How to Defend a Linux System from Attacks

December 2, 2020

In November this year, the BigBasket data breach compromised the information of more than 2 Billion users. Evidently, companies of all sizes are facing cyber-security risks, and it is important to address the measures that must be taken. In this article, we discuss the bit-by-bit of securing Linux servers from cyber attacks.

What is a cyber-attack?

A cyber-attack is an assault launched by cyber criminals using one or more computer networks. Attackers commonly use any vulnerable public servers and computers that are connected to the internet to launch the assault. The main goal of the attacker is to breach the firewall and extract company data for ransom. The attacker may also be a competitor who gains from ruining your company’s reputation and goodwill.

Types of cyber-attacks

The most common type of attacks are:

  1. DDoS attack: Here, the attacker uses a vulnerable server to launch a series of attacks on the target server. The attacker launches floods, i.e., directs a large amount of traffic to you, which will cause downtime on your server. To prevent a DDoS attack, purchase a high-bandwidth server so that floods cannot be caused easily.
  1. SQL Injection: If you are hosting a CMS like WordPress, Joomla, Magento, etc., using third-party themes and plugins from untrusted sources leaves your system vulnerable. SQL injection can manipulate all data in your database. Both server-side and code-side prevention methods are available to mitigate SQL injection. Make sure to adopt the latest technologies and update your CMS regularly. To be extra sure, using a vulnerability scanner like Acunetix is highly recommended. 
  1. Man-in-the-middle attack: Here, the attacker launches from the client-side and sets himself up as a mediator between the user and the server. Suppose, you are on public wi-fi, the attacker can crack the public wi-fi and enter your PC to steal information.  A secure network is the only way to prevent these types of attacks.

Cybersecurity Dos and Don’ts

  • Don’t use old software
  • Don’t write open-ended codes
  • Do use a robust firewall
  • Don’t set-up passwords that are in human-readable format
  • Do use antivirus on both system and server, especially remote systems like laptops, phones and tablets. (80% of users still don’t use even a free one!)
  • Do use an intrusion detection system on both server and system. As malware and Trojan can be uploaded from client PC as well, it is very important to counterbalance by setting up strong gates from the hosting side.
  • Do implement HTTPS. 
  • While uploading files, always use SFTP port.
  • Do train employees about permissions and antivirus. 

Basic security setups for linux web-hosting servers

There are several cyber-security processes that can secure files and databases on your servers to prevent, as well as actively defend attacks in real-time. As the WHM control panel is the most popular among Linux OS users, this article shows how you can implement many security features with WHM. However, the general rules are applicable to all other control panels.

Types of security:

  1. SSH hardening: SSH is one of the most popular communication protocols on the net. Although SSH is more secure than FTP, taking further steps to secure SSH is highly recommended. If you are non-technical, you can ask your hosting provider to execute the same. SSH-hardening can be done through WHM easily through the intuitive GUI.
  1. /tmp security: Securing the /tmp folder is unignorable if you are using Linux. The reason is because any malicious files can be executed by attackers on /tmp directories. WHM has a ready-made script to implement /tmp security. This creates a tmp partition which automatically fixes tmp security.
  1. Security using software-based firewalls: There are several third-party tools which easily integrate on host to improve security features. Here, we discuss the best tools available in the market for Linux systems.
  • Imunify360: This tool is an advanced firewall that tracks all activities on the server. It provides proactive defence by quarantining files that may be malicious. Using Imunify360, you can capture IPs, send alerts, block network-level access, scan malware, patch old PHP versions by default. It scans all uploaded files automatically, catches vulnerability and blocks IP. All tools are inbuilt and there is no need for configuration. 
  • CSF firewall: This open-source firewall for linux monitors incoming and outgoing traffic on network servers. Features include bruteforce attack alerts, suspicious process alerts, security score, warnings and per Port connection flooding detection and mitigation to help block DOS attacks. The system is quite fluid as you can enable/disable protections and configure custom SSH.
  • BitNinja - This intrusion detection system gives you security against wordpress, joomla, drupal infections for hosted websites.
  • Bigger organizations with heavy traffic can use third-party CDN like cloudware like Akamai. 

Lastly, in case an attack is encountered we must have a disaster recovery plan in  place to ensure that downtime is minimal. Some ways you can do this include:

  • Create backups for websites and portals. For image files backup, use any third party tools. You can also set up incremental backup on cPanel. WHM has integrations with Google Cloud, Azure AWS for implementing backups. You can pre-define the backup path and you also have an option to add an additional destination for backup. Custom script for backups can override existing scripts in WHM, in case you are looking for more secure solutions.
  • Set up version control systems which allow you to default back to previous versions in case your new versions are deemed insecure.
  • Regularly take MySQL backups and make sure to sync db files to a remote backup service.

This article thoroughly discusses all necessary measures to be taken in order to ensure a smooth-sailing Linux operation. Ensuring that all precautions are taken can help you mitigate any cybersecurity issues in the future.

