Abstract: Even though serverless computing has advantages like lower cost, simplified scalability, simplified backend code and quicker turnaround, they have also given rise to a new form of cyber-attacks. Most of the conventional approaches are reactive based where steps are taken to control the aftereffects of an attack and preventive mechanism is of less focus. The present honeypot based approach for serverless cloud architecture, honeypots capture unauthorized users in order to provide security of the overall system. The honeypots redirect the attackers to a set of dummy nodes that form a random loop. Using a controlled time based loop, the attacker could be trapped for a maximum amount of time, thus penalizing the attacker by a negative award. It would result in exhaustion of resources and bandwidth of attacker. The present disclosure is also applicable to multi-cloud or hybrid cloud setup.

Abstract: A mechanism for error containment in a data processing system includes receiving a transaction request at a gateway between a host and a device, allocating an entry for the request in a local request tracker of the gateway and sending a link request, to a port of the gateway. In response to an isolation trigger, the port is moved into isolation by completing in-process requests with entries in the tracker and locking the entries. On receiving a response to an in-process request while the port is in isolation, the response is dropped, the associated entry is unlocked, and allocation of the entry is enabled. A completion response is sent to the requester without dispatching a new link request to the port. When requests are completed, the system is quiesced, locked entries are unlocked, and the port is moved out of isolation.

Abstract: The present disclosure provides an efficient system for cancelable biometric template protection which is not available in the conventional systems. Initially, the system receives a biometric template from a user. The biometric template is one of, a face image, a fingerprint, an iris image and a palmprint. Further, a vector embedding is computed based on the biometric template using a pretrained neural network. After computing the vector embedding, a key based permutation is computed based on the vector embedding and a permutation key. The permutation key is generated based on an Identification number (ID) associated with the user using a random number based key generation technique. Finally, a protected biometric template is generated by computing a permuted embedding corresponding to the biometric template based on the key based permutation using a plurality of fully connected layers pretrained using a weight based center triplet loss function.

Abstract: A mechanism for error containment in a data processing system includes receiving a transaction request at a gateway between a host and a device, allocating an entry for the request in a local request tracker of the gateway and sending a link request, to a port of the gateway. In response to an isolation trigger, the port is moved into isolation by completing in-process requests with entries in the tracker and locking the entries. On receiving a response to an in-process request while the port is in isolation, the response is dropped, the associated entry is unlocked, and allocation of the entry is enabled. A completion response is sent to the requester without dispatching a new link request to the port. When requests are completed, the system is quiesced, locked entries are unlocked, and the port is moved out of isolation.

Abstract: State of the art approaches used to address security aspects in serverless platforms perform workflow validations on an end to end flow, however, this cannot prevent attacks targeted at intermediate function calls in the workflow. Further, the existing systems store policy data in insecure manner, which causes security issues. The disclosure herein generally relates to serverless clouds, and, more particularly, to a method and system for privacy-preserving workflow validations in serverless clouds. The system stores policy data in a secured/encrypted manner. The system also performs validations at different levels, at a first level to allow/deny access at an ingress point, and at a second level to allow/deny access at critical intermediate points. This approach thus provides safety against attacks that may have been initiated post initial validation, and offers added data security.

Abstract: The present disclosure detects a pupil of an eye using circle formation based scoring method. The conventional approaches fail to provide an accurate and reliable biometric authentication due to the usage of simple thresholding based statistical methods and iris dependent segmentation methods. The present disclosure utilizes a circle plotting approach and selects the optimum circle using several parameters. The present disclosure can generate a pupil boundary that fits the pupil region inside an iris perfectly. Initially, the system receives an input image of an eye. After removing reflections, a core point of the reflection free image is identified. Further, a plurality of points are obtained based on a sudden gradient change. and a plurality of circles are plotted. Further, an optimum circle is identified using a score based optimum circle selection method. Finally, the pupil associated with the input image is identified based on the optimum circle.

Abstract: The present disclosure provides an efficient system for cancelable biometric template protection which is not available in the conventional systems. Initially, the system receives a biometric template from a user. The biometric template is one of, a face image, a fingerprint, an iris image and a palmprint. Further, a vector embedding is computed based on the biometric template using a pretrained neural network. After computing the vector embedding, a key based permutation is computed based on the vector embedding and a permutation key. The permutation key is generated based on an Identification number (ID) associated with the user using a random number based key generation technique. Finally, a protected biometric template is generated by computing a permuted embedding corresponding to the biometric template based on the key based permutation using a plurality of fully connected layers pretrained using a weight based center triplet loss function.