Abstract: Detecting malware attacks is described herein. A computer-implemented method may include receiving, via a processor, events from a plurality of activity monitors. The method also include extracting, via the processor, a plurality of behavioral features from the received events. The method may further include detecting, via the processor, a malware attack based on the extracted behavioral features using a malware identification model trained on private data and public data using a machine learning technique, wherein the private data includes private enterprise attack findings. The method may also include executing, via the processor, an ad hoc protection improvement based on the detected malware attack.

Abstract: Detecting malware attacks is described herein. A computer-implemented method may include receiving, via a processor, events from a plurality of activity monitors. The method also include extracting, via the processor, a plurality of behavioral features from the received events. The method may further include detecting, via the processor, a malware attack based on the extracted behavioral features using a malware identification model trained on private data and public data using a machine learning technique, wherein the private data includes private enterprise attack findings. The method may also include executing, via the processor, an ad hoc protection improvement based on the detected malware attack.

Abstract: Detecting malware attacks is described herein. A computer-implemented method may include receiving, via a processor, events from a plurality of activity monitors. The method also include extracting, via the processor, a plurality of behavioral features from the received events. The method may further include detecting, via the processor, a malware attack based on the extracted behavioral features using a malware identification model trained on private data and public data. The method may also include executing, via the processor, an ad hoc protection improvement based on the detected malware attack.

Abstract: Detecting malware attacks is described herein. A computer-implemented method may include receiving, via a processor, events from a plurality of activity monitors. The method also include extracting, via the processor, a plurality of behavioral features from the received events. The method may further include detecting, via the processor, a malware attack based on the extracted behavioral features using a malware identification model trained on private data and public data. The method may also include executing, via the processor, an ad hoc protection improvement based on the detected malware attack.

Abstract: A technique for downloading multiple objects from at least one server in an accelerated manner. Typically, in a TCP/IP environment, a client is limited in the number of sockets that can be opened for a single server. A spoofer (410) is utilized to intercept traffic between the server and the client and modify the traffic so that from the client's perspective, it appears as though objects from a single server are actually being sourced from multiple servers. Thus, the client is able to open additional sockets to receive objects from the server thereby allowing for a parallel download of the objects. This greatly reduces the amount of time necessary to download the objects.

Abstract: A technique for downloading multiple objects from at least one server in an accelerated manner. Typically, in a TCP/IP environment, a client is limited in the number of sockets that can be opened for a single server. A spoofer (410) is utilized to intercept traffic between the server and the client and modify the traffic so that from the client's perspective, it appears as though objects from a single server are actually being sourced from multiple servers. Thus, the client is able to open additional sockets to receive objects from the server thereby allowing for a parallel download of the objects. This greatly reduces the amount of time necessary to download the objects.

Abstract: A technique for downloading multiple objects from at least one server in an accelerated manner. Typically, in a TCP/IP environment, a client is limited in the number of sockets that can be opened for a single server. A spoofer (410) is utilized to intercept traffic between the server and the client and modify the traffic so that from the client's perspective, it appears as though objects from a single server are actually being sourced from multiple servers. Thus, the client is able to open additional sockets to receive objects from the server thereby allowing for a parallel download of the objects. This greatly reduces the amount of time necessary to download the objects.

Abstract: A method for preparing flame retardant thermoplastic nylon compositions comprising incorporating into the thermoplastic nylon a halogenated bisphenol-A epoxy resin having a halogen content of at least 20% and a molecular weight above 8,000 in an amount sufficient to impart flame retardance.