Persian :
برای اولین بار فایل کامل ایمیل های لیک شده پتروشیمی خلیج فارس برای روزنامه نگاران و محققان و مردم ایران

English :

For the first time, the complete file of leaked Persian Gulf Petrochemical emails for journalists, researchers and the people of Iran

password:OpIran

https://mega.nz/file/EBIi0a4Y#PfBS1tdaAfmwEYFyzL4sN317NPtNglTNh2dwqMW0pX4


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🖥 سری ویدیو های امنیت بلاکچین و قراردادهای هوشمند

🖥BSCS:Blockchain & Smart Contract Security - Smart Contracts


👨‍💻مدرس : saeid ghasemshirazi
🧬لینک ویدیو:
⛓https://youtu.be/D5I1NcTWQtk

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🏹The three stages of building a machine learning model are:

🏹Model Building
Choose a suitable algorithm for the model and train it according to the requirement
🏹Model Testing
Check the accuracy of the model through the test data
🏹Applying the Model
Make the required changes after testing and use the final model for real-time projects

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🛎What do you mean by Domain Name System (DNS) Attack?

DNS hijacking is a sort of cyberattack in which cyber thieves utilize weaknesses in the Domain Name System to redirect users to malicious websites and steal data from targeted machines. Because the DNS system is such an important part of the internet infrastructure, it poses a serious cybersecurity risk.

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🔥Clustering?

Clustering problems involve data to be divided into subsets. These subsets, also called clusters, contain data that are similar to each other. Different clusters reveal different details about the objects, unlike classification or regression.

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🔺What is Cross-Validation?

🔸Cross-Validation in Machine Learning is a statistical resampling technique that uses different parts of the dataset to train and test a machine learning algorithm on different iterations. The aim of cross-validation is to test the model’s ability to predict a new set of data that was not used to train the model. Cross-validation avoids the overfitting of data.

🔺K-Fold Cross Validation is the most popular resampling technique that divides the whole dataset into K sets of equal sizes.

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🪡Differentiate between spear phishing and phishing?

Spear phishing is a type of phishing assault that targets a small number of high-value targets, usually just one. Phishing usually entails sending a bulk email or message to a big group of people. It implies that spear-phishing will be much more personalized and perhaps more well-researched (for the individual), whereas phishing will be more like a real fishing trip where whoever eats the hook is caught.

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✳️What do you mean by Active reconnaissance?

Active reconnaissance is a type of computer assault in which an intruder interacts with the target system in order to gather information about weaknesses.
Port scanning is commonly used by attackers to detect vulnerable ports, after which they exploit the vulnerabilities of services linked with open ports.
This could be done using automatic scanning or manual testing with tools like ping, traceroute, and netcat, among others. This sort of recon necessitates interaction between the attacker and the victim. This recon is faster and more precise, but it generates far more noise. Because the attacker must engage with the target in order to obtain information, the recon is more likely to be detected by a firewall or other network security device.

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What do you mean by Authenticode?

Authenticode is a technology that identifies the publisher of Authenticode sign software. It allows users to ensure that the software is genuine and not contain any malicious program.

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🧅What is the Difference Between Supervised and Unsupervised Machine Learning?

🥨Supervised learning - This model learns from the labeled data and makes a future prediction as output
🍗Unsupervised learning - This model uses unlabeled input data and allows the algorithm to act on that information without guidance.


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⛔️What are Polymorphic viruses?

🔰Polymorphic viruses are sophisticated file infectors that may build changed versions of themselves in order to avoid detection while maintaining the same fundamental behaviors after each infection. Polymorphic viruses encrypt their programming and employ various encryption keys each time to alter their physical file makeup throughout each infection.

🔰Mutation engines are used by polymorphic viruses to change their decryption routines every time they infect a machine. Because typical security solutions do not use a static, unchanging code, traditional security solutions may miss them. They are considerably more difficult to detect because they use complicated mutation engines that generate billions of decryption routines.

