Abstract: Aspects of the present disclosure relate generally to software development environments and, more particularly, to systems, computer program products, and methods of automating software development, security, and operations (DevSecOps). For example, a computer-implemented method includes receiving, by a processor, a plurality of infrastructure as code files specifying a configuration of a runtime environment for a deployable image of source code in a continuous integration and continuous delivery pipeline for a cloud platform; generating, by the processor, compliance code for at least one file of the plurality of infrastructure as code files; building, by the processor, the deployable image of the source code in the continuous integration and continuous delivery pipeline according to the configuration specified by the plurality of infrastructure as code files and the compliance code; and deploying, by the processor, an instance of the image in the runtime environment.

Abstract: A method for Governance, Risk, Compliance (GRC) and security compliance in a cloud computing environment is provided. The method includes maintaining a cloud resource to be in a transient state that keeps the cloud resource from being visible to other cloud resources for a configured rule driven duration during which validations comprising the GRC and security compliance are applied to the cloud resource. The method further includes provisioning the cloud resource responsive to the cloud resource meeting a time-in-transient-state requirement and passing the GRC and security compliance. The maintaining step includes reusing reactive validations for further GRC and security compliance in a resource lifecycle leveraging Application Programming Interface (API) based lifecycle events during the transient state, and deriving a next set of configurable actions for provisioned resources by providing hooks to a provisioning service to get a compliance posture for the cloud resource in the transient state.

Abstract: Using an image analysis model within an image intended for distribution online, an image portion depicting personally identifiable information is identified, the personally identifiable information comprising image data usable to identify a specific individual. Using an online profile, a person depicted in the image portion is identified. A transaction is posted in a publicly-accessible distributed encrypted ledger, the transaction comprising an encrypted request to allow the image to be distributed online. According to a response to the request, the image portion is obfuscated, the obfuscating comprising altering data of the image portion, the altering making the image portion unusable to identify the person.

Abstract: Using an image analysis model within an image intended for distribution online, an image portion depicting personally identifiable information is identified, the personally identifiable information comprising image data usable to identify a specific individual. Using an online profile, a person depicted in the image portion is identified. A transaction is posted in a publicly-accessible distributed encrypted ledger, the transaction comprising an encrypted request to allow the image to be distributed online. According to a response to the request, the image portion is obfuscated, the obfuscating comprising altering data of the image portion, the altering making the image portion unusable to identify the person.

Abstract: An approach is provided for validating and managing certificates. A certificate is received. Information related to the certificate and additional information an additional data source are determined. A risk factor is rated based on the information related to the certificate and the additional information from the additional source. The certificate is validated based on the rating of the risk factor. A unique hashtag ID is generated for the validated certificate and recorded on a blockchain network.

Abstract: A computer generates a profile, where the profile comprises one or more programs to monitor. The computer determines a baseline for each of the one or more programs by collecting one or more values associated with a normal operation for each of the one or more programs. The computer detects an anomaly based on deviation of the one or more values from the normal operation. Based on identifying a playbook for the anomaly, the computer applies the playbook on the program from the one or more programs. The computer organizes chat services based on identifying one or more members associated with the anomaly.

Abstract: A computer generates a profile, where the profile comprises one or more programs to monitor. The computer determines a baseline for each of the one or more programs by collecting one or more values associated with a normal operation for each of the one or more programs. The computer detects an anomaly based on deviation of the one or more values from the normal operation. Based on identifying a playbook for the anomaly, the computer applies the playbook on the program from the one or more programs. The computer organizes chat services based on identifying one or more members associated with the anomaly.

Abstract: Trustable delivery of a product uses a package with a printed label having a unique product ID, an RFID marker applied to the product that contains the ID, and a smart chip inside the product that contains the ID and a digital key. The ID from the RFID marker is compared to the label for initial validation of the package. The smart chip is further interrogated to generate an encoded value of the ID, such as a hash value, using the digital key. The hash value is then used to authenticate the ID, thereby verifying that the product as delivered is the original, untampered product. The product ID and the hash value are recorded in a blockchain ledger associated with the product. In this manner, the packaged product can be validated by any party in the delivery chain, e.g., manufacturer, seller, distributor, delivery service, and final recipient.

Abstract: An example operation includes one or more of selecting, by a trust maintainer node, at least two blockchain nodes to be assigned as non-human intelligent nodes controlled by separate consortiums, identifying, by the trust maintainer node, a plurality of blockchain nodes that are not assigned as non-human intelligent nodes, assigning, by the trust maintainer node, a trust value to each of the plurality of the blockchain nodes based on voting histories of each of the plurality of the blockchain nodes to determine an overall trust value of a blockchain, and responsive to the overall trust value of the blockchain being below a minimum threshold, selecting at least one node from the plurality of the nodes to be assigned as the non-human intelligent node to increase the overall trust value of the blockchain.

Abstract: An example operation includes one or more of selecting, by a trust maintainer node, at least two blockchain nodes to be assigned as non-human intelligent nodes controlled by separate consortiums, identifying, by the trust maintainer node, a plurality of blockchain nodes that are not assigned as non-human intelligent nodes, assigning, by the trust maintainer node, a trust value to each of the plurality of the blockchain nodes based on voting histories of each of the plurality of the blockchain nodes to determine an overall trust value of a blockchain, and responsive to the overall trust value of the blockchain being below a minimum threshold, selecting at least one node from the plurality of the nodes to be assigned as the non-human intelligent node to increase the overall trust value of the blockchain.

Abstract: Trustable delivery of a product uses a package with a printed label having a unique product ID, an RFID marker applied to the product that contains the ID, and a smart chip inside the product that contains the ID and a digital key. The ID from the RFID marker is compared to the label for initial validation of the package. The smart chip is further interrogated to generate an encoded value of the ID, such as a hash value, using the digital key. The hash value is then used to authenticate the ID, thereby verifying that the product as delivered is the original, untampered product. The product ID and the hash value are recorded in a blockchain ledger associated with the product. In this manner, the packaged product can be validated by any party in the delivery chain, e.g., manufacturer, seller, distributor, delivery service, and final recipient.

Abstract: Using an image analysis model within an image intended for distribution online, an image portion depicting personally identifiable information is identified, the personally identifiable information comprising image data usable to identify a specific individual. Using an online profile, a person depicted in the image portion is identified. A transaction is posted in a publicly-accessible distributed encrypted ledger, the transaction comprising an encrypted request to allow the image to be distributed online. According to a response to the request, the image portion is obfuscated, the obfuscating comprising altering data of the image portion, the altering making the image portion unusable to identify the person.