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Threat Modeling at Ripple

Ripple Engineering

My team is making use of a process known as threat modeling in order to assist our software engineers in building more secure products and features.   Threat model documents are the output of a threat modeling exercise. Once a security engineer has confirmed this is the case, then phase two begins. 

Coding 59
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Cyber Threat Hunting: Types, Methodologies, Best Practices

Knowledge Hut

Cyber threat can be defined as a potential attack, destruction or damage of a cyber system that is launched over a network. Cyber threat hunting is the practice of looking for cyber threats that are present undetected in a network. Threat hunting is known to spot malicious actors that slip past the security defenses.

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The Future of Cybersecurity: Career Growth

Knowledge Hut

This transformation has brought with it a new wave of threats and dangers, thus, making cybersecurity essential for businesses, governments, consumers and practically everyone else. Because of the continuous adoption of mobile devices, cloud services, and smart technologies, cyber threats are modernizing day by day.

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Optimizing the Value of AI Solutions for the Public Sector

Cloudera

In fact, most of the public servants I spoke with were predominantly cautious about the current limitations of generative AI, and underscored the need to ensure that models are used responsibly and ethically. As also expected, most had experimented on their own with large language models (LLM) and image generators.

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Intrusion Detection System (IDS): Types, Techniques, and Applications

Knowledge Hut

Depending upon these alerts, a SOC (security operations center) analyst or the incident responder investigates the issue and takes the required steps to eradicate the threat. Signature Detection: Signature -based intrusion detection systems use fingerprints of known threats to keep a check on them. Some of them are: 1.

Systems 52
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What is Machine Learning and Why It Matters: Everything You Need to Know

Knowledge Hut

Training involves using an appropriate algorithm and modelling the data. The training data is used to create the model. Evaluating the model includes testing its accuracy. To verify its accuracy to the fullest, the model so developed is tested on such data which is not present in the data during the second step.

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Parcel Protection: Inside UPS Capital’s Defensive Strategy with Striim & Google

Striim

Vertex AI then becomes pivotal , running advanced machine learning models like route anomaly detection and fraud detection for shipping transactions. Using Vertex AI’s extensive tools, these models are trained, refined, and implemented to discover insights, predict trends, and extract valuable information.