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▫️Inductive Learning

◾️It observes instances based on defined principles to draw a conclusion

🔹Example: Explaining to a child to keep away from the fire by showing a video where fire causes damage

Deductive Learning

🔹It concludes experiences

🔺Example: Allow the child to play with fire. If he or she gets burned, they will learn that it is dangerous and will refrain from making the same mistake again


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✳️What is Microsoft Baseline Security Analyzer?

Microsoft Baseline Security Analyzer or MBSA is a graphical and command-line interface that provides a method to find missing security updates and misconfigurations.

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MC-GAN: A Reimplementation of GameGAN With a Gaming Perspective

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#Academic #Paper #GameGan
🛡MC-GAN: A Reimplementation of GameGAN With a Gaming Perspective


🔰Link
Publisher: IEEE
ISBN:978-1-6654-0426-6
Abstract:

Creating games is a costly process involving tons of vigorous efforts, time, and resources. Different game engines were introduced to facilitate the game-making process, such as Unreal Engine, Unity, and Godot. However, despite the advent of game engines, the vacuum of automatically creating new games by computers was still felt. With artificial intelligence (AI) development and its growing presence in the industry, game developers made a new game development branch using AI. One of the essential steps in this context was the introduction of GameGAN, which inspired us for this article. Here we propose Multi-Class GamgeGan(MC-GAN), a starting point for the next generation of game engines based on GameGAN. In addition, MC-GAN is capable of classifying each desired game element and even changing its class to change the element’s nature (e.g., MC-GAN can change static elements to dynamic ones). Moreover, MC-GAN uses only one complex model trained once per game. Once it is trained for that specific game, there will be no need for training to produce a new level of that game, a considerable step in the developing industry. Considering that MC-GAN is only the beginning of this big journey; therefore, it is now the best choice for developing web games since they are compact and straightforward. This article first briefly introduces GamGAN and its features; afterward, we get through MC-GAN features and compare them to other similar works.

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What Are the Differences Between Machine Learning and Deep Learning?

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🔥What is Overfitting?

The Overfitting is a situation that occurs when a model learns the training set too well, taking up random fluctuations in the training data as concepts. These impact the model’s ability to generalize and don’t apply to new data.

When a model is given the training data, it shows 100 percent accuracy—technically a slight loss. But, when we use the test data, there may be an error and low efficiency. This condition is known as overfitting.
There are multiple ways of avoiding overfitting, such as:

Regularization. It involves a cost term for the features involved with the objective function
Making a simple model. With lesser variables and parameters, the variance can be reduced
Cross-validation methods like k-folds can also be used
If some model parameters are likely to cause overfitting, techniques for regularization like LASSO can be used that penalize these parameters

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🥗Association

🍕In an association problem, we identify patterns of associations between different variables or items.

🥪For example, an e-commerce website can suggest other items for you to buy, based on the prior purchases that you have made, spending habits, items in your wishlist, other customers’ purchase habits, and so on.

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♠️What Is ‘naive’ in the Naive Bayes Classifier?

♣️The classifier is called ‘naive’ because it makes assumptions that may or may not turn out to be correct.

♣️The algorithm assumes that the presence of one feature of a class is not related to the presence of any other feature (absolute independence of features), given the class variable.

🔊For instance, a fruit may be considered to be a cherry if it is red in color and round in shape, regardless of other features. This assumption may or may not be right (as an apple also matches the description).

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💻AweClone

📌$29.95 FREE

نرم افزار شبیه سازی دیسک قابل اعتماد و با استفاده آسان. Magoshare AweClone راهی آسان، ایمن و سریع برای شبیه سازی تمام محتویات هارد دیسک به هارد دیسک/دستگاه دیگر را به شما ارائه می دهد. به لطف فناوری شبیه‌سازی بخش به بخش AweClone، می‌توانید تمام داده‌ها از جمله فایل‌ها/نرم‌افزار/تنظیمات را به‌طور کامل به یک هارد دیسک دیگر منتقل کنید یا هارد دیسک خود را به یک دیسک خارجی شبیه‌سازی کنید.

📥لینک دانلود

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💣What is a Random Forest?

A ‘random forest’ is a supervised machine learning algorithm that is generally used for classification problems. It operates by constructing multiple decision trees during the training phase. The random forest chooses the decision of the majority of the trees as the final decision.

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