Chatbots are quickly becoming a standard method for consumers to interact with a business. Organisations are beginning to identify the benefits of deploying chatbots. They are a revolutionary way in which people, computers and IoT devices can access and update information in real-time. Whilst bot technology has been around for the past few years now, there are several reasons for the recent uptick in their use.
Chatbots: Language and Communication
First, the core technology that powers chatbots is improving dramatically. This is enabling computers to process language and converse with humans in ways they never could before. Substantial advancements in Artificial Intelligence (AI) and Natural Language Processing (NLP) are making it possible for bots to better understand users’ needs and how to meet them.
Secondly, the way we communicate has changed drastically. In-person visits, phone calls and even emails are no longer the primary services by which companies engage with customers. Social media platforms, such as Facebook, have been early leaders in this new way of communicating. By promoting chatbot technology, developers gain the opportunity to produce a chatbot for their brand’s page. This can then interact with consumers and perform specific tasks within their messaging platform.
Controversy and Security
As we move forward in 2018, chatbot integrations will continue to gain popularity and usher in a new era of conversational interfaces. We have already seen many of the major tech companies release their own conversational interfaces. This includes the Amazon Echo, Samsung’s Bixby bot, and Apple’s Siri. In each of these, there’s no need to click or interact in any other way than using your voice. As chatbot technology continues developing, these conversations will eventually seamless. So much so that they will be indistinguishable from the conversations that we have with our friends and family. However, it would be foolish to ignore the security issues for bots.
Current bot solutions are not entirely secure and could leave a new door open to attacks from hackers. The insecurity of bots provides a cyber attacker direct access to an organisations’ network, applications and databases. One of the ways to improve this technology is to develop end-to-end encryption allowing only authorised users to access the information shared. The end-to-end encryption method would reduce the risk of third party attempts from breaking into the system. Chatbots will develop further over time, learning to collect more sensitive and personal information through AI and machine learning capabilities. Therefore, it is crucial for the security to enhance on the platform at the foundation level.
It is especially important for organisations to educate themselves and be aware of the risks when running a chatbot. They must consider vital factors, including sharing and storing the information, and most importantly who can access it.
Natural Language Processing and Security Awareness
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If companies aren’t aware of potential security risks, confidential data will be accessible by any determined hacker. Additionally, attackers may be able to repurpose chatbots to harvest sensitive data from unsuspecting customers. Digital and technology advancements should not come at the expense of enterprise security. They also do not need to come at the cost of security. To help prevent attacks opening from chatbot services it is essential to have a forward-thinking approach.
At BOHH Labs, we believe it is critical to ensure that each data request validates to the bot before gaining authorised access to a backend system or application. The security service supporting chatbot technology should be able to separate out the requestor from the request and securely allow the request to navigate to whatever end-point is required. This leaves the requestor waiting until the response has been collected and checked before moving it forward and returning the application to the requestor.
BOHH Labs does this in a number of ways, but mainly with our AI and NLP engines. These manage the data transaction process – the AI engine looks at and cleans any unwanted traffic, while the NLP engine takes the incoming message and determines where to send it. This means the user can use plain text with no command languages. Together, these two technologies can separate, recognise and maintain a secure connection to many different systems and prevent any third parties from trying to hop on the connection and get to the backend database. All of this happens in real time (hundredths of a second), so there is no disruption to the user experience, just the confidence that their transaction/request is secure.