Deep Dive: How Avast Uses AI To Maintain The Trust Of 435 Million User Base
The use of mobile phones in India has increased exponentially in recent years, with the main reason being more accessible internet. Today, the internet is being used in almost every remote area of our country. While people of India leverage its capabilities, most of them are also aware of the risks that it comes with. As digitisation increases, the risk of possible malware attacks and breaches through the internet has also increased. One of the names that often come up while talking about protection from attacks and device safety is Avast. The Indian market has always been a mobile-first market with the majority of the users accessing the internet on their mobile phones. Avast has more than 19 million active mobile and PC users and protecting these people has always been Avast’s priority. Avast started back in 1988, when one of its two founders, Pavel Baudis, encountered Vienna Virus on a floppy disk and developed a program to remove it. Avast’s business took off in the early 2000s when they introduced a freemium strategy that boosted their consumer user growth. Avast also offers solutions for small and medium-sized enterprises. In early years Avast majorly focused on PC security and they subsequently expanded their focus onto Android and iOS security. With a massive consumer base, Avast has been one of the best when it comes to providing security. So, for this week’s Deep Dive column, we got in touch with Avast’s Security Evangelist, Luis Corrons, to discuss their plans and how they use AI and machine learning in their products and services. Avast’s TechStack & Other Products Avast uses a wide range of technologies since their products run on different platforms, Windows and Mac’s applications are written mostly in C++ because their products such as Avast Antivirus, SecureLine VPN or CleanUP require low-level access to operating systems. For Windows, JavaScript is also used because of the flexibility to create a usable and friendly user interface. The backend system has JVM as their primary platform using Java and Scala to serve more than 400M users. Avast’s other products, apart from their flagship Antivirus for both desktops and mobiles, they offer privacy solutions to the users through SecureLine VPN for an encrypted connection, AntiTrack to mask fingerprint, Secure browser for safer and faster internet browsing or Passwords for managing passwords and credit cards details. They also offer products, which increase device performance like CleanUp, Battery Saver and Driver Updater. Use AI and ML Avast believes that a man and machine collaboration is what creates an efficient and secure system. Avast’s approach allows researchers to concentrate more time in the study of sophisticated and evasive threats if the AI takes the responsibility of detecting and blocking the malware. Avast believes as AI progresses towards helping fight against cybercrimes, the technology can also be used for the same, i.e., to promote cybercrime and exploit vulnerabilities better. The AI codes could launch attacks that can be run through software to find vulnerabilities that can then be exploited routinely. This is where something called behavioural pattern detection becomes essential. Because when everything fails, the behavioural patterns and anomalies are still possible to detect. Avast is always looking at the latest AI research and also searching for ways to adopt them. They work on the state-of-the-art techniques, for example; currently, they have been successful in the application of deep learning techniques on static analysis based detection of malware in Windows executable files. DeepAttacks: DeepAttacks are defined as ‘malicious content automatically generated by AI algorithms’. For example, DeepAttacks can be used to automatically adapt a generic phishing site to a target brand based on learning its visual style from the legitimate homepage. Avast has developed a mechanism to detect and block such attacks. DeepFakes: DeepFakes have become alarming, thus, Avast has shifted its concentration onto them. Aside from the internal research that they carry out, they have also been investing in academic research, funding universities research projects aimed at AI. Avast’s Engineering Team And Their Hiring Over 50% (from 1700+) of Avast’s employees work in research and development (R&D). Avast believes the R&D department has significant contributions when it comes to integrating AI in their products. Besides, when it comes to hiring for their AI and data science positions, Avast believes that the candidate should have fundamental skills in mathematics, statistics and engineering (modelling, signal processing, etc.). Avast thinks that a candidate who is strong in these essential areas and has worked on real data sets in previous jobs will be an ideal candidate to crunch the talent gap. Avast invests in training and developing its existing staff when it comes to AI. They cooperate with universities, support AI activities globally and work very close to the AI market. Company’s Future, Customer Trust and Competition Avast is dedicated to people’s security and privacy and has been rewarded regularly with awards such as VB100, AV-Comparatives, AV-Test SE Labs, among others. What sets Avast apart is their massive user base, which is around 435M and with adopting new technologies, Avast intends on building this user base even more. In future, they intend to continue to enhance security and extend their solutions on to the home smart device, IoT and smart home security areas.
The use of mobile phones in India has increased exponentially in recent years, with the main reason being more accessible internet. Today, the internet is being used in almost every remote area of our country. While people of India leverage its capabilities, most of them are also aware of the risks that it comes with. […]
One of the names that often come up while talking about protection from attacks and device safety is Avast.﻿ Here's how they use AI to protect their users from threats.
["deep fake"]
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["AI", "machine learning", "ML", "deep learning", "data science", "Aim", "RAG", "R", "JavaScript", "Go"]
Sameer is an aspiring Content Writer. Occasionally writes poems, loves food and is head over heels with Basketball.