DESC:FIELD OF INVENTION
[0001] The embodiments of the present disclosure generally relate to systems and techniques for fingerprinting of devices. More specifically, the disclosure relates to providing fingerprinting of devices behind an internal router.

BACKGROUND OF THE INVENTION
[0002] The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
[0003] In today’s world, in a home network, we can fingerprint devices directly connected to the Optical Network Termination (ONT) via WiFi/Ethernet. However, understanding about other devices which are connected behind an internal router is not easy. In current implementation, the fingerprinting agent would be getting entries for each device connected behind a router, but it would keep overwriting its entry based on user traffic since it does one to one mapping for a device and its MAC address.
[0004] For example, a router may be identified as a smart phone with hostname of both phone and router giving wrong fingerprint information to a user and thus miss out on capturing such devices in the database. as This is very common topology in Homes with a large surface area where you need to connect an additional router to extend your home network’s reachability.
[0005] There is therefore a need in the art to provide a system and a method that can facilitate mitigating the problems associated with the prior art.

OBJECTS OF THE PRESENT DISCLOSURE
[0006] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.
[0007] It is an object of the present disclosure to identity multiple user agents and single mac address.
[0008] It is an object of the present disclosure to apply any policy on all the devices behind the internal router that will be applied on the internal router.
[0009] It is an object of the present disclosure to help both customer and an entity to identify devices in the network.

SUMMARY
[0010] This section is provided to introduce certain objects and aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.
[0011] In an aspect, the present disclosure provides for a system for fingerprinting a plurality of computing devices in a network. The system may include an user equipment operatively coupled to a first network and a second network. In an embodiment, the first network may be operatively coupled to a plurality of first computing devices and the second network, the second network may be further coupled to a plurality of second computing devices. In an embodiment, the user equipment may include one or more processors coupled with a memory, the memory storing instructions which when executed by the one or more processors may cause the user equipment to receive a first set of data packets pertaining to device metadata of each first computing device. In an embodiment, each first computing device may be operatively coupled to the first network. In an embodiment, the user equipment may be configured to receive a second set of data packets pertaining to device metadata of each second computing device, each second computing device may be further operatively coupled to the second network. In an embodiment, the user equipment may be configured to extract a first set of attributes from the first set of data packets, the first set of data packets pertaining to device details and a predefined set of instructions of each said first computing device and the second network and further extract a second set of attributes from the second set of data packets, the second set of data packets pertaining to device details and the predefined set of instructions of each said second computing device. Based on the first set of attributes, the user equipment may be configured to identify each said first computing device and the second network and generate, a one-to-many mapping of each second computing device to the first network. Based on the one-to-many mapping, the user equipment may identify and fingerprint each second computing device.
[0012] In an embodiment, the predefined set of instructions applied on the second network may be applied on the plurality of second computing devices behind the second network.
[0013] In an embodiment, the predefined set of instructions may include website filtering, time of day limits, safe browsing and blocking of a first computing device or a second computing device.
[0014] In an embodiment, the user equipment may be further operatively coupled to a dashboard configured to display one or more details of the identified and finger printed first computing devices and the second computing devices.
[0015] In an embodiment, the user equipment may be coupled to a set of databases to store device meta data of each first computing device (102) and second computing device (106) and one or more networks.
[0016] In an embodiment, the user equipment may be configured to update the predefined set of instructions based on one or more changes in one or more first computing device and one or more second computing devices.
[0017] In an embodiment, the user equipment may be configured to detect a new connection associated with a new computing device being connected to the first network or the second network.
[0018] In an embodiment, the user equipment may be configured to update the dashboard based on the new connection detected.
