Abstract: A cable barrier assembly or system can include line posts extending along a barrier section. Cables can extend along the line posts. In addition, each line post can have a total number of cable retention features that is less than a total number of the cables. Each cable retention feature can include at least a partial loop that limits a range of radial motion of a cable extending through an eye of the partial loop, relative to an axis of the cable.

Abstract: Methods and apparatus for optimizing security configurations of a set of computers are disclosed. A set of local servers, each functioning as a deep-security manager supporting a respective subset of the computers, maintains protection software containing filters and rules for deploying each filter. A local server receives updated protection software from a central server. Each local server interrogates each computer of its subset of computers to acquire computer-characterizing data and applies relevant rules to determine an optimal set of filters for each computer. Each rule adaptively determines required characterizing data elements from each computer for determining an optimal security configuration. A local server updates the security configuration of a computer to suit changes in the operational environment of the computer.

Abstract: Methods and apparatus for optimizing security configurations of a set of computers are disclosed. A set of local servers, each functioning as a deep-security manager supporting a respective subset of the computers, maintains protection software containing filters and rules for deploying each filter. A local server receives updated protection software from a central server. Each local server interrogates each computer of its subset of computers to acquire computer-characterizing data and applies relevant rules to determine an optimal set of filters for each computer. Each rule adaptively determines required characterizing data elements from each computer for determining an optimal security configuration. A local server updates the security configuration of a computer to suit changes in the operational environment of the computer.

Abstract: Methods and apparatus for optimizing security configurations of a set of computers are disclosed. A set of local servers, each functioning as a deep-security manager supporting a respective subset of the computers, maintains protection software containing filters and rules for deploying each filter. A local server receives updated protection software from a central server. Each local server interrogates each computer of its subset of computers to acquire computer-characterizing data and applies relevant rules to determine an optimal set of filters for each computer. Each rule adaptively determines required characterizing data elements from each computer for determining an optimal security configuration. A local server updates the security configuration of a computer to suit changes in the operational environment of the computer.

Abstract: Methods and apparatus for optimizing security configurations of a set of computers are disclosed. A set of local servers, each functioning as a deep-security manager supporting a respective subset of the computers, maintains protection software containing filters and rules for deploying each filter. A local server receives updated protection software from a central server. Each local server interrogates each computer of its subset of computers to acquire computer-characterizing data and applies relevant rules to determine an optimal set of filters for each computer. Each rule adaptively determines required characterizing data elements from each computer for determining an optimal security configuration. A local server updates the security configuration of a computer to suit changes in the operational environment of the computer.

Abstract: Methods and apparatus for optimizing security configurations of a set of computers are disclosed. A set of local servers, each functioning as a deep-security manager supporting a respective subset of the computers, maintains protection software containing filters and rules for deploying each filter. A local server receives updated protection software from a central server. Each local server interrogates each computer of its subset of computers to acquire computer-characterizing data and applies relevant rules to determine an optimal set of filters for each computer. Each rule adaptively determines required characterizing data elements from each computer for determining an optimal security configuration. A local server updates the security configuration of a computer to suit changes in the operational environment of the computer.

Abstract: Methods and apparatus for optimizing security configurations of a set of computers are disclosed. A set of local servers, each functioning as a deep-security manager supporting a respective subset of the computers, maintains protection software containing filters and rules for deploying each filter. A local server receives updated protection software from a central server. Each local server interrogates each computer of its subset of computers to acquire computer-characterizing data and applies relevant rules to determine an optimal set of filters for each computer. Each rule adaptively determines required characterizing data elements from each computer for determining an optimal security configuration. A local server updates the security configuration of a computer to suit changes in the operational environment of the computer.

Abstract: Methods and apparatus for optimizing security configurations of a set of computers are disclosed. A set of local servers, each functioning as a deep-security manager supporting a respective subset of the computers, maintains protection software containing filters and rules for deploying each filter. A local server receives updated protection software from a central server. Each local server interrogates each computer of its subset of computers to acquire computer-characterizing data and applies relevant rules to determine an optimal set of filters for each computer. Each rule adaptively determines required characterizing data elements from each computer for determining an optimal security configuration. A local server updates the security configuration of a computer to suit changes in the operational environment of the computer.

Abstract: An intrusion prevention/detection system filter (IPS filter) performance evaluation is provided. The performance evaluation is performed at both the security center and at the customer sites to derive a base confidence score and local confidence scores. Existence of new vulnerability is disclosed and its attributes are used in the generation of new IPS filter or updates. The generated IPS filter is first tested to determine its base confidence score from test confidence attributes prior to deploying it to a customer site. A deep security manager and deep security agent, at the customer site, collect local confidence attributes that are used for determining the local confidence score. The local confidence score and the base confidence score are aggregated to form a global confidence score. The local and global confidence scores are then compared to deployment thresholds to determine whether the IPS filter should be deployed in prevention or detection mode or sent back to the security center for improvement.

Abstract: Methods and apparatus for optimizing security configurations of a set of computers are disclosed. A set of local servers, each functioning as a deep-security manager supporting a respective subset of the computers, maintains protection software containing filters and rules for deploying each filter. A local server receives updated protection software from a central server. Each local server interrogates each computer of its subset of computers to acquire computer-characterizing data and applies relevant rules to determine an optimal set of filters for each computer. Each rule adaptively determines required characterizing data elements from each computer for determining an optimal security configuration. A local server updates the security configuration of a computer to suit changes in the operational environment of the computer.

