Vulnerabilities of VA Chatbot Systems

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Chatbots are AI-powered systems that can appropriately interact with humans employing the direct use of natural language. Virtual assistant Chatbots are often known as ‘human computers’ with exceptional natural language processing skills. Alan Turing in 1950, first conceptualized a Virtual Chatbot by seeking the answer to “Can machines think?” Since then, Chatbots and virtual assistant technology have improved with great advances in natural language processing and machine learning algorithms. The availability of computational means for natural language interaction between computers and humans is becoming very similar to human interactions. More VA Chatbot systems are produced with an intent to support humans to organize complex tasks or making challenging decisions. As face to face interactions are less common these days, most of us are inclined to talk to our virtual assistants.

VA Chatbots rely on a set of rules or trained neural networks that decide the flow of dialogue in the interactions between the user and the Chatbot. In principle, VA Chatbots are not restricted to the application domain, but it is often found that Chatbots also rely on pre-specified patterns that trigger its behavior. This consequently restricts the possibilities of interaction patterns with human users. VA Chatbots can access large amounts of data to perform its function, making them extremely vulnerable to cyber-security attacks. Despite dependency on Chatbot services and the incorporation of more efficient and user-friendly customer experience across various platforms, one cannot easily overcome the cyber-security threats and attacks faced due to the use of these AI-powered systems.

VA Chatbot security risks can be grouped into two categories- Threats and Vulnerabilities.
Threats and vulnerabilities of VA Chatbots often go hand in hand. Threats can be defined as one-time occurring events, however, vulnerabilities are the cracks in the Machine learning systems that empower hackers or cyber-security attackers to comprise the overall security of AI-powered systems.

Vulnerabilities are how a system can be composed and made to function with diminished efficiency. An AI-powered VA Chatbot system can become vulnerable and open to attacks if it is not maintained properly. Poor coding, lack of protection, or simple human errors also make a VA Chatbot vulnerable to cyber-security attacks. Some common vulnerabilities of a VA Chatbot system are:

  • Discrepancies in rules that deal with data handling and storage:
    VA Chatbots collect information from users to be able to respond and resolve the queries put forth by them. This is how the Chatbots train themselves while interacting with the users and resolving the issues. The information assimilated by the Chatbots is stored and used later while again interacting with the users to make the conversation similar to the ones humans have in real-life. Before the implementation of the Chatbots, organizations must establish certain rules with regards to the data collected, its storage, the duration of its storage, and so on. Any discrepancies in establishing such rules make them vulnerable to attacks and susceptible to loss of sensitive information.
  • Malicious voice commands:
    Many virtual assistants function by listening to voice commands and following them. Though this feature of a VA Chatbot makes them highly superior, it also makes the Chatbots susceptible to cyber-security attacks. Most virtual assistants may not be able to recognize between real or fake voices. The attackers can use this to deceive the Chatbots by impersonating the voice and thus making them extremely vulnerable. Such malicious voice commands can be used to perform or override tasks such as opening smart doors, to starting the car engines to even retrieving money from the user’s accounts for various unlawful purposes.
  • VA Chatbot’s MFA vulnerabilities:
    Multi-factor authentication of Chatbot systems is considered as one of the best defense systems against cyber-security attacks. MFA protects weak and reused credentials while critically blocking automated attacks. With the implementation of long-term remote working, the underlying vulnerabilities of the MFA are more visible now. Attackers impersonating users can access the company as well as personal accounts by using phishing scams and social engineering. Some hackers may even simply exploit the flaws existing in the design of the ML –powered systems and manipulate it for malicious purposes.
  • Back door access:
    Virtual assistants are used for various tasks such as calling an Uber or sending a text. This feature of the Chatbots enables it to have complete access to other applications on the devices thus leaving them to be vulnerable to cyber-security attacks. Hackers can use VA Chatbots to extract private information from third-party applications to use the stored data for malicious activities. Cyber-security attackers can develop tools to enhance the VA Chatbot’s locus of control and employing them for malevolent purposes.
  • Transfer-learning attack:
    Most AI-powered VA Chatbots are constructed by fine-tuning already trained models with the addition of specialized attributes. This makes the Chatbots susceptible to various transfer learning attacks. For instance, in cases where the pre-trained models of the Chatbots are openly available, an attacker can use it to detour the Chatbot to perform malicious activities. All the generic features of the Chatbot can be manipulated and be used for conducting various cyber-security breaches.
  • Impersonation by criminal Chatbots:
    As VA Chatbots are becoming better and better at imitating humans, it is also becoming alarmingly vulnerable to cyber-security attacks. Hackers are manipulating and coercing once-friendly VA Chatbots to now impersonate or imitate customers and carry out criminal activities. These rogue Chatbots are viciously designed to establish rapport with organizations or individuals and probe them to either click malicious links or share sensitive information. The capability of smart hackers to turn virtual assistants into criminal Virtual assistants is now being explored by many organizations as it poses a threat to their businesses and client information.
  • Unauthenticated voice recording:
    Generally, the voice of a person speaking within the range of a VA Chatbot can be recorded. Even though the recording may be performed accidentally, the voice is still transferred to the cloud. This allows cyber-security attackers to break into one’s personal or organizational database. Hackers use this to eavesdrop on private and business conversations and collect or steal information. This potential for unintended voice recording shows that VA Chatbots do not necessarily have complete control over the voice data, thus making it intensely vulnerable to cyber-security risks.

Conclusion:
VA Chatbots have paved the way for a new technology where users can ask queries and the AI-powered systems interact using natural language nuances and provide the most optimized solutions. VA Chatbots have good potential to transform businesses online, but they can become vulnerable and end up thing destructive. These ML-powered systems are extremely complex so it ensures correct functionality while interacting with humans.  Any failure to fulfill the complex functionalities can lead to negative consequences for both the companies and the individuals using VA Chatbots for personal and business use. To resolve this, it is very crucial to test the functionality of Chatbots and monitor its codes and changes in attributes. To overcome the issue of cyber-security attacks and other vulnerabilities one must invest in a good virtual assistant shield or protection application. VA-protection systems that are built on machine learning using natural language processing as its interface layers can efficiently protect the VA Chatbots from malicious cyber-security activities. Adopting trustworthy AI-powered protection systems such as VA Shield ™ enables efficient protection of Virtual Assistant Chatbots from Machine learning attacks while securing and protecting the business without disrupting the existing workflow.