30 Nov 2020, 15:52 — 8 min read
By this time, most of us have grown accustomed to interacting with intelligent virtual assistant chatbots, and in the meantime, we never realised that we are actually in touch with machines and not human beings.Whenever we connect with any customer care executive, it’s not a human; it is a bot that assists us by using the NLP (Natural Language Processing) method. But are you sure that your data is in safe hands in this era of rapid automation?
Developer reports say that 33 percent of the world web traffic is composed of malignant bot, and these unprotected terrible bots are responsible for a large number of security threats that online businesses are facing today.Because it is much obvious that no one can beat a human mind and virtual assistant chatbots became a vital part of every company’s technology infrastructure, companies are relying on it, but now this is the time when you need to protect yours. Companies and users are blindly trusting the system’s output due to which hackers have found it as a perfect vehicle for attacks. The vulnerabilities in chatbots may result in private data theft, IT theft, non-compliance, and many other cybersecurity attacks.
Here, are some ways on how to prevent your artificial intelligence bots from machine learning attacks. But before that, have a quick understanding of chatbots and their working.
Chatbots are intelligent virtual assistants who act like normal human beings, and the conversation mainly occurs via voice or text messages. Every industry vertical from banking to the healthcare industry has employed chatbots to serve its customers better in real-time. Bots use NLP (Natural Language Processing) to interact with the customers on the other end, and the best part is that you won’t even doubt that a bot is conversing with you.
To reduce customer support costs, waiting time for calls to get connected, and deliver instant acknowledgment, large tech companies (primarily the eCommerce) implement Virtual assistant chatbots to better assist their customers. Bots are at significant risk due to machine learning attacks, and you need to make sure that these VAs are secured under reliable and multilayer security solutions.
Well, who among us knew that these chatbots who have made the task easier for the companies would also have to face cyber attacks by hackers. On the one hand, they provide streamline and personalised customer service 24*7 while on the other hand, these unprotected chatbots add up to the contingency of data and privacy invasion.
Initially, chatbots were used mainly for conveying generic information, but the moving globe around us demanded automation and cost savings. For this, chatbots replaced human executives and started performing many critical human tasks. This reflects that chatbots are exposed to a high degree of access to sensitive information.
Virtual assistant are the piece of software that continuously interacts with customers and often remain unsupervised. They face the most common cyber attacks or machine learning attacks known as data poisoning. Hackers contaminate the training data of the model by inserting adversarial inputs into it. Let’s try to relate this with real-life examples. We all know that these days, eCommerce companies answer the queries of their customers using chatbots.
The computers are accustomed to the user-input data and replies with an instant pre-set answer using the user’s words or phrases. In the meantime, the conversation is never monitored unless and until the query is escalated to the human customer care executives.This is when hackers gain access to the data, leading to large beaches of private customer data, phishing attacks, and costly lawsuits for the company.
The ML system monitors the conversation between the user and the VA chatbot to keep them running continuously. Here, the network firewall and the web application firewall check the conversational level without disrupting the existing workflows.
Also read: Give AI a chance
Chatbots is a booming market now, and a growing number of companies are adopting to fuel customer experience queries. But, only a few companies have come up in the market to protect these chatbots.Hackers can quickly discover the data as they are sourced from public repositories, including data sets, models, and hyper-parameters.For an organisation to completely prevent its chatbots, it requires them to have in-depth knowledge and expertise in trending technologies like AI (Artificial Intelligence), ML(Machine Learning), NLP, and Data Science.
, an artificial intelligence company in California, is on a mission to protect the machine learning algorithms and the businesses that use them. They believe that machine learning attacks are the next primary threat vector in the security world.For this, they have confidently deployed AI into it and if you are also looking to have a robust solution like VA shield, just have a close eye on its working.
It is an intelligent security solution that analyses context at the conversational level and separates legitimate conversations from malicious attacks. For any organisation to deploy such a solution, it needs to have professional developers who have expertise and experience in the technologies mentioned above. VA Shield will help you protect your VA chatbots from ML attacks and keep the existing security workflow safe and secure. It analyses the request, responses, voice, and text conversation from the user using track analytics to provide an enhanced layer of monitoring and deeper business insights in using these bots.
Earlier, developers never knew that bots would be prone to malware attacks and didn’t incorporate the security component at its inception stage.
This is when companies should focus on the vast ocean of machine learning security use cases and add a critical zero-trust security framework to the existing chatbots system. Suppose your company has an AI-enabled chatbot system, in that case, you need to contact a top to ensure that your bots are protected with the new security level empowered to stop ML attacks.
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Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views, official policy or position of GlobalLinker.
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