Mayur Rele Explains Machine Learning Role In Cybersecurity
The growing dependency on I.O.T(Internet of Things) has attracted Cyber criminals who lay traps to unsuspecting users in order to gain unauthorized access to confidential data like passwords, bank details, emails and all sort of information they could get. The incidents are increasing exponentially proportionate to the growth in digital space. There is a corporate laxity on security investments compared to rolling out new applications and software’s. Therefore, Personal and Corporate data is vulnerable to malware attacks, zero-day attacks, denial of service, social engineering and phishing attacks.
Cyber Security
The concept involves technologies and processes aimed at protecting computer systems, networks or programs from unprecedented access or attack. Cybercrime is a threat to both organizations and individuals, many have lost money from their accounts and when that happens it adversely affects the organizational credibility. To curb this, AI (Artificial Intelligence, data Science and Machine Learning comes in handy to provide applications and tools which are secure, and with a capacity to detect and eliminate such threats in advance.
Data Science
In Artificial intelligence is the processing of organizational data to come up with technical suggestions to eliminate real-time cyber-attacks. Data Science focuses on security data to provide insights on possible threats previously seen or unseen which is in turn used to optimize security measures.
While A.I, Machine Learning and Data Science covers a wider scope in technology, they can be very significant in providing security over the Internet. They are coming in to provide a paradigm shift on the way security solutions are implemented. The Cyber space is rapidly evolving rendering the traditional ways of ensuring security like firewalls, user authentication and access control obsolete.
These technologies do computational statistics, data mining and analytics to enable the system learn previous events and come up with solutions to detect and prevent future occurrences. The process involves analyzing large volumes of data and developing reasonable comparisons to identify the past, present and anticipate future trends.
Mayur Rele, cyber security expert and cloud automation leader, explain the AI And Machine Learning in Cybersecurity. Scientific methods are applied to identify the sequence and patterns of occurrence and provide intelligence and insights to understand and analyze the actual phenomena by use of Machine Learning Techniques. A set of rules and methodologies are used to identify data patterns by monitoring behaviors and providing intelligent solutions to prevent future occurrences.
Machine Learning Methodologies
Supervised learning — this is the use of specific targets by classification of tasks to identify specific inputs to be utilized in the analysis and development of solutions.
Unsupervised Learning — the approach targets unlabeled data to learn behaviors and identify patterns from a cluster of dynamic data which keeps on changing to avoid detection. Clustering techniques helps to identify hidden data patterns which helps in identifying sophisticated attacks.
Deep Learning- this is computational model inspired by neural networeks from the human brain. It performs its functions through a multi-layer feed forwards neural network with an input layer, one or several hidden layers and an output layer. Mayur Rele believes Deep learning performs well in large volumes of data-sets.
To mitigate the contemporary security threats, it is a prudent measure to aggressively integrate A.I in our security systems.
Originally Posted at: https://mygentec.com/security/machine-learning-improves-cybersecurity/
