Poisoned AI: A Threat to Cyber Security
The growing trend of Artificial Intelligence (AI) shows how important and mainstream position is taking in the business, marketing, and other industries. AI is used for the detection of faces, credit worthiness, and prediction of weather.
Moreover, the combination of AI and cyber security is unavoidable. Both can impact each other in many ways. Both fields also are on the lookout for better tools and techniques for better working. These efforts are prone to be disrupted when they bypass the threats and risks without being able to detect the problem or issues.
Manipulation of information happens through machine learning. It offers to make a way around the AI that enables threats or issues to go undetected. This whole thing or trend creates quite a challenge. It means it is difficult to be able to make cyber security intact. The global market for cyber security is also expected to increase manifold by the year 2028. The amount of market share is expected to be 35 billion. Moreover, it is needed that all the cyber security companies and their clients work together. And devise new strategies that enable them to be able to keep the business safe and eliminate the cyber risks and threats.
Machine learning is called to be a subset of artificial intelligence. Data manipulation and poisoning, target the machine learning aspect. It helps them to ease the process. As computers have heaps of data. They can identify, collect and categorize the information accurately. Computers draw inferences from the information. It doesn’t know the exact answers. But they reach it based on the past data.
For example, if anybody is searching for a particular dog. Like German shepherds. Then the AI will not only give pictures of dogs. But it will be able to provide exact breed results in the form of images through machine learning. The same approach of machine learning is used by cyber security companies. They feed their systems with the data so that they can catch the malicious software.
These cyber security companies use the advanced technique as well. It is called a neural network. It is said to be inspired by the human brain. This technique does not need to have seen a particularly bad code. But they can know themselves by learning. It enables them to differentiate between the good and the bad codes. And protect the system from cyber risks.
Good and correct prediction requires a huge number of samples. That is correctly labeled. It is said that even the biggest cyber security companies can categorize limited data. So one can also crowdsource the data. It increases their scope of the sample and increases the chances of detecting the malware.
But there is a risk in such a situation as well that professional hackers can manipulate such data by labeling the data incorrectly. It makes them able to keep away the cyber security companies from the detection of cyber threats. An example of this data poisoning by the hacker is if anyone wants to see pictures of sloths. But they will get the pictures of kittens instead as hackers had incorrectly labeled the pictures as kittens.
It shows how the hackers poison the data for the cyber security companies by using malicious codes and then labeling them as well. It makes the cyber security company unable to identify the cyber risks and gets into much fraud and loss.
At the security conference in Taipei last year, Cheng Shin-Ming and Tseng Ming-Huei presented their information and knowledge. That the machine learning system is still vulnerable to cyber threats and risks. As small amounts of data poisoning can make it harder for cyber security to track the issue. They specifically said 0.7% of data poisoning can do the work of hackers. It shows how crucial it is for the safety of the business.
Tips to Prevent Data Poisoning
This knowledge of the potential of data poisoning makes the cyber security companies work more diligently for the security of the businesses and their data. Following are some tips. That can work for the cyber security companies to avoid data poisoning:
- Scientists should keep a regular check whether all the labels of the data are accurate or not. As an Open AI LLP does the regular checking with special filters. That removes anything that is wrongly labeled in the data. It eliminates the chances of cyber risks. Thus, correct labeling avoids a lot of confusion.
- Moreover, companies should keep their data clean as much as possible. It allows them to be confident about their data. They don’t go for open-sourced data as it increases the chances of cyber risk. They train the machine learning system with a few examples. As the sample size is an essential factor for the machine learning system.
- Keep on the lookout for the possibility of hacker interventions. In every new technology or trend. It makes you proactive in saving the data before a cyberattack.
Thus avoiding data poisoning is an essential need of cyber security management. It shows this competition between the cyber security companies and hackers has been going on for so many years. AI is one of the important tools that enable the cyber security companies to get solutions. But it does not mean that there is no risk of hackers with AI. One should always be proactive to detect any such cyber risks from hackers.