Cyber Attacks have been a major concern for the software security industry since the beginning of the internet. What cyber attack means is an attempt by hackers to damage, destroy, or steal data from a computer network or system, making it a big threat to a smooth computing experience.
Now, as long as these attacks are taking place, in most cases, they can be detected. Detecting cyber attacks is a big necessity for the security of every legitimate user within a system. So it has been through a lot of work and improvements over these years. Some most common methods are signature scan and anomaly detection.
The limitation with these approaches, however, is that we have to let the attack happen first, then apply countermeasures, leaving the system vulnerable.
Do you remember the futuristic thriller film “Minority Report”? It had an idea that fascinated and also made us concerned a lot of us for the days to come. Predicting and preventing crime before it takes place. Interestingly enough, this particular type of crime prediction is also seeing a turn towards reality with the help of artificial intelligence. Predicting real-world crimes with the help of Artificial Intelligence might also be a thing sooner than we can think.
While we can’t use their “psychic” technology as it is bound to be fiction, the attack patterns and motives for the cyberattacks into the depths of the internet might just be straightforward enough to predict a lot of them.
It’s a technology that’s still in its infancy, and a lot of research and developments are being needed to be and will be conducted. Researchers around the world have devised multiple ways to predict cyber attacks. Let’s discuss two promising ones.
Social media Data analysis for cyber attack prediction
To understand this, first of all, we need to know what a dataset is. A dataset is a collection of data that can be analyzed and manipulated by a computer. For example, a collection of MRI scans of tumors can be a dataset. And with the help of machine learning, we can find patterns in the dataset, leading us to decide if a patient has cancer or not. Given enough relevant data and a good machine learning or deep learning model we can teach a computer to solve problems that were never even thought to be possible before. Predicting cyberattacks falls right in that alley.
A recent research paper of 2017 about predicting cyberattacks with social media data came up with a plan to use a bunch of news articles. They extracted the core keywords from those articles and applied a machine learning technique called artificial neural network. The mechanism of how neural networks work vaguely mimics our brain activity, with neuron-like nodes connected with each other, passing signals as numbers with each other until a satisfactory output comes up, it’s a long process. However, that process can lead us to find correlations between a news article and a cyber attack. In short, if any news vaguely points to a direction of potential cyber-attack, this approach will help us prepare for it.
Recommendation engine to cyber-attack prediction
We see recommendation systems everywhere nowadays. From suggesting what movie might trigger your fancy on Netflix to buying something on Amazon, they’re pretty much everywhere. They suggest products, services, information to us based on analysis of data like previous purchases or preference of like-minded users. What’s interesting is that this kind of recommendation suggestion mechanism can be a viable tool for predicting cyberattacks too.
Recommender systems meeting security: From product recommendation to cyber–attack prediction is a research paper that explains how to make this happen.
There are a handful more methods of prediction, like Predicting cyberattack rates with extreme values, game-theoretic approach, CAPTURE, etc. It’s pretty obvious that a lot of research and works are being conducted for this particular piece of technology. Unfortunately, there is not much information about the industry-level works available to the public.
There’s a cybersecurity company called RiskAware that has been developing its CyberAware Predict capability, which uses scan-based network attack surface predictions in an interactive operational graphics dashboard. This work has also led to a collaboration with the University of Southampton to incorporate real-time alerts and predictions about the next steps of an evolving attack.
This combined capability is currently undergoing testing in a virtualized military environment. Once complete, the capability will allow cyber protection teams to rapidly observe and predict cyberattacks. This same approach is additionally applicable to enterprise networks. With this capability in place, businesses too can stay one step ahead of those who would seek to compromise their networks.
There is a common catchphrase that goes like “If you make a better lock, along comes a better lock picker.” So, while this ever-raging war between cybercriminals and security providers might not reach any conclusion, this piece of tech is sure to bring a new line of defense. The future is exciting.
For now, you can get a glance at the cybersecurity measurements we take at nascenia.
Contributor: Istiaq Salam Siaam