Chatbots have made a huge impact on just about everything around us. From healthcare to banking, these clumsily disguised chatting robots have left a mark on every sector. They are making customer experiences grander, healthcare more navigable, and banking much easier.
In fact, by the end of this year, almost 80% of companies would have employed a chatbot to elevate their customer experience and around 85% of customer interactions will happen without human interference. No matter how much people try to doubt it or reject it, chatbots are not going anywhere. They are here to stay. So, it makes sense that we get acquainted with their ugly downsides too.
Security Risks in view of Chatbots
While an increasingly automated world makes our lives easier, it also brings forward the possible security risks that might have been swept under the rug by the rapid pace of innovations.
Recently many cyber-security incidents relating to VA chatbots have come to light. The Delta Airline’s data breach case of 2017 being the most controversial one. The hackers were able to modify the chatbot’s source code and steal users’ confidential data.
Delta Airline’s case demonstrates just how attackers are exploiting the loopholes in the chatbot developmental frameworks to access sensitive data. Hackers are using these largely unseen backdoor channels to manipulate chatbots with malicious intent. For instance, a user interacting with a banking chatbot can be provided a duplicitous link that could redirect the user to another web-page where fraudulent transactions can occur.
Thanks to the prevailing digitization in the world of business, the value of data is often equated to that of gold. And failing to secure this data can put your business on shaky grounds in the eyes of your customers. What’s more, it can even result in consumer class action lawsuits that can put your business back millions of dollars.
But data theft is not where it all ends. There is also a recent emergence of a new category of stealthy attackers whose aim is not to steal data, but rather to manipulate or poison it. Attackers can corrupt chatbots in such a manner that the purpose or user request is mis-classified triggering an incorrect response. This, in turn, can cause disappointment and frustration among customers or, worse yet, a complete shutdown of the model. Another case is where an attacker adds an excessive number of malicious queries through bots or overloads the system with bot requests by releasing multiple bots at once, which can end up causing massive problems in customer retention by obstructing the passage for genuine customers. Both of these cases can end up increasing computational expenses and manual labor for the company.
Cybercriminals can also tinker with the chatbot requests to falsify the analytics drawn from these engagements. Because most businesses make decisions based on analytics, such type of poisoning can be detrimental to a company’s entire business strategy.
All the above-mentioned scenarios of possible chatbot attacks highlight the urgent need for security measures required to combat malicious actors. But protecting chatbots or even developing such a solution that defends against chatbot attacks is a highly difficult job.
Well, this question is pretty hard to answer. For starters, the underpinning technologies that are fueling these chatbots are Machine Learning (ML) and Natural Language Processing (NLP) – both of which are equally difficult to defend against attacks. The former due to its inherent constitution is vulnerable to malicious attacks and the latter because of its free form nature brings additional complexity.
At the end of the day, a chatbot is just an ML-based software program that attempts to disguise itself as a human. But, unlike humans, these ML models have no baseline knowledge their entire intelligence comes from either the dataset or the ‘learning’ they do from experiences. On top of that, ML algorithms used to build these ML models are available publicly as part of the open-source movement. Armed with this knowledge, hackers can get hold of the models which makes it that much easier to craft attacks.
This is why it is so challenging to secure VA chatbots, not to mention, the obscurities that NLP brings. Natural language processing is a new and evolving domain, there is not enough exposition available on the ways it can be foiled by alterations in context.
Thus, in the end, it all adds up to one big head scratch for the companies looking to employ chatbots. At best, chatbots are a way to automate your business and fine-tune customer engagement. At worst, they’re a dangerous cybersecurity risk that could probably compromise the integrity of your company. We were also on the same crossroads once. But with our years of research and expertise in machine learning (ML), artificial intelligence (AI) and natural language processing (NLP), we developed a security solution to help keep up with the continuous innovation. VA Shield, our flagship product, is a chatbot security solution that analyzes requests, responses, and conversations to and from the system to provide an enhanced layer of monitoring.
In this age of instant gratification and advancing digitization, much of our attention often gravitates towards those businesses that provide real-time, hassle-free customer service. With quality user experience demand growing alongside expanding chatbot employment, Scanta’s VA Shield™ is primed to protect your business from possible VA attacks so that your business is in a better position against the changing tides of technological tactics.