Deepware Blog

To accurately analyze the danger of synthetic media, it is worth comparing it with other methods of today, commonly used in crimes targeting companies. Predicting how synthetic media will develop and strengthen financial crime schemes that have caused billions of dollars in losses to date is important for assessing the level of threat.

Deepfake, the most advanced and dangerous type of synthetic media manipulated by artificial intelligence (ai) tools, could soon serve many different demonic purposes. It is not difficult to predict that the most common cyber-attacks, on the other hand, will be financially qualified. Because IT crimes, which are registered on judicial records with definitions such as cyber extortion or fraud, are more dynamic, fast, easy, effective, profitable and difficult to catch and they will increasingly turn to deepfake. Deepfake-backed financial crimes, in the pandemic process where face-to-face communication is restricted, have achieved far more favorable conditions for setting cyber traps.

In order to detect synthetic media, defined as Deepfake, in a timely manner and without causing major damage, detection technologies also need to achieve hyper-realistic detection performance in the near future. The key point in deepfake detection is to eliminate boundaries in detection and get a clue that will allow deepfakes to reach the level of capture that will be produced using as-yet unknown techniques.

All developed deepfake detection models focus on the common characteristics of deepfakes and aim to detect synthetic media produced by different production techniques in the widest possible scope and with the highest accuracy. As long as we identify a vulnerability that will make deepfake easier to detect and limit the danger, it doesn’t seem like it’s time to completely solve it.

This is not a 2009 Hollywood 3-Oscar 3D science fiction masterpiece with an official budget of $ 237 million. We’re talking about your synthetic digital image that you can easily create using simple everyday applications on your personal phone, tablet or computer. Who doesn’t want to look fitter, more attractive, and more handsome and face others with more beautiful skin? “Digital makeup”, which covers physical defects and reveals a synthetic digital image that can be called an avatar of a person, is becoming increasingly important as communication becomes more and more online due to the pandemic. But is that a good development, that’s pretty doubtful. Digital makeup started with photography Photo tricks that hide physical problems had already entered our …

The reason synthetic media is becoming an increasingly big online threat is not yet because of cyber-attacks carried out in this way. The growing danger is that the conditions for these attacks are becoming more and more appropriate or introduced at a great speed.  In other words, easily accessible advances in deepfake technologies almost nudge those who can use them with bad intentions. It offers them ready, comfortable, easy opportunities under different legitimate covers. All that remains is to combine artificial intelligence (AI) with demonic intelligence in terms of how the offered deepfake synthetic audio and video generation capabilities can be used for attack, fraud or deceit. Every deadly danger, for those who hold that danger, also becomes a great …

It’s not easy to separate past budget figures into one another. But all the sources reveal that the United States allocates tens of billions of dollars each year to air defense alone. Did all the advanced radar systems, satellite networks, missile shields and fighter jets prevent the tragic September 11 attacks 9 years ago? Unfortunately, no. And that dagger was not hit American cross-border targets, but in the heart of the United States. So, all these investments, technologies have been wasted, are we going to say that it was not necessary? Terrorist attacks carried out by hijacking passenger planes and flying at a low altitude may have caused a very heavy price. But that air defense system, which could not …