Field
Embodiments of the present invention generally relate to access of resources over a computer network. In particular, embodiments of the present invention relate to retrieval and evaluation of client reputation (CR) score of a user and assigning policies to the user for accessing network resources based on the CR score.
Description of the Related Art
In a network such as a computing network or a telecommunication network that is coupled to resources such as computers, laptops, mobiles, Personal Digital Assistants (PDAs), virtual server, virtual machines, widgets, among other computing devices, the resources are generally susceptible to hostile attacks arising as a result of malicious objects such as malware, web robots or BOTS, phishing, modified virus codes, and other viruses. Global networks, such as the Internet, when coupled with the ability of remote access, increase the vulnerability of corporate data, the risk of information leaks, the risk of unauthorized document access and the disclosure of confidential information, the risk of fraud, and also the risk of attacks on privacy. Such malicious objects may contaminate the resources and initiate risky activities in the network such as bad connection attempts, file sharing applications, session initiation for incoming connections, and so forth. Therefore, a resource contaminated with one or more malicious objects may be considered as a malicious resource for the network. At the time, it would also be appreciated that it is often the case that vulnerability of a resource depends on the actions that a user takes while communicating with external resources. For instance, the extent, manner, and mode of access to websites, portals, and applications that have high likelihood of causing threat to a resource is proportional to an actual attack that might take place on the resource.
Such malicious resources may further contaminate other resources that are operatively coupled with each other in the network. For instance, if a user, using a first computing device, is connected to other users over a local area network (LAN), the probability of computing devices of such other users being attacked by malware, virus codes, among others is likely to increase in case the first computing device is affected by such network level threats or attacks, and therefore detecting, evaluating, and appropriately handling the first computing device becomes a top priority.
Employees are among the greatest threats to an organization's information security and also significantly responsible for network level threats that an organization faces for its resources. Employees, with access to information resources including email, the Internet, and on-line networks, significantly increase the security risks, making it extremely important to proactively monitor the kind of data that employees share through multiple messaging platforms or try to access or receive from external networks, and accordingly take necessary measures to prevent any potential misuse of information or exposure of internal resources to the outside networks.
Setting appropriate, flexible, and robust security policies is a recommended method for creating order and for setting standards for network use. However, most existing techniques for setting security policies are not individual user based and largely apply the policies to the entire organization at large. Such techniques also do not take into account each user's network access behavior and rather take departments or groups of employees as a whole and implement network access policies on them based on the organizational requirements. Such policies, as a result, do not evaluate the condition of each internal resource/computing device, its pattern of network access, files accessed, network activity, external resource violations, and its vulnerability to network attacks, among other parameters for setting network access policies and hence are loosely implemented.
In view of the foregoing, there is therefore a need for new and more effective techniques for assigning appropriate network policies to users based on their reputation scores, which is computed based on network level activities and activities/interactions of the users.