Abstract: Methods and apparatus for optimizing security configurations of a set of computers are disclosed. A set of local servers, each functioning as a deep-security manager supporting a respective subset of the computers, maintains protection software containing filters and rules for deploying each filter. A local server receives updated protection software from a central server. Each local server interrogates each computer of its subset of computers to acquire computer-characterizing data and applies relevant rules to determine an optimal set of filters for each computer. Each rule adaptively determines required characterizing data elements from each computer for determining an optimal security configuration. A local server updates the security configuration of a computer to suit changes in the operational environment of the computer.

Abstract: An intrusion prevention/detection system filter (IPS filter) performance evaluation is provided. The performance evaluation is performed at both the security center and at the customer sites to derive a base confidence score and local confidence scores. Existence of new vulnerability is disclosed and its attributes are used in the generation of new IPS filter or updates. The generated IPS filter is first tested to determine its base confidence score from test confidence attributes prior to deploying it to a customer site. A deep security manager and deep security agent, at the customer site, collect local confidence attributes that are used for determining the local confidence score. The local confidence score and the base confidence score are aggregated to form a global confidence score. The local and global confidence scores are then compared to deployment thresholds to determine whether the IPS filter should be deployed in prevention or detection mode or sent back to the security center for improvement.

Abstract: An intrusion-prevention server supporting a set of hosts comprises data filters and an engine which uses a set of encoded rules for assigning data filters to hosts according to metadata characterizing the hosts. Each data filter corresponds to at least one intrusion pattern from among a set of intrusion patterns and the data filters are continuously updated as intrusion patterns change. Metadata acquired from a host varies with a changing state of the host. Acquisition of metadata from each host is streamlined to reduce communications between the server and the hosts and to minimize processing effort for both the server and the hosts.

Abstract: An intrusion-prevention server supporting a set of hosts comprises data filters and an engine which uses a set of encoded rules for assigning data filters to hosts according to metadata characterizing the hosts. Each data filter corresponds to at least one intrusion pattern from among a set of intrusion patterns and the data filters are continuously updated as intrusion patterns change. Metadata acquired from a host varies with a changing state of the host. Acquisition of metadata from each host is streamlined to reduce communications between the server and the hosts and to minimize processing effort for both the server and the hosts.

Abstract: An intrusion-prevention server supporting a set of hosts comprises data filters and an engine which uses a set of encoded rules for assigning data filters to hosts according to metadata characterizing the hosts. Each data filter corresponds to at least one intrusion pattern from among a set of intrusion patterns and the data filters are continuously updated as intrusion patterns change. Metadata acquired from a host varies with a changing state of the host. Acquisition of metadata from each host is streamlined to reduce communications between the server and the hosts and to minimize processing effort for both the server and the hosts.

Abstract: An intrusion prevention/detection system filter (IPS filter) performance evaluation is provided. The performance evaluation is performed at both the security center and at the customer sites to derive a base confidence score and local confidence scores. Existence of new vulnerability is disclosed and its attributes are used in the generation of new IPS filter or updates. The generated IPS filter is first tested to determine its base confidence score from test confidence attributes prior to deploying it to a customer site. A deep security manager and deep security agent, at the customer site, collect local confidence attributes that are used for determining the local confidence score. The local confidence score and the base confidence score are aggregated to form a global confidence score. The local and global confidence scores are then compared to deployment thresholds to determine whether the IPS filter should be deployed in prevention or detection mode or sent back to the security center for improvement.

Abstract: Methods and apparatus for optimizing security configurations of a set of computers are disclosed. A set of local servers, each functioning as a deep-security manager supporting a respective subset of the computers, maintains protection software containing filters and rules for deploying each filter. A local server receives updated protection software from a central server. Each local server interrogates each computer of its subset of computers to acquire computer-characterizing data and applies relevant rules to determine an optimal set of filters for each computer. Each rule adaptively determines required characterizing data elements from each computer for determining an optimal security configuration. A local server updates the security configuration of a computer to suit changes in the operational environment of the computer.

Abstract: An intrusion-prevention server supporting a set of hosts comprises data filters and an engine which uses a set of encoded rules for assigning data filters to hosts according to metadata characterizing the hosts. Each data filter corresponds to at least one intrusion pattern from among a set of intrusion patterns and the data filters are continuously updated as intrusion patterns change. Metadata acquired from a host varies with a changing state of the host. Acquisition of metadata from each host is streamlined to reduce communications between the server and the hosts and to minimize processing effort for both the server and the hosts.

Abstract: A system and method for controlling program execution for a first-party includes providing application registration data, by a second-party (trusted party), wherein the application registration data contains a plurality of first unique application verification data (i.e., data elements), such as a list of hash values. Each unique application verification data element corresponds to at least one of the plurality of approved executable programs. The unique application verification data element is determined as a uniquely associatable data corresponding to each of corresponding executable programs from the plurality of executable programs. Prior to allowing individual program execution by the first-party, the first-party generates a second unique application verification data element, such as a hash value, of an executable file designated for execution on a processing device and compares the generated hash value to the list of hash values. If a match is found, the program is allowed to execute.

Abstract: A surgical instrument includes a plastic hub which is received by a handpiece for operating the instrument. The plastic hub includes a wall that encloses a passage that receives a surgical tool-carrying member, and at least one detectable coding element is embedded at a selected circumferential position in the wall. For example, the coding element is embedded in a hole disposed in the wall. Alternatively, the coding element is molded into the wall during injection molding of the hub. The coding element is, for example, a magnet.