The ubiquitous role of Artificial Intelligence requires no proof. Where the digital era has observed a continuous surge, AI and cybersecurity go hand in hand.
If you want to know why? You must know that with the increased use of virtual platforms, the probability of cyber-attacks has also seen an upward gush. There are technological and legal complexities that have heightened cybersecurity threats.
Numerous organizations that earlier were aware of cyber threats, but did not have enough measures to curb them have now implemented unshakeable measures to mitigate cyber threats. In this process, AI has been a boon owing to its potential of recognizing malicious and malware codes along with anomalies that reduce the risk of any such cyber breach.
What are the Challenges to Cybersecurity?
Before we perceive the solutions, we must know the core problems associated with cybersecurity. These threats below are the common ways used by hackers to steal vital corporate data, especially for those who work from home. In fact, as reported by the FBI there has been a fourfold increase in cybersecurity complaints and global losses due to cybercrime exceeding $1 trillion in 2020.
- Refined hacking systems by changing IP addresses
The use of Virtual Private Networks (VPN), Tor Browsers, and proxy servers to advance the hacking system has been on a rise. Using these enables the hackers to remain undetected.
Unauthorized access to a computer or a system is the malware’s way of accessing data that is otherwise crucial. This attack on the vital information available on the system is done through malicious software that is introduced through various methods. These are disguised as legitimate code as malware attaches itself to legal software appearing as genuine.
The user unknowingly introduces them by clicking on the option of downloading. This opens the way for the malware to access the information. This data is then used to launch cyber attacks. The cyberattacks give access to the very secret information leading to precarious consequences and sometimes dissolving big companies with large turnovers. Some examples of malware are Trojans, viruses, and worms.
- Attacks on the server
One of the most notable ways of cyberattacks is on the server. Performed through the Distributed Denial of Service attacks, known as DDoS— numerous attacks on the server are performed by sending repeated requests on the same server so that ultimately the server crashes. This is done under the jurisdiction of the hackers who target one server enabling it to crash. The process is called Memcached that further enhances the requests to the servers.
- Data Misuse
Misuse of data by the employees by leaking secured information to sources that may use it for their personal interest. Several employees who for their personal benefit often sell the data to public sources which are in turn misused. This sometimes also leads to mixing personal and business passwords.
Solutions to Overcome the Challenges
With advanced technology, some solutions help overcome challenges. Machine learning and the use of predictive analytics is the best way to overcome data intrusion and breach of security.
Using Machine Learning, artificial intelligence and cybersecurity methods to predict when the cyberattack is about to occur, the IT in charge should be able to realize and take corrective action. This can be easily done using ML and AI and cybersecurity can be prevented. Cybersecurity measures using predictive analysis (which should be the security protocol in all companies) will prevent the data to be misused. This protocol if not applied in time the data can be consistently misused owing to the breach.
- Data Back-Up
A backup strategy that involves solutions for effective data prevention is a must. There are many platforms that provide various solutions for secure remote access, especially during Covid-19 when every company is operating from home. This saves the data and minimizes the downtime of the companies. This increases the overall efficiency of the employees and they remain focused. This is most useful in the case of DDoS and Ransomware when servers are attacked. The companies must aim at keeping the service uptime at the maximum so the risk is compensated.
- Deploying Deep Learning Neural Networks and AI-based Network-Monitoring Tools
Deep learning neural networks and AI monitoring tools can be deployed to create algorithms that target the ‘DNA’ of malware and other cyber threats. The presence of these enables active self-defence ensuring the detection and replication of digital antibody functions. Once detected and identified, the threats or viruses are neutralized. Similarly, when AI detects a user’s daily work, it can easily detect anomalies and prevent threats.
- Behavioral Analytics
ML and AI algorithms can identify a user’s behaviour. Everyday activities of a user are tracked and when AI detects unusual activity, it flags it and eventually prevents it. This can be exercised during e-commerce activities, where traits like differences in typing speed, or changes in the number of orders can be suspicious and can be flagged to prevent frauds.
- Password Protection
Using artificial intelligence and cybersecurity measures to develop biometric authentication is an accurate way to prevent hackers from cracking the password. Although biometrics scanners are used in physical offices, for work from home, these need to be more refined and advanced. Thus, adding AI algorithms to biometrics increases efficiency exponentially. Just like some organizations use ‘Face ID’, similar identification tools that are empowered with infra-red sensors, neural engines, aiding recognition and proffering a sound technology.
With a real mark of the pre and post-digital world, widespread advantages have been offered. However, there is a price we pay to manoeuvre the advantages. Balancing its use and exercising its precedence needs to be supervised and AI and ML together with their monitoring tools can righteously do this. In fact, it is said that the cyber insurance market is likely to raise $20 billion by 2025.
Cloud threats and Phishing being the most popular threats, each email received for business and as a customer must be scanned and analyzed before reverting and disclosing details. These details are significant and confidential which can be easily done through AI and cybersecurity operations.