AI Image Generator: An Emerging Cybersecurity Threat
Artificial intelligence (AI) has the potential to change the nature of society. Although artificial intelligence tools bring us a lot of expectations, we also need to be vigilant in many aspects. For example, cybercriminals and other threat actors are weaponizing artificial intelligence, and even AI image generators are not immune to abuse.
What is an AI image generator? How do they work? If you've ever used an AI image generator, it's pretty clear what they are all about. Even if you've never used one, you've likely encountered AI-generated images on social media and elsewhere. Today's popular software works very simply: the user enters text, and artificial intelligence generates an image based on that text.
In recent years, with the development of artificial intelligence technology, most text-to-image generators adopt diffusion models, which means that they accept Long hours of "training", which is the main reason why their work is so impressive and stunningly realistic.
What makes these AI tools even more impressive is that they not only modify existing images or merge thousands of images into one, but also create new original images from scratch. The more people use these text-to-image generators, the more information they get and the better their creations become.
There are already many famous AI image generators: WOMBO, DALL-E, Stable Diffusion, Midjourney, DeepAI, Fotor and Craiyon. Tech giants - including Google - are releasing their own, so we can only speculate that more value will come in the future.
4 Ways Threat Actors Weaponize AI Image Generators
Like almost all technologies, AI image generators can be abused by malicious actors. In fact, they have been used for all sorts of nefarious purposes. But exactly what types of scams can criminals pull off with the help of AI image generators?
1. Social Engineering
One obvious thing that threat actors can do with AI image generators is to engage in social engineering; for example, creating fake social media profiles . Some of these programs can create incredibly realistic images that look like real photos of real people, and scammers can use these fake social media profiles for phishing purposes.
Unlike photos of real people, AI-generated photos cannot be discovered through reverse image searches, and cybercriminals don’t have to use a limited number of photos to deceive targets — using AI, they can generate any number of photos, Build a compelling online identity from the ground up.
However, in real life, threat actors can use AI image generators to trick people. In April 2022, Tech Talk blogger Ben Dickinson received an email from a law firm claiming that he had used an image without permission. The attorneys emailed a DMCA copyright infringement notice, telling Dickinson he needed to link back to their client or remove the image.
Dickinson searched the law firm on Google and found the official website. It all seems completely legal; the website even has photos of 18 attorneys, including their biographies and credentials. But none of this is true. The photos were all generated by artificial intelligence, and the alleged copyright infringement notice was sent by someone hoping to extort backlinks from unsuspecting bloggers.
2. Charity Scam
When devastating earthquakes hit Turkey and Syria in February 2023, millions of people around the world expressed their gratitude by donating clothes, food and money. Solidarity with victims.
Scammers are taking advantage of this, using artificial intelligence to create realistic images and solicit donations, according to a BBC report. A scammer showed off AI-generated images of ruins on TikTok Live, asking their viewers for donations. Another posted an AI-generated image of a Greek firefighter rescuing an injured child from rubble and asked his followers to donate.
One can only imagine what types of charity scams criminals will run with the help of artificial intelligence in the future, but it’s a safe bet that they will only get better at abusing the software.
3. Deepfakes and disinformation
Governments, activist groups and think tanks have long warned of the dangers of deepfake AI image generators, and that’s because nothing can Stop disinformation agents from creating false images with the help of bots and promoting it on social media.
In March 2022, a fake video depicting the Ukrainian president telling Ukrainians to surrender circulated online, according to NPR. While this is just one example, the possibilities are nearly endless, and there are countless ways threat actors can damage someone’s reputation, promote false narratives or spread fake news with the help of artificial intelligence.
4. Advertising fraud
Trend Micro researchers discovered in 2022 that scammers are using artificial intelligence-generated content to create misleading ads and promote shady products. They create images suggesting popular celebrities use certain products and run advertising campaigns based on those images.
For example, one ad for “Financial Advice Opportunities” features Tesla’s founder and CEO. Of course, Musk never endorsed the product in question, but the AI-generated footage made it look like this, presumably to lure unsuspecting viewers into clicking on the ad.
Artificial Intelligence and Cybersecurity: Complex Issues We Need to Solve
Looking ahead, government regulators and cybersecurity experts may have to work together to address the emerging emergence of AI-driven cybercrime threats. But how can we regulate AI and protect ordinary people without stifling innovation and limiting digital freedom? This issue will become prominent in the coming years.
Until you get an answer, do what you can to protect yourself: scrutinize anything you see online, avoid questionable websites, use security software, keep your devices up to date, and learn to use Use artificial intelligence to your advantage.
Original title: AI Image Generators: An Emerging Cybersecurity Threat
##Original author: DAMIR MUJEZINOVIC
The above is the detailed content of AI Image Generator: An Emerging Cybersecurity Threat. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1658
14
1415
52
1309
25
1257
29
1231
24
Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions
Jun 28, 2024 am 03:51 AM
This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP
Context-augmented AI coding assistant using Rag and Sem-Rag
Jun 10, 2024 am 11:08 AM
Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application
Seven Cool GenAI & LLM Technical Interview Questions
Jun 07, 2024 am 10:06 AM
To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text
Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations
Jun 11, 2024 pm 03:57 PM
Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it
Five schools of machine learning you don't know about
Jun 05, 2024 pm 08:51 PM
Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing
To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework
Jul 25, 2024 am 06:42 AM
Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A
SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time
Jul 17, 2024 pm 06:37 PM
Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S
SK Hynix will display new AI-related products on August 6: 12-layer HBM3E, 321-high NAND, etc.
Aug 01, 2024 pm 09:40 PM
According to news from this site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year
