Abstract: The present disclosure relates to a method and system for determining goodness of pricing initiative on a digital platform. Said method comprises: (1) identifying, by a processor [102], a first set of products that are low churn products, brand rule independent products and competition independent products; (2) pre-clustering, by a clustering unit [108], the first set of products to identify pre-clusters such that the products within a pre-cluster are highly correlated products and products in different pre-clusters are independent of each other; (4) clustering, by the clustering unit [108], the pre-clusters based on predefined parameters to identify clusters; and (5) determining, by the processor [102], the goodness of the pricing initiative based at least on a testing of said pricing initiative based on the one first cluster.

Abstract: A system and method for determining a competitiveness value for set(s) of substitutable items. The method comprises determining, a relative demand value of each set from the set(s) of substitutable items based on a normalized demand value of said each set of substitutable items determined for each of a plurality of digital platforms. The method thereafter comprises identifying, a first target digital platform for each set of substitutable items, based on a demand weighted average selling price of said each received set of substitutable items for one or more of the plurality of digital platforms. Further, to determine the competitiveness value, the method comprises identifying, a second target digital platform for the set(s) of substitutable items based on the first target digital platform identified for each set of substitutable items and a relative demand value of said each set of substitutable items.

Abstract: Identifying potential network attacks on servers and protecting the servers from those potential attacks until the associated client requests can be confirmed as either legitimate or an actual attack is disclosed. Client requests for server resources are received by a network traffic management device (NTMD). The NTMD initially responds to the client requests on behalf of the associated servers. The initial responses include client side language scripts for execution by the clients. Executing the scripts causes the clients to resend their initial requests identified as a potential attack by the NTMD along with information indicating the client's legitimacy, such as the result of a computational JavaScript challenge. The NTMD receives the resent initial request, determines it was sent from a legitimate requestor and is therefore not an attack, and forwards it to the associated server.

Abstract: Client requests for server resources are received by a network traffic management device (NTMD). The NTMD initially responds to the client requests on behalf of the associated servers. The initial responses include client side language scripts for execution by the clients. Executing the scripts causes the clients to resend their initial requests identified as a potential attack by the NTMD along with information indicating the client's legitimacy, such as the result of a computational JavaScript challenge. The NTMD receives the resent initial request, determines it was sent from a legitimate requestor and is therefore not an attack, and forwards it to the associate server.

Abstract: A method of inspecting Web elements for real-time classification and detection of Web elements spoofing attempts, according to which trustworthy Web locations are identified for generating a database of safe zones. For each inspected element, it is checked whether or not its top frame URL is included in the database, and if it is included, the element is classified as suspected in Web elements location spoofing attempt.