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The DOs and DON’Ts of Passwords

The DOs and DON’Ts of Passwords

Passwords are the foundation of security and are required for almost everything. It's now essential for your email, bank accounts, and digital gadgets, among other things. It might be terrible if your personal or private information fell into the wrong hands. Always remember your password is as valuable as yo...

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Cybersecurity Vs. Information Security

Cybersecurity Vs. Information Security

Even among those in the security field, the terms "cybersecurity" and "information security" are used interchangeably. However, the two terms are not synonymous. Each of them addresses different kinds of security, and every organization investing in a proper security framework must understand each term, wh...

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A Complete Guide to Building Your Career as a Data Scientist

A Complete Guide to Building Your Career as a Data Scientist

We always wish to have someone, a mentor of sorts, who can guide us to start our professional careers. So, today, Infosectrain is here to help you towards your Data Science career. In this article, you will get some highly essential tips to start your career as a Data Scientist. Before going into the c...

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A Guide to Android Malware

A Guide to Analyze and Study the Android Malware

When I say we can't go a day without our phones or mobiles, I'm not exaggerating. I think everyone agrees because we store our entire lives on mobiles these days, right from pictures, important emails, contacts, documents, and bank details. With all this sensitive information on your mobile, imagine it fallin...

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Protect Your Organization with Pen Testing

Protect Your Organization with Pen Testing

Penetration testing, also attributed to Pen Testing, is a process of testing the security weaknesses or vulnerabilities of a system, application, or network and checking the possibilities of our network, system, or applications being hacked. Let me tell you a simple example to understand this concept q...

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Importance of Python in Data Science

Exploring Python and Its Significance in Data Science

As the world entered the era of big data in the last few decades, the need for better and more efficient data storage became a significant challenge. Organizations that use big data have primarily focused on developing frameworks that can store large amounts of data. Then frameworks such as Hadoop were develo...

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