Preventive medicine has long been recognized as an essential approach to preserving our physical health. We take a variety of tests and assessments so doctors can discover key biological markers that can indicate the potential development of certain diseases or conditions as early as possible.
Cybercrime in the digital world also has distinctive characteristics, and we can respond to cyberattacks by neutralizing the source. As phishing attacks increase in frequency and sophistication and are carried out by a whole new breed of cybercriminals, it’s time we used the latest technologies to anticipate threats before they spread.
A digital contagion
Smartphones are increasingly targeted by hacking attempts, especially since the pandemic, with the total number of phishing attacks in Q2 2022 reaching over one million. Makes sense: Smartphones are our main connection to our digital endpoints – social media, email, apps, SMS, etc. – and the sophistication of today’s phishing criminals means that even the most active and knowledgeable users can fall prey to attacks. This has made cybercrime big business and a huge drain on public funds. Making even a small dent in it will be a huge win for businesses and consumers alike.
Behavioral profiling to identify every potential hack
Future threats need an equal match. A guaranteed way to prevent and neutralize threats at an unprecedented level is to anticipate their movement, design and presentation. Just as clinicians assess diseases in the human body, cybersecurity professionals are tasked with creating software that can not only diagnose untrusted websites, messages, or emails, but also predict areas of vulnerability. and concern. This type of technology would use behavioral algorithms to identify phishing attempts in real time and actively protect users against known and unknown malicious attacks. Dynamic detection should not only anticipate the behavior of long-established sites, but also be ready and prepared to detect and repel newly developed sites; a website is created, suspicion markers are found and its access attempts are blocked.
Enabling wholesale security for mobile phones requires more than reflective analysis – we need to capture data on a user’s device and model an algorithm based on behavior and interaction – predict malicious sites and protect against them an user. Combine that with URL blacklisting and whitelisting, and you have a comprehensive machine learning tool that can analyze live threats more accurately than ever before. It’s the cybersecurity equivalent of a doctor ordering a complete blood count: if there’s something that shouldn’t be there, the algorithm will pick it up. There will always be a need for built-in human replacement capability, but if there are enough safeguards built in before that, then we can be sure that we are making the right decisions.
Compiling data from many websites helps build an accurate profile of a site with malicious intent. Typical things to look out for may include slightly inconsistent logos or branding from the actual releases, messaging inaccuracies, spelling mistakes, negative reviews of a site, and site traffic patterns. The data derived from these instances informs the kind of real-time automated technology that will focus not only on building a list of markers that raise suspicion, but also on reducing the volume of threats that get through in the first place. This behavioral, science-based piracy prevention tool would be invaluable to individuals and businesses alike and would finally begin to truly level the playing field between consumers and scammers.
Take advantage of human error
In 2022, we are dealing with a different breed of hackers. They don’t just target suboptimal phone security or take advantage of exploitable systems – they understand the end user (you and me). They know how we think and what we will do.
Like an alien entity exploiting a weakened immune system, the hacker strikes at our most vulnerable point. They know that 82% of data breaches are caused by human error and that many people have become addicted to their phones, and they design scams that exploit these vulnerabilities. Every minute on the phone – whether a user takes a quick look, browses social media, opens an email or message, or confirms a purchase – activates switches or fuses that allow or prevent current from malicious content.
Here is an example. A message is sent via email or SMS regarding supposed suspicious activity detected and requires an immediate response from the user to confirm if they are the source of this activity. It’s the urgency in this case that shortens our decision-making – which, by the way, is made much more difficult on a phone’s small screen, as we can’t clearly see the full URL or the sender details. One regrettable click later and we’ve invited the hacker into our lives, bypassing small talk and polite conversation and allowing them to invade our privacy.
In this case, mobilizing a behavioral algorithm would ensure that a message is flagged as “phishy” before it reaches the user. Maybe the communication is written inconsistently, maybe the font is unusual, or the wording is inconsistent with the company it’s supposed to come from. Just as an irregular heartbeat or high blood pressure would reveal important information to a doctor about a patient’s well-being, the countless digital markers available to the algorithm would tell the user that clicking on a link or responding to this message could be an error. movement.
Beat the odds
How we as businesses and consumers react to cyberattacks depends on how dangerous we think the attack is. According to a recent PWC survey, at least 78% of 722 U.S. executives surveyed consider cybersecurity the #1 business risk – rather than a technology risk – and as a result, cyber threats are no longer solely the domain of the CISO.
This is part of the solution: properly assign ownership to deal with the threat, then arm businesses or individuals with the digital arsenal to fight back. It’s damning that nearly 80% of organizations don’t have a cybersecurity incident response plan, and most companies take almost six months to detect a data breach. It is the environment that emboldens pirates and allows them to thrive, making their fight an uphill battle.
In terms of target, just like viruses looking for a human host, hackers don’t discriminate: small businesses, large corporations, and individuals are all at risk.
In an ideal world, organizations would train their employees to be aware of cyber risks and have the appropriate solutions to combat them, and individuals would recognize malicious sources almost by reflex. However, this takes time and a major shift in mindset, so more than anything we need to deploy technology that can detect, decode and everything else.