ENHANCING SECURE INTERNET FINANCIAL TRANSACTIONS THROUGH MULTI-FACTOR AUTHENTICATION AND MACHINE LEARNING

Abstract

Enhancing Secure Internet Financial Transactions through Multi-Factor Authentication and Machine Learning is the proposed invention. The proposed invention focuses on understanding the functions of Multi-Factor Authentication. The invention focuses on analyzing the parameters of Secure Internet Financial Transaction using algorithms of Machine Learning Approach.

Specification

Description:[0001] Background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0002] Machine learning (ML) is a subset of artificial intelligence (AI) that allows systems to learn and improve themselves using data. Machine learning (ML) systems use algorithms and data to learn how humans learn and improve their accuracy over time. They can be trained to perform tasks like identifying spam in emails. Machine learning (ML) systems can analyze data to make predictions, classifications, and decisions.
[0003] A number of different types of techniques for analysing secure online transactions that are known in the prior art. For example, the following patents are provided for their supportive teachings and are all incorporated by reference.
[0004] US20140189808A1: Embodiments are directed to a system and method for authenticating a user of a client computer making a request to a server computer providing access to a network resource through an authentication platform that issues a challenge in response to the request requiring authentication of the user identity through a reply from the client computer, determining one or more items of context information related to at least one of the user, the request, and the client computer, and determining a disposition of the request based on the reply and the one or more items of context information. The reply includes a user password and may be provided by an authorizing client device coupled to the client computer over a wireless communications link.
[0005] Multi-factor authentication (MFA) is a security measure that requires users to provide more than one form of identification to access an account. It's also known as two-step verification. MFA is designed to make it more difficult for unauthorized users to access accounts and data. It can help prevent account access if a user's password is compromised. MFA can help organizations improve trust, reduce costs, and make logins easier. The proposed invention focuses on analyzing the Secure Internet Financial Transaction through algorithms of Machine Learning Approach.
[0006] Above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, no assertion is made, and as to whether any of the above might be applicable as prior art with regard to the present invention.
[0007] In the view of the foregoing disadvantages inherent in the known types of techniques for analyzing secure online transactions now present in the prior art, the present invention provides an improved system. As such, the general purpose of the present invention, which will be described subsequently in greater detail, is to provide a new and improved techniques for enhancing Secure Internet Financial Transactions through Multi-Factor Authentication and Machine Learning that has all the advantages of the prior art and none of the disadvantages.
SUMMARY OF INVENTION
[0008] In the view of the foregoing disadvantages inherent in the known types of techniques for analysing secure online transactions now present in the prior art, the present invention provides an improved one. As such, the general purpose of the present invention, which will be described subsequently in greater detail, is to provide a new and improved techniques for enhancing Secure Internet Financial Transactions through Multi-Factor Authentication and Machine Learning which has all the advantages of the prior art and none of the disadvantages.
[0009] The Main objective of the proposed invention is to design & implement a framework of Machine Learning techniques for analyzing the parameters of Secure Internet Financial Transaction. Secure Internet Financial Transactions is analyzed.
[0010] Yet another important aspect of the proposed invention is to design & implement a framework of Machine Learning techniques that will consider on understanding the functions of Multi-Factor Authentication. Secure Internet Financial Transactions is analyzed by predictive unit. The results of prediction are displayed on the display unit.
[0011] In this respect, before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not limited in its application to the details of construction and to the arrangements of the components set forth in the following description or illustrated in the various ways. Also, it is to be understood that the phraseology and terminology employed herein are for the purpose of description and should not be regarded as limiting.
[0012] These together with other objects of the invention, along with the various features of novelty which characterize the invention, are pointed out with particularity in the disclosure. For a better understanding of the invention, its operating advantages and the specific objects attained by its uses, reference should be had to the accompanying drawings and descriptive matter in which there are illustrated preferred embodiments of the invention.
BRIEF DESCRIPTION OF DRAWINGS
[0013] The invention will be better understood and objects other than those set forth above will become apparent when consideration is given to the following detailed description thereof. Such description makes reference to the annexed drawings wherein:
Figure 1 illustrates the schematic view of Enhancing Secure Internet Financial Transactions through Multi-Factor Authentication and Machine Learning, according to the embodiment herein.
DETAILED DESCRIPTION OF INVENTION
[0014] In the following detailed description, reference is made to the accompanying drawings which form a part hereof, and in which is shown by way of illustration specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, and it is to be understood that the embodiments may be combined, or that other embodiments may be utilized and that structural and logical changes may be made without departing from the spirit and scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined by the appended claims and their equivalents.
