AI benefits of the Internet industry
The Internet industry uses AI technologies a lot. This includes such solutions as face and object recognition on social networks, voice recognition, photo search, and so on.
AI risk management for Internet Industry
The flip side: AI risks
Due to the popularity of AI-based solutions used over the Internet, this industry is extremely prone to attacks.
Privacy violation
Any recognition function involves the collection of information about an object or person. Incorrect and unethical use of this feature may lead to privacy violations. In case an attacker succeeds in deceiving the face or voice recognition system, the system, as in the case of cameras, may stop recognizing a person or will start mistaking him for another.
Copyright detection
Automated content checks can miss copyright infringement thus preventing those who claim ownership from identifying matching media or texts uploaded by users. It can come at a troubled time in distribution. The attack vector includes evasive content modifications.
Risks for content moderation and spam filters
Automated text analysis can misclassify spam and toxic online comments if malicious actors modify the text. This makes content moderation and spam filters ineffective.
Deepfakes and disinformation
Deepfakes has created a huge resonance in society and can seriously damage reputation. They make it possible to generate fake videos and images. Fake news detectors are special systems trained to detect artificially generated content. If manipulated, detectors can start to recognize comments as fake, which will lead to them being mistakenly blocked. Automated content integrity can misidentify disinformation.
Inaccurate recommendations
Search pages and news feeds can show unsafe or manipulated results in case of strategic data poisoning. These attacks refer to attempts to pollute machine learning models and threaten their integrity as well as to control the behavior of a trained model. They impact the ability to produce correct results.
LLMs and AI Chatbots
AI language models and chatbots such as GPT, Claude are vulnerable to various attacks: prompt injections, jailbreaks, data stealing, adversarial examples, and other safety bypass techniques.
AI incidents
- Face recognition systems implemented by social networks can be bypassed easily, and there are over 100 research articles published that are describing various ways to do that.
- Algorithms used by content filters can be spoofed by hackers to publish any illegal and offensive content. A number of examples have already been published in various research papers.
- Inference attacks on AI algorithms can be used to find out if an algorithm uses your own data in the training dataset, which can violate privacy.
- Advertising ML-based algorithms can be spoofed in order to perform fraudulent actions.
- Sentiment analysis can be bypassed to post comments that seem acceptable but are detected by AI systems as inappropriate, therefore downgrading the publication.
How we can help with AI risk management
Our team of security professionals has deep knowledge and considerable skills in cyber security, AI algorithms, and models that underlie any content moderation system. Your algorithms can be tested against the most critical AI vulnerability categories that include Evasion, Poisoning, Inference, Trojans, Backdoors, and others.
We offer Solutions for Awareness, Assessment, and Assurance areas to provide 360-degree end-to-end visibility on the AI threat landscape.
- Secure AI Awareness to demonstrate AI risks and shape AI governance strategy. It consists of Policy Checkup, AI Risks Training Threat Intelligence for informed decisions;
- Secure AI Assessment helps to perform AI integrity validation and identify AI vulnerabilities through Threat Modeling, Vulnerability Audit, and automated AI Red Teaming;
- Secure AI Assurance helps to remediate AI risks and implement a lifecycle for AI integrity. It consists of Security Evaluation, Risk Mitigation, and Attack Detection.
