As the world embarks on a digital journey, several cybersecurity experts are questioning the extent to which the digital landscape has influenced our real lives. With a staggering increase in the similarity that our digital identities have with our real-life personas, many individuals are worried about the ease with which cybercriminals can extract user’s confidential information online.
Moreover, over the course of recent years, as the threat landscape harbors increasingly sophisticated and complex threats- identity theft has risen to the top of the cybercrime totem pole, with its dire influence being felt by thousands, if not millions of innocent people globally.
With the personal data of thousands of individuals at risk, which even includes the monumental danger associated with a cybercriminal gaining access to a user’s financial details and carrying out unauthorized transactions through the stolen information. Along with hackers leveraging confidential data for financial gains, they can also commit a range of crimes, including phishing scams, blackmail/extortion, harassment/threats, along with launching targeted ransomware attacks.
Fortunately, there is still a silver lining to look forward to, which makes itself evident in the form of technologies such as artificial intelligence and machine learning. With the cybersecurity world buzzing with articles about the potential that AI has in virtually revolutionizing the present-day IT landscape, it is high time that companies explore the role that AI can play in combating identity theft.
Although the future for identity theft might seem to be growing bleaker by the second, with the 2019 Official Annual Cybercrime Report citing a 12 percent increase in the number of cyberattacks- not all hope is lost. In an attempt to aid our readers in the fight against identity theft and the cybercriminals that launch these attacks, we’ve compiled an article that explores the potential that AI has in combating identity-based crimes.
What Measures Have Been Taken to Combat Identity Theft So Far?
- 1 What Measures Have Been Taken to Combat Identity Theft So Far?
- 2 How Can AI Aid Cybersecurity Professionals in the Fight Against Identity-Based Crime?
- 3 Concluding Words
As identity theft grows in complexity, the measures that have been utilized in the fight against identity theft have also altered significantly, even more so over the course of the last decade. Previously, companies relied on a more traditional approach to identity theft detection, which had them perform a manual process, with little to no automation.
Typically, going down the traditional route entails a scenario of a specific agent being warned in the instance that the systems pick up any suspicious activity that does not line up with the user’s typical online behavior. These specific agents would then launch an investigation to find out the root cause of the abnormal behavior, along with contacting the user and letting them know that they had been a victim of identity theft.
The most significant issue that makes itself known in the more conventional method of combating identity theft irrelevant in the modern IT landscape is the fact that it is excruciatingly slow. Moreover, since the entire investigative process is manual, it is prone to an arsenal of errors, which enables hackers to circumvent their way into an organization’s infrastructure by using tricks to avoid manual detection.
As time elapsed, however, an increasing number of companies, including several banks and governments have come to the realization that the only way through identity theft can be stopped is by automating as many processes as possible. Furthermore, security analysts also need to account for false positives, which can be extremely annoying for a user to find themselves unable to access their accounts after a slight alteration in their online browsing habits.
How Can AI Aid Cybersecurity Professionals in the Fight Against Identity-Based Crime?
As we’ve already mentioned above, perhaps the most significant step that companies can take is to propagate automation as much as possible- a feat made quite easy to achieve through the amalgamation of AI. In some cases, AI inclusion has gone as far as to replace the need for a human operator entirely.
With that being said, some of the most prevalent ways through which AI aids in the fight against identity theft consist of the following:
#1- Recognizing Suspicious Activity in its Early Stages:
In the traditional method that cybersecurity analysts used to remedy identity theft, the manual nature of the diagnosis of the identity theft led to the crime being recognized, after it had already wreaked damage, and was in its later stages.
Through the inclusion of AI, however, an enterprise’s security team is now equipped with the ability to determine whether they’ve been hit with an identity-based crime, by ‘diagnosing’ while the crime is still in its early stages, that is, before it becomes a massive problem.
Furthermore, with identity-theft being diagnosed in its early stages, companies can act accordingly to ensure that they exercise as many cybersecurity measures as they can to mediate the threat. In addition to enabling a fast-paced response to the threat of identity theft, companies can also leverage the power of AI to reduce the error rate in performing preventative action.
#2- Providing Increasingly Accurate Results and Performance Over Time:
Similar to a majority of analyses being conducted amidst the present-day IT landscape, most insights generated by the inclusion of artificial intelligence into an organization’s infrastructure rely on massive data collection.
With that being said, however, it is extremely important that companies come to terms with this fact, and utilize AI-generated insights’ reliance on big amounts of data to improve accuracy and performance, as time elapses.
In order to achieve the goal of improving accuracy and performance, we’d recommend that companies scrutinize the data that they’re feeding into their AI-centric insights generator. If consistently done over a period of time, the accuracy of the highly valued AI insights can be improved significantly, which typically occurs when companies have access to enough data to learn and harvest information from.
Moreover, companies also need to realize the significance of ensuring that the data from which they’ve generated their insights is valid, fresh and makes sense within the context of the particular company that it’s being used in. Resorting back to outdated data sets might confuse the analytical engine, and set the mediation of identity-based crimes back to what you started with.
#3- Utilizing New AI-Based Methodologies to Combat Identity Theft:
As advances in technology progress at a rapid pace, an organization’s security team can increase their reliance on new AI-based methodologies to combat identity theft. Some of the most popularly implemented models of ID authentication that play a crucial role in protecting an organization from identity-based crimes consist of the following:
Through the process of data mining, security teams scrutinize large (read massive or monumental) databases, and then convert raw data into useful data. What this implies is simple- a larger database of clean data, results in improved performance and more accurate insights.
This recent AI-centric technology makes use of severe scrutiny to test and analyze the results to improve the algorithm being employed by the organization, ultimately increasing efficiency and accuracy.
With this method, security experts utilize unlabeled data for training, and test it for training. Typically, this includes a small amount of labeled data being tested in tandem with unlabelled data to increase efficiency, accuracy and the overall performance of the AI algorithm.
At the end of the article, we’d like to reinstate everything that we’ve stated above, and hope that our readers make use of the tips that we’ve listed, to stay safe from the perils of identity theft!