An overview of SIEM components and capabilities:

Alerting-Identifies urgent issues by analyzing

events and sending alerts

Threat Hunting- Allows security staff to search logs

and events for threats proactively Forensic analysis- Provides insight into security

incidents by exploring log and event data

Data Aggregation- Gathers and aggregates data from security systems and network devices

Threat Intelligence- Integrates internal data with third-party data on threats and vulnerabilities

Dashboards-Presents visualizations that help staff

identify patterns and anomalies in event data

Incident response-It helps security teams identify, and respond to security incidents, bringing in all relevant data rapidly to respond on time.

Retention- Data and metrics are recorded for a long time, which is quite useful for forensic investigations and compliance in the future.

SOC automation- SIEMS with advanced capabilities can respond to security incidents by orchestrating multiple security systems (SOAR)

Analytics- A range of statistical models and machine learning algorithms are used to identify relationships between data elements within metrics.

گزارش صنعت نسل ۴ برای توسعه فراگیرجهان در آغاز یک انقلاب جدید فناوری مبتنی بر فناوری‌های صنعتی نسل 4.0 مانند هوش مصنوعی، روباتیک و اینترنت اشیا است. در این راستا ستاد اقتصاد دیجیتال و هوشمندسازی این گزارش را به زبان فارسی در اختیار علاقمندان قرار می‌دهد.

دانلود کتاب فارسی WSTG
استاندارد جامعی که اغلب در فرآیند تست نفوذ وب مورد استفاده قرار می گیرد، استاندارد WSTG یا Web Security Testing Guide است.
نویسنده : مهندس نیک آور
@SecCode

How Android's Private Compute Core works

Android's Private Compute Core essentially keeps sensitive data for features like Live Translate, Now Playing, and Smart Reply confidential from other subsystems. To do so, Google utilizes techniques like Interprocess Communications (IPC) binds and isolated processes. These techniques are included in the Android Open Source Project and can be controlled by publicly available surfaces like Android framework APIs.

To summarize, here are the top types of charts and their uses:

Number Chart - gives an immediate overview of a specific value.

Line Chart - shows trends and changes in data over a period of time.

Maps - visualizes data by geographical location.

Waterfall Chart - demonstrates the static composition of data.

Bar Graphs - used to compare data of large or more complex items.

Column Chart - used to compare data of smaller items.

Gauge Chart - used to display a single value within a quantitative context.

Pie Chart - indicates the proportional composition of a variable.

Scatter Plot - applied to express relations and distribution of large sets of data.

Spider Chart - comparative charts great for rankings, reviews, and appraisals.

Tables - show a large number of precise dimensions and measures.

Area Chart - portrays a part-to-whole relationship over time.

Bubble Plots - visualizes 2 or more variables with multiple dimensions.

Boxplot - shows data distribution within multiple groups.

Funnel Chart - to display how data moves through a process.

Bullet Chart - comparing the performance of one or more primary measures.

Treemap - to plot large volumes of hierarchical data across various categories.

Stream Graph - shows trends and patterns over time in large volumes of data.

Word Cloud - to observe the frequency of words within a text.

Progress Chart - displays progress against a set target or goal.