[0019] In an aspect, the present disclosure provides for a method for fingerprinting a plurality of computing devices in a network. The method may include the step of receiving, by an user equipment, a first set of data packets pertaining to device metadata of each first computing device. In an embodiment, user equipment operatively coupled to a first network and a second network. In an embodiment, the first network may be operatively coupled to a plurality of first computing devices and the second network, the second network may be further coupled to a plurality of second computing devices. In an embodiment, the user equipment may include one or more processors coupled with a memory, the memory storing instructions which may be executed by the one or more processors. The method may further include the step of receiving, by the user equipment, a second set of data packets pertaining to device metadata of each second computing device operatively coupled to the second network. The method may further include the step of extracting, by the user equipment, a first set of attributes from the first set of data packets, the first set of data packets pertaining to device details and a predefined set of instructions of each first computing device and the second network and the step of extracting, by the user equipment, a second set of attributes from the second set of data packets, the second set of data packets pertaining to device details and the predefined set of instructions of each second computing device. The method further may include the step of identifying, by the user equipment, each first computing device and the second network based on the first set of attributes and the step of generating, by the user equipment, a one-to-many mapping of each second computing device to the first network. Based on the one-to-many mapping, the method may include the step of identifying and fingerprinting, by the user equipment, each second computing device.
[0020] In an aspect, the present disclosure provides for an user equipment for fingerprinting a plurality of computing devices in a network. The device may include may include one or more processors operatively coupled to a first network and a second network. In an embodiment, the first network may be operatively coupled to a plurality of first computing devices and the second network, the second network may be further coupled to a plurality of second computing devices. In an embodiment, the one or more processors may be coupled with a memory, the memory storing instructions which when executed by the one or more processors may cause the user equipment to receive a first set of data packets pertaining to device metadata of each first computing device. In an embodiment, each first computing device may be operatively coupled to the first network. In an embodiment, the user equipment may be configured to receive a second set of data packets pertaining to device metadata of each second computing device, each second computing device may be further operatively coupled to the second network. In an embodiment, the user equipment may be configured to extract a first set of attributes from the first set of data packets, the first set of data packets pertaining to device details and a predefined set of instructions of each said first computing device and the second network and further extract a second set of attributes from the second set of data packets, the second set of data packets pertaining to device details and the predefined set of instructions of each said second computing device. Based on the first set of attributes, the user equipment may be configured to identify each said first computing device and the second network and generate, a one-to-many mapping of each second computing device to the first network. Based on the one-to-many mapping, the user equipment may identify and fingerprint each second computing device.

BRIEF DESCRIPTION OF DRAWINGS
[0021] The accompanying drawings, which are incorporated herein, and constitute a part of this invention, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present invention. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that invention of such drawings includes the invention of electrical components, electronic components or circuitry commonly used to implement such components.
[0022] FIG. 1 illustrates an exemplary network architecture in which or with which the system of the present disclosure can be implemented for facilitating enhanced conference call, in accordance with an embodiment of the present disclosure
[0023] FIG. 2 illustrates an exemplary representation of system based on an artificial intelligence (AI) based architecture, in accordance with an embodiment of the present disclosure
[0024] FIG. 3 illustrates exemplary method flow diagram for fingerprinting a plurality of devices in a network, in accordance with an embodiment of the present disclosure.
[0025] FIG. 4 illustrates an exemplary block flow diagrams depicting components of the system involved in the fingerprinting of a plurality of devices in a network, in accordance with an embodiment of the present disclosure.
[0026] FIG. 5 illustrates a generic flow diagram of implementations of exemplary fingerprinting of devices, in accordance with an embodiment of the present disclosure.
[0027] FIG. 6 illustrates another flow diagrams of implementations of exemplary fingerprinting of devices, in accordance with an embodiment of the present disclosure.
[0028] FIG. 7 refers to the exemplary computer system in which or with which embodiments of the present invention can be utilized, in accordance with embodiments of the present disclosure.
[0029] The foregoing shall be more apparent from the following more detailed description of the invention.

DETAILED DESCRIPTION OF INVENTION
[0030] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0031] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth.
[0032] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.
[0033] The present invention provides a robust and effective solution to an entity or an organization by enabling the entity to implement a system for fingerprinting a plurality of computing devices in a network. Thus, the system and method of the present disclosure may be beneficial for both entities and users.