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June 29, 2022

Project Management for AI-ML-DL Projects

Managing a project properly is one of the factors behind its completion and subsequent success. The same can be said for any artificial intelligence (AI)/machine learning (ML)/deep learning (DL) project. Moreover, efficient management in this segment holds even more prominence as it requires continuous testing before delivering the final product.

An efficient project manager will ensure that there is ample time from the concept to the final product so that a client’s requirements are met without any delays and issues.

How is Project Management Done For AI, ML or DL Projects?

As already established, efficient project management is of great importance in AI/ML/DL projects. So, if you are planning to move into this field as a professional, here are some tips –

  • Identifying the problem-

The first step toward managing an AI project is the identification of the problem. What are we trying to solve or what outcome do we desire? AI is a means to receive the outcome that we desire. Multiple solutions are chosen on which AI solutions are built.

  • Testing whether the solution matches the problem-

After the problem has been identified, then testing the solution is done. We try to find out whether we have chosen the right solution for the problem. At this stage, we can ideally understand how to begin with an artificial intelligence or machine learning or deep learning project. We also need to understand whether customers will pay for this solution to the problem.

AI and ML engineers test this problem-solution fit through various techniques such as the traditional lean approach or the product design sprint. These techniques help us by analysing the solution within the deadline easily.

  • Preparing the data and managing it-

If you have a stable customer base for your AI, ML or DL solutions, then begin the project by collecting data and managing it. We begin by segregating the available data into unstructured and structured forms. It is easy to do the division of data in small and medium companies. It is because the amount of data is less. However, other players who own big businesses have large amounts of data to work on. Data engineers use all the tools and techniques to organise and clean up the data.

  • Choosing the algorithm for the problem-

To keep the blog simple, we will try not to mention the technical side of AI algorithms in the content here. There are different types of algorithms which depend on the type of machine learning technique we employ. If it is the supervised learning model, then the classification helps us in labelling the project and the regression helps us predict the quantity. A data engineer can choose from any of the popular algorithms like the Naïve Bayes classification or the random forest algorithm. If the unsupervised learning model is used, then clustering algorithms are used.

  • Training the algorithm-

For training algorithms, one needs to use various AI techniques, which are done through software developed by programmers. While most of the job is done in Python, nowadays, JavaScript, Java, C++ and Julia are also used. So, a developmental team is set up at this stage. These developers make a minimum threshold that is able to generate the necessary statistics to train the algorithm.  

  • Deployment of the project-

After the project is completed, then we come to its deployment. It can either be deployed on a local server or the Cloud. So, data engineers see if the local GPU or the Cloud GPU are in order. And, then they deploy the code along with the required dashboard to view the analytics.

Final Words-

To sum it up, this is a generic overview of how a project management system should work for AI/ML/DL projects. However, a point to keep in mind here is that this is not a universal process. The particulars will alter according to a specific project. 

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June 29, 2022

Top 7 AI & ML start-ups in Telecom Industry in India

With the multiple technological advancements witnessed by India as a country in the last few years, deep learning, machine learning and artificial intelligence have come across as futuristic technologies that will lead to the improved management of data hungry workloads.


The availability of artificial intelligence and machine learning in almost all industries today, including the telecom industry in India, has helped change the way of operational management for many existing businesses and startups that are the exclusive service providers in India.


In addition to that, the awareness and popularity of cloud GPU servers or other GPU cloud computing mediums have encouraged AI and ML startups in the telecom industry in India to take up their efficiency a notch higher by combining these technologies with cloud computing GPU. Let us look into the 7 AI and ML startups in the telecom industry in India 2022 below.


Top AI and ML Startups in Telecom Industry 

With 5G being the top priority for the majority of companies in the telecom industry in India, the importance of providing network affordability for everyone around the country has become the sole mission. Technologies like artificial intelligence and machine learning are the key digital transformation techniques that can change the way networks rotates in the country. The top startups include the following:


Founded in 2021, Wiom is a telecom startup using various technologies like deep learning and artificial intelligence to create a blockchain-based working model for internet delivery. It is an affordable scalable model that might incorporate GPU cloud servers in the future when data flow increases. 


As one of the companies that are strongly driven by data and unique state-of-the-art solutions for revenue generation and cost optimization, TechVantage is a startup in the telecom industry that betters the user experiences for leading telecom heroes with improved media generation and reach, using GPU cloud online


As one of the strongest performers is the customer analytics solutions, Manthan is a supporting startup in India in the telecom industry. It is an almost business assistant that can help with leveraging deep analytics for improved efficiency. For denser database management, NVIDIA A100 80 GB is one of their top choices. 


Just as NVIDIA is known as a top GPU cloud provider, NetraDyne can be named as a telecom startup, even if not directly. It aims to use artificial intelligence and machine learning to increase road safety which is also a key concern for the telecom providers, for their field team. It assists with fleet management. 

