With rapidly advancing technology comes a huge burden of securing the data systems in the company from the potential cybercrimes. Data, customer information, codes, company revenues, etc. can be accessed by cyber-criminals leading to the loss of millions of dollars in the company. In such cases, cyber security systems have to be stringent and troubleshoot any possible errors before occurring. Reaction quickly and efficiently against cyber attacks is crucial to prevent the loss of vital information and data at the hands of criminals.
In this blog, we talk about how graphs can help in cyber attack analysis and identify potential attack vectors before causing any harm to the company’s data.
How Does the Graph-Based Approach Work?
The graph-based approach in cyber security analysis can scan the patterns of adverse behavior associated with cyber threats such as phishing, data breach, firewall attack, IP spoofing, and more.
- A rigorous cyber security system can unravel these details and patterns in real-time and prevent the leakage of confidential information.
- A graph database can also trace back the error while someone tries to breach your firewall or steal a file. It can detect a specific IP address that tries to breach your cyber security within a few minutes.
- Graph features can also be used to train Artificial Intelligence (AI) to detect and differentiate between normal and abnormal system behavior patterns in real-time.
- Graph databases can analyze and calculate potential risks quickly and provide enough time for rectifying the threat or error.
- The graph-based approach must be paired with VPN connections to add multiple layers of security to the data system. VPN (Virtual Private Network) is the best way to protect your privacy online. It hides crucial information like your identity, location, monetary information, etc., from the hackers or anyone who tries to steal the valuable information.
GRAPH-BASED APPROACH AND ITS IMPORTANCE
Graph-based analysis approaches have been on the rise as one of the most practical tools to evaluate extensive and discrete data sets of businesses, companies, finances, healthcare, and other domains. With cybercrimes on the rise and criminals finding novel ways to perform their crimes, companies must invest in protecting their datasets. Graph databases are ideal for detecting and preventing fraud or cyber-attacks, either from outside an organization or within.
Graph databases are mostly preferred because they include:
- Enormous data analysis – up to terabytes of data generated daily has to be analyzed, for threats and security
- Multi-level data structure – data stored in various services, domains, subdomains, and other organizational hierarchies, need to be examined.
- Multiple data sources – data from log files, infrastructure, user info, and others have to be integrated systematically into the system without any trouble.
- Rapid response time – whatever queries are submitted must receive rapid solutions within seconds.
- Deep-link graph analytics – the next advanced factor in machine learning helps analyze the graph patterns by providing explainable and potential results.
By collaborating with the SaaS security team, the graph-based approach for threat detection can be included for increased data security. Cybersecurity is daunting but crucial in domains like the government, banks, healthcare, education, transportation, smart gadgets, etc. Avantologies’s graph technologies offer fast screening, improved turnaround time, minimize false results, and provide high-quality information about the potential cybercrime.