Law enforcement agencies are facing growing threats due to the ease of access to the Internet, enabling criminals to exploit the social media and the dark web to leverage their activities. Acquiring and analyzing large amounts of data, extracting insights and connecting between all the dots in order to get a complete picture of the crime committed, can be very difficult and time-consuming, even to well-experienced investigators.
Finding the connections among a target’s digital footprints can pave the way to obtaining leads of a well-developed target profile.
The market definition of Threat Intelligence (TI) is evidence-based knowledge – including context, mechanisms, indicators, implications and action-oriented advice about an existing or emerging hazard to IT or information assets. It can be used to inform decisions regarding the subject's response to that menace or hazard.
Most threat intelligence solutions available today rely on a higher level of human effort in order to analyze the vast amounts of data, which tend to be time-consuming and a more expensive pricing model.
Innovative Threat Intelligence solutions have developed through the years, some of which have incorporated unique and advanced technologies such as Artificial Intelligence, Machine Learning, and Image Recognition. This type of technology is a game changer in the TI sphere, moving from the manual human analysis, to full automatization, enabling to attain precision, bring faster insights and extract data from web sources that investigators in many cases cannot access.
Statistics show that by 2020, 15 percent of large enterprises will use commercial TI services to inform of their security strategies, which is an increase from today's less than 1 percent.
Since brand recognition and consumption in the past decade have moved to the digital domain, protecting the digital asset has become a growing challenge.
Data breaches have gained attention with the increasing use of digital files, companies and users’ large reliance on digital data, causing a significant impact on the brand.
Worldwide, identity theft is the most common type of data breach incident, accounting for 59 percent of all global data breach incidents in 2016. The largest data breach to date was uncovered in 2016 after online platform Yahoo announced that hackers stole user information associated with at least 1 billion accounts in 2013. Another Yahoo hack was uncovered only a few months earlier, revealing 500 million compromised data records.
The annual number of data breaches and exposed records in the United States from 2005 to 2018 has increased significantly. Starting from only 157 data breaches in 2005 exposing 66.9 million records, it peaked to 1579 data breaches in 2017, exposing an inconceivable amount of 178.6 million records.
How Can Automated TI Technology Help?
Automated TI technology conducts an automatic search that reveals anonymous targets details, targeting your brand and business performance, it analyzes objectives, groups, and locations. It can also detect data breaches by monitoring darknet marketplaces for stolen data and also monitor your situational awareness on the open, deep and dark web, a task that a human is incapable of performing accurately and in real time. The most sophisticated solutions can even predict various actions such as attempts to deceive customers with impersonating domain registrations, users’ intentions, etc. Technologies that use Natural Language Processing enable investigators to understand content sentiments and context, even in foreign languages.
When considering the risks to a brand correlated with these “brand jackers,” one could be very overwhelmed. Nevertheless, planning the right strategy and prioritizing brand protection within the organization can significantly reduce the impact resulting from impersonating acts, fraud and stolen web traffic. Organizations that implement strategies for mitigating these risks, can easily prevent damage to their customers, increase a long-term relationship while positioning their brand in a healthier, higher level and bring positive ROI to the brand.
Analysts’ reports conclude that protecting a brand reputation and preserving customer loyalty, should be based on real-time social media, domain, and mobile marketplace monitoring from all web sources: open, deep and dark web.
When preparing a risk strategy, one should plan a method to discover all news and posts related to the asset or brand from around the web, understand the context in which the assets are mentioned and evaluate the sentiments in the related discussions – if they are positive, negative or just neutral. The strategy should enable avoiding a brand crisis in case of negative mentioning or fake news and track the results of your remediation efforts.
Government agencies and the private sector use web intelligence technologies in order to identify and develop target profiles, map groups, and cover their investigations from end-to-end under time constraints. They use these technologies in order to gain situational awareness and control events with ease, and moreover, predict and respond to threats instantly.
Some investigations are more complex, as their leads are don’t necessarily reside in the same country and they often need to search data and analyze links from global web sources that include social links and even data from un-indexed, hidden content or private websites. The advantage of not having to employ a technical analyst around the clock in order to keep track of evolving situations and entities, saves on expenses and the constant need to be alert, instead, using the automated TI solutions enable the investigators to focus on the important aspects of the investigation while being fed with alerts only with the crucial evidence.
When a digital asset is at stake, and the growing sophistication of challenges alienate professionals from preventing damage to the brand, the Artificial Intelligence incorporated with technologies such as Natural Language Processing, Face Detection and Recognition, Pattern Recognition, OCR and Predictive Analysis leverage investigations and demonstrate a unique advantage from all other solutions.
Udi Levy is the CEO of Cobwebs Technologies