[0034] Referring to FIG. 1 that illustrates an exemplary network architecture (100) in which or with which system (110) of the present disclosure can be implemented, in accordance with an embodiment of the present disclosure. As illustrated in FIG. 1, by way of example and not by not limitation, the exemplary architecture (100) may include a plurality of first computing devices (102-1, 102-2…102-N) (collectively referred to as first devices (102) and individually as first device (102)) associated with a first network (104-1). One or more second computing devices (106-1, 106-2..106-N) (collectively referred to as second devices (106) and individually as second device (106)) may further be coupled to the first network (104-1) (also referred to as the router herein) and at least a second network (104-2) (also referred to as the internal router herein), at least a centralized server (112) and at least a third computing device (114) associated with an entity (116). More specifically, the exemplary architecture (100) includes a system (110) equipped with an artificial intelligence (AI) engine (214) (not shown in FIG. 1) for fingerprinting the plurality of first computing devices (102) in the first network (104-1). The second computing device (106) may be communicably coupled to the centralized server (112) through the second network (104-2) to facilitate communication therewith. As an example, and not by way of limitation, the second computing device (106) may be operatively coupled to the centralised server (112) through the second network (104-2) and may be associated with the entity (116).
[0035] In an exemplary embodiment, the system (110) may be coupled to the third computing device (114) (interchangeably referred to as the User equipment (114)) that may identity the plurality of second computing devices (106) and single mac address. The user equipment (114) may be configured to receive a first set of data packets pertaining to device metadata of each first computing device (102) and receive a second set of data packets pertaining to device metadata of each second computing device (106). The user equipment (114) may then extract a first set of attributes from the first set of data packets, the first set of data packets pertaining to device details and a predefined set of instructions of each first computing device (102) and the second network (104-2) and further extract a second set of attributes from the second set of data packets, the second set of data packets pertaining to device details and the predefined set of instructions of each second computing device (106).
[0036] In an embodiment, the predefined set of instructions applied on the second network (104-2) may be applied on the plurality of second computing devices (106) behind the second network (104-2). The predefined set of instructions may include policies, website filtering, time of day limits, safe browsing and blocking of a first computing device (102) or a second computing device (106).
[0037] In an embodiment, based on the first set of attributes, the user equipment (114) may be configured to identify each first computing device (102) and the second network (104-2) and generate, a one-to-many mapping of each second computing device (106) to the first network (104-1). Based on the one-to-many mapping, the user equipment (114) may be configured to identify and fingerprint each second computing device (106). For example, the devices identification behind the second network (104-2) will be using device’s HTTP traffic but not limited to it.
[0038] In an embodiment, the user equipment (114) may be further operatively coupled to a dashboard configured to display one or more details of the identified and finger printed first computing devices (102) and the second computing devices (106). The user equipment (114) may be further coupled to a set of databases (420) to store device meta data of each first computing device (102) and second computing device (106) and one or more networks.
[0039] In an embodiment, the user equipment (114) may be configured to update the predefined set of instructions based on one or more changes in one or more first computing device (102) and one or more second computing devices (106). If one or more new devices are connected to the first network or the second network (104-2), the user equipment (114) may be configured to detect one or more new connections associated with the new devices being connected to the first network (104-1) or the second network (104-2). The user equipment (114) may then be configured to update the dashboard based on the new connection detected.
[0040] In an embodiment, the first computing device (102), the second computing device (106) and the user equipment (114) may communicate with the system (110) via set of executable instructions residing on any operating system, including but not limited to, Android TM, iOS TM, Kai OS TM and the like. In an embodiment, the first computing device (102), the second computing device (106) and the user equipment (114) may include, but not limited to, any electrical, electronic, electro-mechanical or an equipment or a combination of one or more of the above devices such as mobile phone, smartphone, virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device, wherein the computing device may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as camera, audio aid, a microphone, a keyboard, input devices for receiving input from a user such as touch pad, touch enabled screen, electronic pen and the like. It may be appreciated that the first computing device (102), the second computing device (106) and the user equipment (114) may not be restricted to the mentioned devices and various other devices may be used. A smart computing device may be one of the appropriate systems for storing data and other private/sensitive information.
[0041] In an exemplary embodiment, a network (104) such as the first network (104-1) and the second network (104-2) may include, by way of example but not limitation, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. A network may include, by way of example but not limitation, one or more of: a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a public-switched telephone network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, a router, some combination thereof.
