainly thought AI was used to automate tasks. While working and researching on the career path assignment I learned that its uses are much broader and can help cybersecurity professionals detect threats, analyze data, and respond to attacks.

One application I found interesting was Assala Energy’s use of an AI-powered SOC assistant. The system helps analysts review and prioritize security alerts by identifying suspicious activity and escalating important events. This can reduce alert fatigue and allow analysts to focus on more serious threats.

I was also interested in Visa’s use of AI and machine learning to detect financial fraud. The system analyzes transactions in real time using factors such as spending patterns, locations, devices, and previous fraud trends. This allows Visa to analyze huge amounts of data much faster than humans could.

Another example was Google’s use of AI to detect phishing and scams across products such as Search, Chrome, and Android. Instead of only identifying known malicious websites, AI can analyze webpage content and behavior to recognize patterns associated with scams. This showed me how AI can help identify new and emerging threats.

I also learned that AI has limitations. It can make mistakes, depend on the quality of its data, and sometimes miss real attacks or flag legitimate activity. Attackers can also use AI to create more convincing scams and attacks. Because of this, cybersecurity professionals need to understand both how AI can defend against threats and how attackers can use it against them.

Comments

Post a Comment

Popular posts from this blog

Week 7: Data Privacy

Image
    What Is Data Privacy? 1. Defining Privacy & Data Privacy Privacy is the fundamental right to keep your personal life and information to yourself. Data privacy specifically focuses on protecting your digital personal data—like your name, birthdate, online activity, medical info, and financial details—from unwanted access or sharing 2. Why It Matters in the Digital Age Vast volumes of data are generated whenever you go online—your web behavior, purchases, and even the time spent on a page. Companies analyze this data to personalize ads, predict behavior, and make decisions—but it also means your every action becomes part of a digital footprint   3. Data Privacy vs. Cybersecurity Cybersecurity is about protecting data from unauthorized intrusions, like hacks or malware. Data privacy is about your rights and choices—deciding who gets access to your information and what they can do with it .  Data privacy is all about making informed choices and ...
Read more

Week 3- Attackers Impersonate as Managed Devices

 A report was created that a high-severity vulnerability has been found in Cisco's Nexus Dashboard Fabric Controller which allows unauthenticated attackers to impersonate managed network devices through SSH connections that are compromised. Security researchers from REQON B.V. identified the flaw, which comes from insufficient SSH host key validation mechanisms within the NDFC infrastructure. The affected system fails to properly validate SSH host keys during connection, that allows malicious actors to conduct machine-in-the-middle attacks giving themselves the chance to position themselves between the NDFC controller and managed devices, potentially intercepting and manipulating network management traffic. Attackers that successfully exploit this vulnerability could create persistent backdoors within the managed network environment. Cisco has released software updates to address this vulnerability, with no available workarounds for affected systems. The fix implements enhances the...
Read more

Week 9: Vulnerability Management

Image
   Vulnerability management is a continuous process that identifies, evaluates, treats, and reports security vulnerabilities across systems and software. It helps reduce the attack surface and ensure compliance. The process includes asset discovery, vulnerability scanning, risk prioritization, remediation, and verification. Automation and risk-based tools enhance its efficiency, making it essential for modern cybersecurity strategies. Key Stages (Lifecycle) Asset Discovery Identify and catalog all IT assets—servers, endpoints, apps, networks—which forms the foundation for vulnerability scanning. Vulnerability Scanning Use automated tools to detect known flaws such as misconfigurations, open ports, and out-of-date software across the infrastructure . Prioritization & Risk Rating Assign risk levels (e.g., CVSS scores, severity ratings) based on likelihood, business impact, exploitability, and compliance requirements .. Remediation & Mitigation Apply patches,...
Read more