The integration of artificial intelligence systems and machine learning is the next big development in the sphere of information technology. These systems have brought a new wave of advancements in technological developments. It has also transformed the way organizations were using Cyber Security Services to prevent cyber attacks. In old times, cybersecurity was used based on signature pattern matching or rules. With the advent of anti-virus software, companies started to rely on them, but it was used for detecting malware only that matches with the signature or virus definition.

A few years back, when someone said "Artificial Intelligence" (AI), we immediately thought about Skynet, Terminator, Matrix, HAL 9000, J.A.R.V.I.S., and all the other SCI-Fi technologies we saw in movies. Since then, things have changed quite drastically. When you hear about AI, you expect a conversation about smart assistants like Siri, Cortana, Alexa, or you expect to hear about how IBM Watson won Jeopardy! AI slowly went past the research phase and made its way into multiple industries including healthcare, fashion, weather forecasting, teaching, and driving. IBM even made Chef Watson cook some food (and it didn't even taste that bad).

Editor's Note: Hamsa Srinivasan contributed to this article. Most organizations have robust cybersecurity initiatives in place. However, it's no secret that such initiatives are not fool-proof. As the sophistication and complexity of cyber attacks increase, application security needs to rely on dynamic processes that can respond to more significant, rapidly-evolving threats. As the number of applications running on the cloud and mobile devices increases, security needs to be more pervasive and intelligent than ever.

This article is featured in the new DZone Guide to Security: Defending Your Code. Get your free copy for more insightful articles, industry statistics, and more! In April 2018, a social media giant had to notify nearly 90 million users that their personal data might have been "improperly shared." It was a colossal security breach. In October 2017, tens of thousands of harmless cameras were used to produce a massive distributed denial-of-service (DDoS) attack that dramatically decreased websites' function or even took them down by sending them billions of requests.

If you missed Part 1, you can check it out here! The next step is obtaining unauthorized access to user accounts. Imagine cybercriminals' need to get unauthorized access to a user's session. The obvious way is to compromise the account. For mass hacking, one of the annoying things is a captcha bypass.

I was reading about how Carbon Black, an endpoint detection and response (EDR) service, was exposing customer data via a 3rd party API service they were using. The endpoint detection and response provider allows customers to optionally scan system and program files using the VirusTotal service. Carbon Black did not realize that premium subscribers of the VirusTotal service get access to the submitted files, allowing a company or government agency with premium access to VirusTotal's application programming interface (API) to mine those files for sensitive data. It provides a pretty scary glimpse at the future of privacy and security in a world of 3rd party APIs if we don't think deeply about the solutions we bake into our applications and services. Each API we bake into our applications should always be scrutinized for privacy and security concerns, making sure end-users aren't being subjected to unnecessary situations.