[0015] While the present invention is described herein by way of example using several embodiments and illustrative drawings, those skilled in the art will recognize that the invention is neither intended to be limited to the embodiments of drawing or drawings described, nor intended to represent the scale of the various components. Further, some components that may form a part of the invention may not be illustrated in certain figures, for ease of illustration, and such omissions do not limit the embodiments outlined in any way. It should be understood that the drawings and detailed description thereto are not intended to limit the invention to the particular form disclosed, but on the contrary, the invention covers all modification/s, equivalents and alternatives falling within the spirit and scope of the present invention as defined by the appended claims. The headings are used for organizational purposes only and are not meant to limit the scope of the description or the claims. As used throughout this description, the word "may" be used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Further, the words "a" or "a" mean "at least one" and the word "plurality" means one or more, unless otherwise mentioned. Furthermore, the terminology and phraseology used herein is solely used for descriptive purposes and should not be construed as limiting in scope. Language such as "including," "comprising," "having," "containing," or "involving," and variations thereof, is intended to be broad and encompass the subject matter listed thereafter, equivalents, and any additional subject matter not recited, and is not intended to exclude any other additives, components, integers or steps. Likewise, the term "comprising" is considered synonymous with the terms "including" or "containing" for applicable legal purposes. Any discussion of documents, acts, materials, devices, articles and the like are included in the specification solely for the purpose of providing a context for the present invention.
[0016] In this disclosure, whenever an element or a group of elements is preceded with the transitional phrase "comprising", it is understood that we also contemplate the same element or group of elements with transitional phrases "consisting essentially of, "consisting", "selected from the group consisting of", "including", or "is" preceding the recitation of the element or group of elements and vice versa.
[0017] A financial transaction is an agreement or communication between a buyer and seller to exchange goods, services, or assets for payment. Financial transactions can involve the transfer of money, securities, or other assets, and can occur between individuals, businesses, or governments. Financial transactions can be conducted in a variety of ways, including through cash, checks, credit cards, wire transfers, and electronic payments.
[0018] Secure Internet Financial Transactions are financial transactions that are protected using security measures to ensure the safety of sensitive information and the transfer of customer data. These measures include Secure Electronic Transaction (SET), Transport Layer Security (TLS), Multi-factor authentication (MFA) and Digital signatures. Other ways to make secure online transactions include Keeping all software current with automatic updating, Installing legitimate antivirus and antispyware software, Never turning off your firewall and etc. The proposed invention focuses on implementing the algorithms of Machine Learning for studying the functions of Multi-Factor Authentication.
[0019] Reference will now be made in detail to the exemplary embodiment of the present disclosure. Before describing the detailed embodiments that are in accordance with the present disclosure, it should be observed that the embodiment resides primarily in combinations arrangement of the system according to an embodiment herein and as exemplified in FIG. 1
[0020] Figure 1 illustrates the schematic view of Enhancing Secure Internet Financial Transactions through Multi-Factor Authentication and Machine Learning 100. The proposed invention 100 includes a various online transaction system 101 for analysis purposes. The payment gateway 105 is connected to the cloud server 102. The machine learning unit 103 will run the predictive algorithm 104 will predict for any interrupts in the transaction. The encryption unit 106 will work along with predictive unit to avoid fake and erroneous transactions.
[0021] In the following description, for the purpose of explanation, numerous specific details are set forth in order to provide a thorough understanding of the arrangement of the system according to an embodiment herein. It will be apparent, however, to one skilled in the art that the present embodiment can be practiced without these specific details. In other instances, structures are shown in block diagram form only in order to avoid obscuring the present invention.
, Claims:1. Enhancing Secure Internet Financial Transactions through Multi-Factor Authentication and Machine Learning, comprises of:
Machine learning unit;
Predictive unit and
Encryption unit.
2. Enhancing Secure Internet Financial Transactions through Multi-Factor Authentication and Machine Learning, according to claim 1, includes a machine learning unit, wherein the machine learning unit will run predictive algorithm.
3. Enhancing Secure Internet Financial Transactions through Multi-Factor Authentication and Machine Learning, according to claim 1, includes an encryption unit, wherein the encryption unit will work along with predictive unit to avoid fake and erroneous transactions.
4. Enhancing Secure Internet Financial Transactions through Multi-Factor Authentication and Machine Learning, according to claim 1, includes a predictive unit, wherein the predictive unit will predict for any interrupts in the transaction.

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