[0042] In another exemplary embodiment, the centralized server (112) may include or comprise, by way of example but not limitation, one or more of: a stand-alone server, a server blade, a server rack, a bank of servers, a server farm, hardware supporting a part of a cloud service or system, a home server, hardware running a virtualized server, one or more processors executing code to function as a server, one or more machines performing server-side functionality as described herein, at least a portion of any of the above, some combination thereof.
[0043] In an embodiment, the system (110) may include one or more processors coupled with a memory, wherein the memory may store instructions which when executed by the one or more processors may cause the system to facilitate detection of active participants. FIG. 2 with reference to FIG. 1, illustrates an exemplary representation of system (110) for facilitating enhanced conference call based on an artificial intelligence (AI) based architecture, in accordance with an embodiment of the present disclosure. In an aspect, the system (110) may comprise one or more processor(s) (202). The one or more processor(s) (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that process data based on operational instructions. Among other capabilities, the one or more processor(s) (202) may be configured to fetch and execute computer-readable instructions stored in a memory (206) of the system (110). The memory (204) may be configured to store one or more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory (204) may comprise any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0044] In an embodiment, the system (110) may include an interface(s) 206. The interface(s) 206 may comprise a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 206 may facilitate communication of the system (110). The interface(s) 206 may also provide a communication pathway for one or more components of the system (110). Examples of such components include, but are not limited to, processing engine(s) 208 and a database (210).
[0045] The processing engine(s) (208) may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) (208). In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) (208) may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) (208) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) (208). In such examples, the system (110) may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system (110) and the processing resource. In other examples, the processing engine(s) (208) may be implemented by electronic circuitry.
[0046] The processing engine (208) may include one or more engines selected from any of a data acquisition engine (212), an artificial intelligence (AI) engine (214), and other engines (216).
[0047] In an embodiment, the data acquisition engine (212) may be configured to receive a first set of data packets pertaining to device metadata of each first computing device (102) and a second set of data packets pertaining to device metadata of each second computing device (106).
[0048] In an embodiment, the AI engine (214) may be configured to extract a first set of attributes from the first set of data packets, the first set of data packets pertaining to device details and a predefined set of instructions of each first computing device (102) and the second network (104-2) and further extract a second set of attributes from the second set of data packets, the second set of data packets pertaining to device details and the predefined set of instructions of each second computing device (106).
[0049] In an embodiment, based on the first set of attributes, the AI engine (214) may be configured to identify each first computing device (102) and the second network (104-2) and generate, a one-to-many mapping of each second computing device (106) to the first network (104-1). Based on the one-to-many mapping, the AI engine (214) may be configured to identify and fingerprint each second computing device (106).
[0050] FIG. 3 illustrates exemplary method flow diagram (300) for enhancing spatial conference call, in accordance with an embodiment of the present disclosure. At 302, the method may include the step of receiving, by an user equipment (114), a first set of data packets pertaining to device metadata of each first computing device (102), and at 304, the step of receiving, by the user equipment (112), a second set of data packets pertaining to device metadata of each second computing device (106), wherein each said second computing device is operatively coupled to the second network (104-2).
[0051] The method (300) may further include at 306, the step of extracting, by the user equipment (112), a first set of attributes from the first set of data packets, the first set of data packets pertaining to device details and a predefined set of instructions of each first computing device (102) and the second network (104-2) and at 308, the step of extracting, by the user equipment (112), a second set of attributes from the second set of data packets, the second set of data packets pertaining to device details and the predefined set of instructions of each second computing device.
[0052] The method (300) further may include at 308, the step of identifying, by the user equipment (112), each first computing device (102) and the second network (104-2) based on the first set of attributes and at 310, the step of generating, by the user equipment (112), a one-to-many mapping of each second computing device (106) to the first network (104-1).
[0053] Based on the one-to-many mapping, the method may include at 314, the step of identifying and fingerprinting, by the user equipment (112), each second computing device (106).
