Hi,i am writing blogs for our platform House of Bots on Artificial Intelligence, Machine Learning, Chatbots, Automation etc after completing my MBA degree. ...Full Bio
Hi,i am writing blogs for our platform House of Bots on Artificial Intelligence, Machine Learning, Chatbots, Automation etc after completing my MBA degree.
Python Opens The Door For Computer Programming
How Cyber-Security Will Be Benefited By Data Science?
As cyber threats continue to evolve, data Science and machine learning are increasingly necessary for a strong cyber security strategy. Data science is the field which includes processes and systems to extract knowledge and insights from data in various forms, which is a continuation of data analysis fields as statistics, data mining, and predictive analysis.
Data science continues to improve and advance the cyber security concerns. Data science helps the cybersecurity field to protect against attacks and identify the abnormal behavior. The idea is to leverage a platform that aggregates and manages big data, and to combine this with a machine learning algorithm that analyzes this data to uncover hidden patterns and detect threats out of it.
In cybersecurity, the goal should be to identify threats, stop intrusions and attacks, identify malware and spam, and prevent fraud. Data from a wide range of samples is used to detect malware and spam. The goal should also be to identify anomalies and abnormalities in user behavior that caused by an intruder and take preventative measures to stop the intrusion from getting severe.
Following are some of the ways cybersecurity can be benefited by data science:
Statistical methodology: The Statistical methodology is one of the parts of data science which uses mathematical models and techniques for statistical analysis of raw data. It extracts information from research data and provides various ways to assess the robustness of research outputs. The methodology is able to detect unusual behavior against statistical models of normality.
Predictive analysis: Predictive analysis predicts future by using numerous techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data. Cybercriminals constantly try to create innovative models and algorithms for cyber-attacks. Data scientists are able to break this stalemate by having insights into data provided by predictive analysis.
Critical framework for cybersecurity: The potential of data science is on hype, to cover this up, National Institute of Standard and Technology came up with a new framework or concept to incorporate data science into security. There are some aims behind this to achieve and to follow the objective.
Risk identification and assessment of consequences: Organizations usually evaluate their assets based on the probability of cyber-attack. By figuring out the consequences of the attack the organizations should equip to develop appropriate models and action plans.
Intrusion detection: Organizations should develop a data-based system that identifies problems within the system of network, and trigger a quick response.
Response to intrusion: Data scientists should use their expertise to process and utilize information from an event of a data breach. The information helps them to analyze the effectiveness of the response and solution of the breach.
Hacking is an evolving threat, and nobody knows what form it takes. But the advancements of data science promise ro all organisations to address their cybersecurity concerns.