Connect with us

Technology

Accessing Blocked Contents on the Internet

“Blocked contents on the internet are often times the most interesting stuffs we badly want to see aren’t they?”

Published

on

Accessing Blocked Contents on the Internet

Blocked contents on the internet are often times the most interesting stuffs we badly want to see aren’t they?

It is quite annoying when you want to click on an interesting content online, let’s say a video or some piece of information and upon first click, the web tells you, ‘restricted’. Like, isn’t it any longer a free world where information and contents should be available to just about everyone who wants it?

Of course not, there are always those ready and willing to gate-keep these things for what they will call, ‘the greater good’. And the worrying thing is they believe the stories themselves.

Other times, they may actually be right; like let’s say when they want to protect an intellectual property and stuffs like that from the public or from just about anybody with nefarious intents. But often times, it is just the government trying to cover its tracks by playing politics.

However, the beauty of the internet age is that, whatever counter measures you devise, there is another counter measure to counter whatever measures you come up with. If any of that makes sense.

So, the whole article is basically how to access blocked contents on the web, so here is how;

The use of Proxies

So what do proxies do exactly? They are practically tools operated in a browser window that is used to reroute internet connections to give fake IP addresses. This tactics is known as ‘spoofing’.

It’s like a teenager going to an adult party dressed as an adult to fool the bouncer into letting him in. In this instance, proxies dress your IP address to pretend it’s someone else so it can gain entry. Let’s say a North Korean wants to access some contents banned by their country, having proxies that mimic the IP address of somewhere else or someone else could see them gain entry to such contents.

Although, the problem with proxies is that they are quite limited, and speaking of North Korea, the user could likely get caught using it, but they are good for unblocking YouTube contents.

Accessing Blocked Contents on the Internet Accessing Blocked Contents on the Internet

The VPN method

Using Virtual Private Networks are a much better option compared to proxies. Like we explained with proxies, they operate very similarly; reroute connections to give fake IPs and location, but they are better at it than the proxies.

This is because they encrypt the user’s connection making it quite harder for anyone to see what the user is doing and having him arrested for viewing such. North Korea again comes to mind.

These tools are quite great at unblocking website contents under restriction, so even if you want to access some Chinese censored stuff or watch streaming contents available to specific regions.

Now, of what importance will the Virtual Private Networks be if they don’t offer protection against those looking to catch you? This is what the VPN does.

Although, the downside is that they cost big money and the even the free ones are quite limited.

The Shadowsocks Protocol

Some would say it was designed for the purpose of breaking through the Firewall of China, which for some reason sounds about racist when you think of it.

In all seriousness, the Shadowsocks protocol is like the love child of proxies and VPNs that was not fully formed. It encrypts connection but limited compared to the standard of the VPN. It is meant to unblock and hide traffic rather than provide security.

Setting it up is quite easy though with the aid of an open source program known as ‘Outline’.

The Onion Router

This one is practically intended for the ‘free folk’, a term for those who may not be privileged to have the money for the VPNs but wish to get past blocks. What TOR started out with was granting users entry into the dark web and the illicit goods it had on the offer.

But let’s not forget the fact that it does quite well spoofing the web and very much on par with the VPNs.

The Onion Router makes it quite difficult to track its user as it bounces off their connection between different nodes run by volunteers. And because they are not commercially owned, it makes the IP look even more real.

Although its downside lies in the fact that it is slow and wouldn’t do quite well downloading large files.

Decentralized VPNs

Now, we have seen the deformed child of the VPN with the Shadowsocks protocol, but when it’s done right, you have the birth of the decentralized VPN. They are the fusion of the ideas that birthed the VPNs and The Onion Router.

They offer the protocols and security of VPNs with the decentralized nodes of the onion router, which makes them the perfect tactics in breaking through blocks without risking safety.

The downside though, is that it is quite a Kryptonite that is complex to access as would be users will need to sign on to a service, buy crypto and have to deal with technical terms they may be oblivious to.

 

Continue Reading
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

Technology

Overview of big data use cases and industry verticals

Published

on

Big data refers to extremely large and complex data sets that are too big to be processed using traditional data processing tools. Big data has several use cases across various industry verticals such as:

  1. Healthcare: Predictive maintenance, personalized medicine, clinical trial analysis, and patient data management
  2. Retail: Customer behavior analysis, product recommendations, supply chain optimization, and fraud detection
  3. Finance: Risk management, fraud detection, customer behavior analysis, and algorithmic trading
  4. Manufacturing: Predictive maintenance, supply chain optimization, quality control, and demand forecasting
  5. Telecommunications: Network optimization, customer behavior analysis, fraud detection, and network security
  6. Energy: Predictive maintenance, energy consumption analysis, and demand forecasting
  7. Transportation: Logistics optimization, predictive maintenance, and route optimization.

These are just a few examples, big data has applications in almost all industry verticals, and its importance continues to grow as organizations seek to gain insights from their data to drive their business outcomes.

Continue Reading

Technology

Data Warehousing and Data Management Cost Optimization

Published

on

Data Warehousing and Data Management Cost Optimization

In this article, we will discuss the key aspects of data warehousing and management cost optimization and best practices established through studies.

Data warehousing and management is a crucial aspect of any organization, as it helps to store, manage, and analyze vast amounts of data generated every day. With the exponential growth of data, it has become imperative to implement cost-effective solutions for data warehousing and management.