KeyPoint Tech

This AI- and ML-driven startup is all set to combine various technologies to provide improved technology solutions for all devices and platforms. At present, they do not use any available cloud GPU servers but expect to experiment with GPU cloud computing in the future when data inflow increases.



Actively known to resolve customer communication, it is also considered to be a startup in the telecom industry as it facilitates better communication among customers for increased engagement and satisfaction. 


An AI startup in Chennai, Facilio is a facility operation and maintenance solution that aims to improve the machine efficiency needed for network tower management, buildings, machines, etc.


In conclusion, the telecom industry in India is actively looking to improve the services provided to customers to ensure maximum customer satisfaction. From top-class networking solutions to better management of increasing databases using GPU cloud or other GPU online services to manage data hungry workloads efficiently, AI and MI-enabled solutions have taken the telecom industry by storm. Moreover, with the introduction of artificial intelligence and machine learning in this industry, the scope of innovation and improvement is higher than ever before.




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June 29, 2022

Top 7 AI Startups in Education Industry

The evolution of the global education system is an interesting thing to watch. The way this whole sector has transformed in the past decade can make a great case study on how modern technology like artificial intelligence (AI) makes a tangible difference in human life. 

In this evolution, edtech startups have played a pivotal role. And, in this write-up, you will get a chance to learn about some of them. So, read on to explore more.

Top AI Startups in the Education Industry-

Following is a list of education startups that are making a difference in the way this sector is transforming –

  1. Miko

Miko started its operations in 2015 in Mumbai, Maharashtra. Miko has made a companion for children. This companion is a bot which is powered by AI technology. The bot is able to perform an array of functions like talking, responding, educating, providing entertainment, and also understanding a child’s requirements. Additionally, the bot can answer what the child asks. It can also carry out a guided discussion for clarifying any topic to the child. Miko bots are integrated with a companion app which allows parents to control them through their Android and iOS devices. 

  1. iNurture

iNurture was founded in 2005 in Bengaluru, Karnataka. It provides universities assistance with job-oriented UG and PG courses. It offers courses in IT, innovation, marketing leadership, business analytics, financial services, design and new media, and design. One of its popular products is KRACKiN. It is an AI-powered platform which engages students and provides employment with career guidance. 

  1. Verzeo

Verzeo started its operations in 2018 in Bengaluru, Karnataka. It is a platform based on AI and ML. It provides academic programmes involving multi-disciplinary learning that can later culminate in getting an internship. These programmes are in subjects like artificial intelligence, machine learning, digital marketing and robotics.

  1. EnglishEdge 

EnglishEdge was founded in Noida in 2012. EnglishEdge provides courses driven by AI for getting skilled in English. There are several programmes to polish your English skills through courses provided online like professional edge, conversation edge, grammar edge and professional edge. There is also a portable lab for schools using smart classes for teaching the language. 

  1. CollPoll

CollPoll was founded in 2013 in Bengaluru, Karnataka. The platform is mobile- and web-based. CollPoll helps in managing educational institutions. It helps in the management of admission, curriculum, timetable, placement, fees and other features. College or university administrators, faculty and students can share opinions, ideas and information on a central server from their Android and iOS phones.

  1. Thinkster

Thinkster was founded in 2010 in Bengaluru, Karnataka. Thinkster is a program for learning mathematics and it is based on AI. The program is specifically focused on teaching mathematics to K-12 students. Students get a personalised experience as classes are conducted in a one-on-one session with the tutors of mathematics. Teachers can give scores for daily worksheets along with personalised comments for the improvement of students. The platform uses AI to analyse students’ performance. You can access the app through Android and iOS devices.

  1. ByteLearn 

ByteLearn was founded in Noida in 2020. ByteLean is an assistant driven by artificial intelligence which helps mathematics teachers and other coaches to tutor students on its platform. It provides students attention in one-on-one sessions. ByteLearn also helps students with personalised practice sessions.

Key Highlights

  • High demand for AI-powered personalised education, adaptive learning and task automation is steering the market.
  • Several AI segments such as speech and image recognition, machine learning algorithms and natural language processing can radically enhance the learning system with automatic performance assessment, 24x7 tutoring and support and personalised lessons.
  • As per the market reports of P&S Intelligence, the worldwide AI in the education industry has a valuation of $1.1 billion as of 2019.
  • In 2030, it is projected to attain $25.7 billion, indicating a 32.9% CAGR from 2020 to 2030.

Bottom Line

Rising reliability on smart devices, huge spending on AI technologies and edtech and highly developed learning infrastructure are the primary contributors to the growth education sector has witnessed recently. Notably, artificial intelligence in the education sector will expand drastically. However, certain unmapped areas require innovations.

With experienced well-coordinated teams and engaging ideas, AI education startups can achieve great success.

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