AI Conversational System in Attack Surface Areas and Effective Defense Techniques

Artificial intelligence (AI) that enables real-time, human-like dialogue between a machine and a human is known as conversational AI. The fact that conversational AI is a fusion of several technologies, such as natural language processing (NLP), machine learning, deep learning, and contextual awareness, must be emphasized. Chatbots are one of the most popular conversational AI applications because they employ natural language processing (NLP) to interpret user input and carry on a conversation. Voice assistants, virtual assistants, and chatbots for customer service are examples of this usage. As the technology and use cases for these automated dialogues advance, there is a flip side to this. Thanks to the availability of scalable systems and AI technology, attackers may now target such systems. In this article, we will look closely at Conversational AI security issues and appropriate defensive solutions.

Conversational AI security risks

Automated conversation systems are particularly susceptible to assaults because they cannot distinguish between talks created by humans and machines. Additionally, because these systems are based on AI/ML, they inherit the greater security weaknesses of AI systems. Conversational systems leverage NLP as an interface layer to facilitate effective interactions with end users, adding a new threat vector to the dangers already present in ML systems.

1. Infected data

As a conversational system is based on AI/ML and is reliant on data, it might malfunction if the data is corrupted. AI systems learn how to do a task via data collected from a variety of sources. If the data are contaminated, the conversational system will also be contaminated, which will lead to poor judgments being made. Let's use an illustration to better understand: A misclassification of product suggestions by an attacker might have a machine-direct effect on revenue. Based on the categorized suggestions, a product might receive a better rating from a machine, but people would view it differently.

2. Adversarial attack

A conversational AI/ML system is most frequently attacked through adversarial assaults/filter evasion, also known as input attacks. Based on the information at their disposal, attackers design an attack and take advantage of a flaw in the ML/NLP models.

The attackers trick the machine learning system into making inaccurate predictions by introducing malicious inputs. A lot of antagonistic assaults have been reported in the past. One demonstrated that it is feasible to 3D-print a toy turtle with a texture that allows Google's object identification AI to label it as a rifle, independent of the perspective from which the turtle is photographed.

3. Fake Requests to the system

The AI system is growing so sophisticated that these assaults are becoming quite simple to carry out. Attackers can simply imitate fraudulent requests and transactions utilizing cloud infrastructure and AI that mimics human behavior.

For instance, attackers frequently email fake complaints, product queries, or purchase orders using a bot. This would ensure that legitimate requests are also lost, which would result in a loss of money.

4. Evil bot

Another issue has arisen as a result of the use of chatbots in hacking. Competition between firms is increasing by the day, ato to undermine the opponent's image in the industry, one may resort to utilizing a chatbot (better known as an "evil bot").

In March 2016, Microsoft introduced Tay, a chatbot meant to imitate and speak with people real timeime. Tay was a Twitter bot advertised as an experiment in conversational comprehension. According to Microsoft, the more you interact with Tay, the smarter it becomes. However, the bot fell short of expectations, revealing itself to be a blunder bot spewing racist, anti-Semitic, and vile insults.

5. Phishing attacks

Email and text message campaigns used in phishing scams, one of the most prevalent types of social engineering assaults, are created to arouse victims' curiosity, anxiety, or urgency. Then it prompts users to divulge private information, access risky websites, or download malicious files.

For instance, an email is sent to online service users warning them of a policy violation that requires immediate action on their part, such as a password change.

Effective Defence Technique

1. End-to-end Encryption

Encryption is the process of transforming a communication into one that only the sender and recipient can decrypt and read. This prevents any portion of the delivered communication from being seen by anybody else. This is unquestionably one of the most effective ways to ensure Chatbot security and is being frequently used by chatbot creators.

It's a crucial component of messaging systems like WhatsApp, and major internet companies have worked hard to ensure its security despite of opposition from national governments.

2. Authentication

This method is used to control access to those who are "really permitted." When logging in, users are required to enter a password and unique identification number. OTP (One Time Password) requests are another addition that users must now make.

This guarantees that no one is attempting to access someone else's account. Each user and employee through a similar authentication process can guarantee chatbot security. Authentication timeout and biometric authentication are other types of authorization.

3. Authentication Timeout

An added layer of protection is provided throughout the authentication process by a ticking clock. Verification tokens in this situation have a time restriction on their validity. When a user tries to get access, a time-sensitive code is delivered to his or her phone number or email address. When the token expires, the access is terminated. The requirement for several tries to get access to the data is eliminated by this strategy.

4. API Security

It provides an additional layer of defense. Users can use this functionality to send data only to IP addresses that have been white-listed. The IP addresses used to access the APIs will also be shown. If API security is enabled and a user attempts to send an SMS from a different IP address, an error will be displayed.

5. Secure Protocols

The HTTPS protocol is always used by default in security systems. Your data is protected from vulnerabilities and many forms of cyber-attacks if it is sent via the HTTPS protocol and encrypted connections, TLS, and SSL.

Conclusion

AI and conversational AI are both a blessing and a scourge in the digital age. Both security and system hacking are possible with its help. Cybersecurity will be strengthened if artificial intelligence is used more widely in industry. AI can investigate everything, although humans can only do so to a limited extent. Businesses will be able to act swiftly against customers who pose a threat if they have the capacity to do in-depth analysis.