Understanding Data Warehousing and Management

Data warehousing is a process of collecting, storing, and analyzing large amounts of data from multiple sources to support business decision-making. The data stored in the warehouse is organized and optimized to allow for fast querying and analysis. On the other hand, data management involves the processes and policies used to ensure the data stored in the warehouse is accurate, consistent, and accessible.

Why is Cost Optimization Important?

Data warehousing and management costs can add up quickly, making it essential to optimize costs. Implementing cost-optimization strategies not only reduces financial burden but also ensures that the data warehousing and management system remains efficient and effective.

Cost optimization is important for data warehousing and management for several reasons:

Financial Benefits: Data warehousing and management can be expensive, and cost optimization strategies can help reduce these costs, thereby increasing the overall financial efficiency of the organization.

Improved Performance: Cost optimization strategies, such as data compression, data archiving, and data indexing, can help improve the performance of the data warehousing and management system, thereby reducing the time and effort required to manage the data.

Scalability: Implementing cost-optimization strategies can help to scale the data warehousing and management system to accommodate increasing amounts of data, without incurring significant additional costs.

Improved Data Quality: By implementing cost-optimization strategies, such as data de-duplication and data partitioning, the quality of the data stored in the warehouse can be improved, which can lead to better decision-making.

Overall, cost optimization is important for data warehousing and management as it helps to reduce costs, improve performance, and maintain the quality of the data stored in the warehouse.

Established Cost Optimization Strategies

Scalable Infrastructure: It is important to implement a scalable infrastructure that can handle increasing amounts of data without incurring significant costs. This can be achieved through cloud computing solutions or using a combination of on-premises and cloud-based solutions.

Data Compression: Data compression can significantly reduce the amount of storage required for data, thus reducing costs. There are various compression techniques available, including lossless and lossy compression, which can be used depending on the type of data being stored.

Data Archiving: Data archiving is the process of moving data that is no longer actively used to cheaper storage options. This helps to reduce the cost of storing data while ensuring that the data remains accessible.

Data de-duplication identifies and removes duplicate data from the warehouse. This helps to reduce storage costs and improve the overall performance of the data warehousing system. Data de-duplication is a cost optimization strategy for data warehousing and management that focuses on identifying and removing duplicate data from the warehouse. This is important for several reasons:

Reduced Storage Costs: Duplicate data takes up valuable storage space, which can be expensive. By removing duplicates, the storage requirements for the data warehouse can be reduced, thereby reducing storage costs.

Improved Data Quality: Duplicate data can lead to confusion and errors in decision-making, as it may not be clear which version of the data is accurate. By removing duplicates, the quality of the data stored in the warehouse can be improved, which can lead to better decision-making.

Improved Performance: The presence of duplicate data can slow down the performance of the data warehousing system, as it takes longer to search for and retrieve the desired data. By removing duplicates, the performance of the data warehousing system can be improved, reducing the time and effort required to manage the data.

Increased Security: Duplicate data can pose a security risk, as it may contain sensitive information that can be accessed by unauthorized individuals. By removing duplicates, the security of the data stored in the warehouse can be increased.

Overall, data de-duplication is an important cost optimization strategy for data warehousing and management, as it helps to reduce storage costs, improve data quality, improve performance, and increase security. It is important to implement an effective data de-duplication solution to ensure the success of this strategy.

Data Partitioning: Data partitioning involves dividing the data into smaller, manageable chunks, making it easier to manage and analyze. This helps to reduce the cost of storing and processing large amounts of data.

Data Indexing: Data indexing is the process of creating an index of the data stored in the warehouse to allow for fast querying and analysis. This helps to improve the performance of the data warehousing system while reducing costs.

Automation: Automating data warehousing and management processes can significantly reduce the cost and effort required to manage the data. This includes automating data extraction, transformation, loading, and backup processes.

Conclusion

In conclusion, data warehousing and management cost optimization is a crucial aspect of any organization. Implementing cost-optimization strategies, such as scalable infrastructure, data compression, data archiving, data de-duplication, data partitioning, data indexing, and automation, can significantly reduce the cost of data warehousing and management while ensuring that the system remains efficient and effective.

It is important to keep in mind that the specific cost-optimization strategies used will depend on the unique needs and requirements of each organization.

 

Continue Reading

Technology

Overview of big data security and privacy

Published

on

Big data security and privacy are crucial considerations in the era of large-scale data collection and analysis. The security of big data refers to the measures taken to protect data from unauthorized access, theft, or damage. Privacy, on the other hand, refers to the protection of sensitive and personal information from being disclosed to unauthorized parties.

To ensure the security of big data, organizations adopt various measures such as encryption, access control, network security, data backup and recovery, and others. Additionally, they may also implement compliance with security standards and regulations such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA).

However, the increased use of cloud-based big data solutions and the rise of the Internet of Things (IoT) have brought new challenges to the security and privacy of big data. To mitigate these challenges, organizations are using technologies such as blockchain, homomorphic encryption, and differential privacy to provide stronger privacy and security guarantees.

In conclusion, big data security and privacy are crucial components of the big data landscape. Organizations must implement robust measures and technologies to protect sensitive and personal information, maintain the security of big data, and comply with relevant security regulations.

Continue Reading

Trending