Category Archives: automation

Harnessing Machine Learning and Automation against Advanced Threats

Estimated reading time: 2 minutes

With the specter of advanced cybersecurity threats always on the horizon, enterprises are seriously considering harnessing the power of machine learning and automation to fight against these threats. For good reason too – a cybersecurity survey suggested that organizations with an extensive use of automation rated themselves as much more likely to prevent, detect, respond and contain a cyber attack.

These concepts are getting increasingly important in today’s changing era of fast-growing cyber threats but what do they mean exactly? Machine learning basically refers to computers learning from data instead of receiving explicit programming. Through such machine learning algorithms, computers are fed huge datasets and parse through them to recognize patterns or co-relations through extended data analysis.

The importance of machine learning

Machine learning is becoming a common feature in more and more industries and cybersecurity has not lagged behind. An ABI Research report estimated that machine learning in cybersecurity will boost big data, intelligence and analytics spending to $96 billion by 2021. It is quite clear why there is such extended growth – machine learning allows business to offer a better response and bolster their own defense when it comes to the big, bad world of cyber threats. Security companies are rejigging the solutions they offer in tune with this trend. They are moving from signature-based systems to layered solutions where machine learning systems interpret data to better detect malware.

Some of these advantages are:

Making Sense of Data – The amount of data that can be collected for cybersecurity is humongous. While the sheer size and amount of data may be too much for humans alone to analyze, this is where machine learning can step in. By analyzing and processing big amount of data, it may be possible to find patterns or categories of certain behavior which can be used to fight advanced cybersecurity threats.

Using Automation for Better Protection – Different threats can have different attack points for an enterprise and even one threat may attack different touchpoints in different ways. This is where automation can do a much more effective job. By understanding the predicted behavior and touchpoints of a potential attack, automation can create better protection measures across touchpoints suited to exactly the type of predicted attack.

Using A Cluster-based approach for better detection – Quick Heal already uses machine learning to solve various cybersecurity problems using a cluster-based approach, illustrated in this whitepaper. Sample are clustered through machine learning with each cluster having samples similar to each other. These generated clusters are huge and processing them happens through machine learning where they are aggregated, analyzed and automated. The data is then labeled and processed to generate models. After scrutiny on numerous factors including time, size, quality, they are qualified for endpoint deployment.

Machine Learning and automation will be great weapons in the fight against advanced cybersecurity threats but it also need to be backed up with a combination of data science and human expertise.


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Siemens LOGO!, a PLC for small automation projects, open to attack

LOGO!, a programmable logic controller (PLC) manufactured by Siemens, sports three vulnerabilities that could allow remote attackers to reconfigure the device, access project files, decrypt files, and access passwords. About LOGO! LOGO! is an intelligent logic module meant for small automation projects in industrial (control of compressors, conveyer belts, door control, etc.), office/commercial and home settings (lighting control, pool-related control tasks, access control, etc.). It is deployed worldwide and can be controlled remotely. About the … More

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Network automation market expected to grow to $16.9 billion by 2022

According to market research by MarketsandMarkets, the network automation market size is expected to grow from $2.3 billion in 2017 to $16.9 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 48.7% during the forecast period. Major drivers of the network automation market include the critical need for network bandwidth management and network visibility, and growing adoption of smart connected devices across industry verticals. Moreover, increasing adoption of virtual and software-defined network infrastructure … More

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Five ways automating IAM saves you money

Identity is the foundation of security, so a robust automated identity and access management (IAM) system is by far the best way to keep your company’s information safe. It’s also a great way to increase efficiency and save money. It’s no wonder so many businesses are adopting IAM systems. The global market value of identity and access management systems has grown from $4.5 billion in 2012 to $7.1 billion in 2018. By 2021, it is … More

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Engineering teams are struggling because they’re missing the right automation

Driven by the trend of microservices creating complexity in code delivery and every company becoming a technology company, the software development community is under enormous pressure to deliver high-quality, leading-edge, and scalable code to an insatiable market. Data from a new survey by Codefresh exposes the relentless pressure, with 32 percent reporting they were not using any CI/CD tools at all, and about 60 percent agreeing that their organizations are “not using the right amount … More

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