Cybersecurity has always been a topic of much concern because of the wide array of risk factors involved. An adequately coordinated cyber attack can bring about chaos to an organization in the form of loss and suffering. More than ever, right now, because of the lockdowns the risk of cyber-attacks is higher. Due to the massive number of remote employees, it is extremely difficult for an organization to manage these remote servers. It is now easy for hackers and thieves to target an individual in order to gain greater access.
In terms of techniques, cyber crimes are diverse to a high degree. Which makes it humanly impossible to detect a crime before happening. The response to the threat is machine learning(ML). ML grants the ability to calculate with a greater degree of efficiency and predict the menace even before happening. Even for undetected zero-hour incidents machine learning can alleviate the damage to an extent.
This discussion will concentrate on examples of areas, where machine learning excels as a weapon against cybercrime.
Detection of phishing
Phishing is the most popular if not the most utilized technique for fetching sensitive information. Phishing is performed with the help of deception. Fraudulence is presented as legitimate for phishing operations in order to gain the target’s trust. Often a malicious link is used for guiding a target to certain inconvenience.
Predictive URL identification(PUI) is the key to the solution for phishing. For PUI, powerful machine learning algorithms are deployed in order to predict malicious communications. These tools enjoy the freedom of analyzing the email body and links for detecting danger.
Preventing watering hole attack
There are a few real-world predators who wait near a watering hole for their prey. In synchrony with the nomenclature, the hacking technique utilizes a similar principle of trapping users. Sometimes the hackers tend to infect a particular server or website in order to target a similar group of individuals in terms of access to the knowledge of desire. For targeting individual users a particular server or website is targeted for trapping the likely group of visitors.
Way traversal discovery algorithms are utilized for neutralizing the threat of watering hole-style attacks. This versatile machine learning tool can detect the possibility of watering hole traps by analyzing the suspicious patterns of diverting designs.
Detection and prevention of ransomware
Ransomware is a program built to sabotage the system of a server or computer. If there is an attempt by the user for accessing the full potential of a system, the program demands a fee for the same. But the ransomware can not infiltrate a private network just like that. It disguises itself as a trusted source and the user is tricked to accept the intrusion. The program then gradually takes over the system and destroyed the promise of convenient performance.
Ransomware can be designed to steal multiple user records including workspace details and media records, machine learning can effectively prevent ransomware by efficient prediction and calculated prevention methods.
A few lines or characters of code can be hidden in a website or server in order to play a game of deception. The program is known to alter the internet root catalog of a website or server. By this method, private and sensitive data can be revealed based on the type of victim website. For instance, in the case of e-commerce websites, card and bank information can be fetched along with purchase history. Additionally, the purchase history can be utilized for targeted marketing in an unethical manner.
Given the cybersecurity threats, we are facing every other day, the need for efficient defense is on the rise. The lockdowns contributed to increasing the numbers of remote workers rendering the managing process way more difficult. These remote servers are the weakest link in a collective server and are targeted for multiple jacking operations. The hackers tend to target individuals in order to gain access to the hist server, exposing it to greater threats.
People from IT and CSE backgrounds might find it easy to utilize machine learning tools for managing defense and security with greater efficacy. But the need for professionals specializing in the same is going to by the day in front of overwhelming threats. A direct recommendation will be to opt for a machine learning certification in order to contribute to the process. Additionally, due to the involvement of massive risks, at-work training should be considered before taking up professional responsibilities.