[0054] FIG. 4 illustrates an exemplary block flow diagrams depicting components of the system involved in the fingerprinting of a plurality of devices in a network, in accordance with an embodiment of the present disclosure. As illustrated, the components of the system may include user centred elements (402), CSP core elements (404), external elements (406). The user centred elements (402) may further include connected device (408), CPE Agent (410), mobile app (412) and the like. The CSP core elements (404) may include Frontend API (414), message bus (416), backend consumer (418), while the external elements (406) may include a set of databases (420). The user centred elements, may include at 422 the step of pairing to routers and at 424, reporting device meta data at 424, publishing data at 430, passing data at 434, querying local cache queries remote DB at 438 by the CSP core elements, and at step 442 answering consumers by the external elements, updating details at 440. The user centred elements (402) may further at 426 send meta data, and at 428, reporting metadeta. Publishing data at 432, passing data at 436, updating local cache update remote DB at step 444, passing data at 448, collecting all data at step 450 at the CSP core elements (404) gathering information from the user at 452. At step 454 displaying all device details. The updated local cache update remote DB at step 444 may be stored data to improve database at step 446.
[0055] FIG. 5 illustrates a generic flow diagram of implementations of exemplary fingerprinting of devices for getting the devices, in accordance with an embodiment of the present disclosure. As illustrated, in an aspect, an endpoint of getting the devices may be invoked by the router to fetch the list of devices and the policy assigned to each of them so it can be enforced. Policy includes website filtering, time of day limits, safe browsing and blocking of the device. At step 502, new device connected from a connected device, at 504, device metadeta is then reported, and at 506, getting device details from mobile application at 508, all device details (type and name) may be obtained from a frontend API at step 510. From CPE Agent, get devices information at step 512, getting all device policies from the frontend API at 514 and at 516, update device policies and at 518 set device policies. At 520, get devices information and at 522 get all device policy information and return device policies to the CPE agent at 524. When a new connection is received from the connected device at 526 then at 528, all device policies may be enforced.
[0056] FIG. 6 illustrates another flow diagrams of implementations of exemplary fingerprinting of devices of posting devices, in accordance with an embodiment of the present disclosure. As illustrated, in an aspect, an endpoint of posting the devices may be invoked by the router to update on changes to devices connected to the router. This can be caused by a new device connected to the network, or new data (e.g. new identified user-agent) that can be used for device identification/fingerprinting. At step 602, new device connected from a connected device, at 604, device metadeta is then reported from a CPE Agent, and at 606, a frontend API may publish data on a message bus. At 608, the data from the bus may be consumed by a backend consumer after which a mobile application at 610, analyze the data looking for cached devices. The backend consumer at 612 may then try to resolve with external or third part services. And then at 614, update device details accordingly. At step 616, new device metadata is received from the connected device, at the CPE Agent. At 618, device metadeta is then reported from the CPE Agent, and at 620, the frontend API may publish the data on the message bus. At 622, the data from the bus may be consumed by a backend consumer after which a mobile application at 624, send previous details and new ones to improve previous detection. And then at 626, update device details accordingly. At 628, getting device details from the mobile application to the frontend API. Getting all device information at 630 and at 632 all device details (type and name) to the mobile application.
[0057] FIG. 7 illustrates an exemplary computer system in which or with which embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure. As shown in FIG. 7, computer system 700 can include an external storage device 710, a bus 720, a main memory 730, a read only memory 740, a mass storage device 750, communication port 760, and a processor 770. A person skilled in the art will appreciate that the computer system may include more than one processor and communication ports. Examples of processor 770 include, but are not limited to, an Intel® Itanium® or Itanium 2 processor(s), or AMD® Opteron® or Athlon MP® processor(s), Motorola® lines of processors, FortiSOC™ system on chip processors or other future processors. Processor 770 may include various modules associated with embodiments of the present invention. Communication port 760 can be any of an RS-232 port for use with a modem based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. Communication port 760 may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which computer system connects. Memory 730 can be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. Read-only memory 740 can be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or BIOS instructions for processor 770. Mass storage 750 may be any current or future mass storage solution, which can be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), e.g. those available from Seagate (e.g., the Seagate Barracuda 7102 family) or Hitachi.
[0058] Bus 720 communicatively couples processor(s) 770 with the other memory, storage and communication blocks. Bus 720 can be, e.g. a Peripheral Component Interconnect (PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), USB or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects processor 770 to software system.
