Secure Data Sharing in Cloud Computing: A Comprehensive Review

Cloud Computing is an emerging technology, which relies on sharing computing resources. Sharing of data in the group is not secure as the cloud provider cannot be trusted. The fundamental difficulties in distributed computing of cloud suppliers is Data Security, Sharing, Resource scheduling and Energy consumption. Key-Aggregate cryptosystem used to secure private/public data in the cloud. This key is consistent size aggregate for adaptable decisions of ciphertext in cloud storage. Virtual Machines (VMs) provisioning is effectively empowered the cloud suppliers to effectively use their accessible resources and get higher benefits. The most effective method to share information resources among the individuals from the group in distributed storage is secure, flexible and efficient. Any data stored in different cloud data centers are corrupted, recovery using regenerative coding. Security is provided many techniques like Forward security, backward security, Key-Aggregate cryptosystem, Encryption and Re-encryption etc. The energy is reduced using Energy-Efficient Virtual Machines Scheduling in Multi-Tenant Data Centers

Secure data sharing in cloud computing: a comprehensive review

Cloud Computing is an emerging technology, which relies on sharing computing resources. Sharing of data in the group is not secure as the cloud provider cannot be trusted. The fundamental difficulties in distributed computing of cloud suppliers is Data Security, Sharing, Resource scheduling and Energy consumption. Key-Aggregate cryptosystem used to secure private/public data in the cloud. This key is consistent size aggregate for adaptable decisions of ciphertext in cloud storage. Virtual Machines (VMs) provisioning is effectively empowered the cloud suppliers to effectively use their accessible resources and get higher benefits. The most effective method to share information resources among the individuals from the group in distributed storage is secure, flexible and efficient. Any data stored in different cloud data centers are corrupted, recovery using regenerative coding. Security is provided many techniques like Forward security, backward security, Key-Aggregate cryptosystem, Encryption and Re-encryption etc. The energy is reduced using Energy-Efficient Virtual Machines Scheduling in Multi-Tenant Data Centers

Enhancing System Transparency, Trust, and Privacy with Internet Measurement

While on the Internet, users participate in many systems designed to protect their information’s security. Protection of the user’s information can depend on several technical properties, including transparency, trust, and privacy. Preserving these properties is challenging due to the scale and distributed nature of the Internet; no single actor has control over these features. Instead, the systems are designed to provide them, even in the face of attackers. However, it is possible to utilize Internet measurement to better defend transparency, trust, and privacy. Internet measurement allows observation of many behaviors of distributed, Internet-connected systems. These new observations can be used to better defend the system they measure. In this dissertation, I explore four contexts in which Internet measurement can be used to the aid of end-users in Internet-centric, adversarial settings. First, I improve transparency into Internet censorship practices by developing new Internet measurement techniques. Then, I use Internet measurement to enable the deployment of end-to-middle censorship circumvention techniques to a half-million users. Next, I evaluate transparency and improve trust in the Web public-key infrastructure by combining Internet measurement techniques and using them to augment core components of the Web public-key infrastructure. Finally, I evaluate browser extensions that provide privacy to users on the web, providing insight for designers and simple recommendations for end-users. By focusing on end-user concerns in widely deployed systems critical to end-user security and privacy, Internet measurement enables improvements to transparency, trust, and privacy.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163199/1/benvds_1.pd

CheriOS: Designing an untrusted single-address-space capability operating system utilising capability hardware and a minimal hypervisor

This thesis presents the design, implementation, and evaluation of a novel capability operating system: CheriOS. The guiding motivation behind CheriOS is to provide strong security guarantees to programmers, even allowing them to continue to program in fast, but typically unsafe, languages such as C. Furthermore, it does this in the presence of an extremely strong adversarial model: in CheriOS, every compartment -- and even the operating system itself -- is considered actively malicious. Building on top of the architecturally enforced capabilities offered by the CHERI microprocessor, I show that only a few more capability types and enforcement checks are required to provide a strong compartmentalisation model that can facilitate mutual distrust. I implement these new primitives in software, in a new abstraction layer I dub the nanokernel. Among the new OS primitives I introduce are one for integrity and confidentiality called a Reservation (which allows allocating private memory without trusting the allocator), as well as another that can provide attestation about the state of the system, a Foundation (which provides a key to sign and protect capabilities based on a signature of the starting state of a program). I show that, using these new facilities, it is possible to design an operating system without having to trust the implementation is correct. CheriOS is fundamentally fail-safe; there are no assumptions about the behaviour of the system, apart from the CHERI processor and the nanokernel, to be broken. Using CHERI and the new nanokernel primitives, programmers can expect full isolation at scopes ranging from a whole program to a single function, and not just with respect to other programs but the system itself. Programs compiled for and run on CheriOS offer full memory safety, both spatial and temporal, enforced control flow integrity between compartments and protection against common vulnerabilities such as buffer overflows, code injection and Return-Oriented-Programming attacks. I achieve this by designing a new CHERI-based ABI (Application Binary Interface) which includes a novel stack structure that offers temporal safety. I evaluate how practical the new designs are by prototyping them and offering a detailed performance evaluation. I also contrast with existing offerings from both industry and academia. CHERI capabilities can be used to restrict access to system resources, such as memory, with the required dynamic checks being performed by hardware in parallel with normal operation. Using the accelerating features of CHERI, I show that many of the security guarantees that CheriOS offers can come at little to no cost. I present a novel and secure IO/IPC layer that allows secure marshalling of multiple data streams through mutually distrusting compartments, with fine-grained authenticated access control for end-points, and without either copying or encryption. For example, CheriOS can restrict its TCP stack from having access to packet contents, or restrict an open socket to ensure data sent on it to arrives at an endpoint signed as a TLS implementation. Even with added security requirements, CheriOS can perform well on real workloads. I showcase this by running a state-of-the-art webserver, NGINX, atop both CheriOS and FreeBSD and show improvements in performance ranging from 3x to 6x when running on a small-scale low-power FPGA implementation of CHERI-MIPS

Fundamentals

Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

Fundamentals

Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Term-driven E-Commerce

Die Arbeit nimmt sich der textuellen Dimension des E-Commerce an. Grundlegende Hypothese ist die textuelle Gebundenheit von Information und Transaktion im Bereich des elektronischen Handels. Überall dort, wo Produkte und Dienstleistungen angeboten, nachgefragt, wahrgenommen und bewertet werden, kommen natürlichsprachige Ausdrücke zum Einsatz. Daraus resultiert ist zum einen, wie bedeutsam es ist, die Varianz textueller Beschreibungen im E-Commerce zu erfassen, zum anderen können die umfangreichen textuellen Ressourcen, die bei E-Commerce-Interaktionen anfallen, im Hinblick auf ein besseres Verständnis natürlicher Sprache herangezogen werden