[0059] Optionally, operator and administrative interfaces, e.g. a display, keyboard, and a cursor control device, may also be coupled to bus 720 to support direct operator interaction with a computer system. Other operator and administrative interfaces can be provided through network connections connected through communication port 760. The external storage device 710 can be any kind of external hard-drives, floppy drives, IOMEGA® Zip Drives, Compact Disc - Read Only Memory (CD-ROM), Compact Disc-Re-Writable (CD-RW), Digital Video Disk-Read Only Memory (DVD-ROM). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[0060] The present disclosure provides an efficient and unique solution for for fingerprinting and identifying a plurality of computing devices in a network. Thus, the system and method of the present disclosure may be beneficial for both entities and users.
[0061] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the invention. These and other changes in the preferred embodiments of the invention will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter to be implemented merely as illustrative of the invention and not as limitation.

ADVANTAGES OF THE PRESENT DISCLOSURE
[0062] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.
[0063] The present disclosure provides a system to identity multiple user agents and single mac address.
[0064] The present disclosure provides a system to apply any policy on all the devices behind the internal router that will be applied on the internal router.
[0065] The present disclosure provides a system to help both customer and an entity to identify devices in the network.
,CLAIMS:1. A system (110) for fingerprinting a plurality of computing devices (102, 106) in a network (104), said system comprising:
an user equipment (114), said user equipment (114) operatively coupled to a first network (104-1) and a second network (104-2), wherein the first network (104-1) is operatively coupled to a plurality of first computing devices (102) and the second network (104-2), wherein the second network (104-2) is further coupled to a plurality of second computing devices (106), wherein said user equipment (114) comprises one or more processors (202) coupled with a memory (204), the memory (204) storing instructions which when executed by the one or more processors, causes the user equipment (114) to:
receive a first set of data packets pertaining to device metadata of each first computing device (102), wherein each said first computing device is operatively coupled to the first network (104-1);
receive a second set of data packets pertaining to device metadata of each second computing device (106), wherein each said second computing device is operatively coupled to the second network (104-2);
extract a first set of attributes from the first set of data packets, the first set of data packets pertaining to device details and a predefined set of instructions of each said first computing device (102) and the second network (104-2);
extract a second set of attributes from the second set of data packets, the second set of data packets pertaining to device details and the predefined set of instructions of each said second computing device;
based on the first set of attributes, identify each said first computing device (102) and the second network (104-2);
generate, a one-to-many mapping of each said second computing device (106) to the first network (104-1); and,
based on the one-to-many mapping, identify and fingerprint each said second computing device (106).
2. The system as claimed in claim 1, wherein the predefined set of instructions applied on the second network (104-2) will be applied on the plurality of second computing devices (106) behind the second network (104-2).
3. The system as claimed in claim 2, wherein the predefined set of instructions includes website filtering, time of day limits, safe browsing and blocking of a first computing device (102) or a second computing device (106).
4. The system as claimed in claim 1, wherein the user equipment (114) is further operatively coupled to a dashboard configured to display one or more details of the identified and finger printed first computing devices (102) and the second computing devices (106).
5. The system as claimed in claim 1, wherein the user equipment (114) is coupled to a set of databases (420) to store device meta data of each first computing device (102) and second computing device (106) and one or more networks.
6. The system as claimed in claim 1, wherein the user equipment (114) is configured to update the predefined set of instructions based on one or more changes in one or more first computing device (102) and one or more second computing devices (106).
7. The system as claimed in claim 1, wherein the user equipment (114) is configured to detect a new connection associated with a new computing device being connected to the first network (104-1) or the second network (104-2).
8. The system as claimed in claim 7, wherein the user equipment (114) is configured to update the dashboard based on the new connection detected.
9. A method (300) for fingerprinting a plurality of computing devices (102, 106) in a network (104), said method (300) comprising:
receiving, by an user equipment (114), a first set of data packets pertaining to device metadata of each first computing device (102), wherein each said first computing device is operatively coupled to a first network (104-1), wherein said user equipment (114) is operatively coupled to the first network (104-1) and a second network (104-2), wherein the first network (104-1) is operatively coupled to a plurality of first computing devices (102) and the second network (104-2), wherein the second network (104-2) is further coupled to a plurality of second computing devices (106), wherein said user equipment (114) comprises one or more processors (202) coupled with a memory (204), the memory (204) storing instructions executed by the one or more processors;
receiving, by the user equipment (112), a second set of data packets pertaining to device metadata of each second computing device (106), wherein each said second computing device is operatively coupled to the second network (104-2);
extracting, by the user equipment (112), a first set of attributes from the first set of data packets, the first set of data packets pertaining to device details and a predefined set of instructions of each first computing device (102) and the second network (104-2);
extracting, by the user equipment (112), a second set of attributes from the second set of data packets, the second set of data packets pertaining to device details and the predefined set of instructions of each second computing device;
based on the first set of attributes, identifying, by the user equipment (112), each said first computing device (102) and the second network (104-2);
generating, by the user equipment (112), a one-to-many mapping of each said second computing device (106) to the first network (104-1); and,
based on the one-to-many mapping, identifying and fingerprinting, by the user equipment (112), each said second computing device (106).
10. The method as claimed in claim 9, wherein the predefined set of instructions applied on the second network (104-2) will be applied on the plurality of second computing devices (106) behind the second network (104-2).
11. The method as claimed in claim 10, wherein the predefined set of instructions includes website filtering, time of day limits, safe browsing and blocking of a first computing device (102) or a second computing device (106).
12. The method as claimed in claim 9, wherein the method further comprises the step of:
displaying one or more details of the identified and fingerprinted first computing devices (102) and the second computing devices (106) on a dashboard operatively coupled to the user equipment (114).
13. The method as claimed in claim 9, wherein the user equipment (114) is coupled to a set of databases (420) to store device meta data of each first computing device (102) and second computing device (106) and one or more networks.
14. The method as claimed in claim 9, wherein the method further comprises the step of:
updating, by the user equipment (114), the predefined set of instructions based on one or more changes in one or more first computing device (102) and one or more second computing devices (106).
15. The method as claimed in claim 9, wherein the method further comprises the step of:
detecting, by the user equipment (114) a new connection associated with a new computing device being connected to the first network (104-1) or the second network (104-2).
16. The method as claimed in claim 7, wherein the method further comprises the step of:
updating, by the user equipment (114), the dashboard based on the new connection detected.
17. An user equipment (114) for fingerprinting a plurality of computing devices (102) in a network (106), said device comprising:
one or more processors (202) operatively coupled to a first network (104-1) and a second network (104-2), wherein the first network (104-1) is operatively coupled to a plurality of first computing devices (102) and the second network (104-2), wherein the second network (104-2) is further coupled to a plurality of second computing devices (106), wherein said one or more processors (202) coupled with a memory (204), the memory (204) storing instructions which when executed by the one or more processors, causes the user equipment (114) to:
receive a first set of data packets pertaining to device metadata of each first computing device (102), wherein each said first computing device is operatively coupled to the first network (104-1);
receive a second set of data packets pertaining to device metadata of each second computing device (106), wherein each said second computing device is operatively coupled to the second network (104-2);
extract a first set of attributes from the first set of data packets, the first set of data packets pertaining to device details and a predefined set of instructions of each said first computing device (102) and the second network (104-2);
extract a second set of attributes from the second set of data packets, the second set of data packets pertaining to device details and the predefined set of instructions of each said second computing device;
based on the first set of attributes, identify each said first computing device (102) and the second network (104-2);
generate, a one-to-many mapping of each second computing device (106) to the first network (104-1); and,
based on the one-to-many mapping, identify and fingerprint each said second computing device (106).
18. The device as claimed in claim 17, wherein the predefined set of instructions applied on the second network (104-2) will be applied on the plurality of second computing devices (106) behind the second network (104-2), wherein the predefined set of instructions includes website filtering, time of day limits, safe browsing and blocking of a first computing device (102) or a second computing device (106).
19. The device as claimed in claim 17, wherein the user equipment (114) is further operatively coupled to a dashboard configured to display one or more details of the identified and finger printed first computing devices (102) and the second computing devices (106).
20. The system as claimed in claim 1, wherein the user equipment (114) is configured to detect a new connection associated with a new computing device being connected to the first network (104-1) or the second network (104-2), wherein the user equipment (114) is further configured to update the dashboard based on the new connection detected.