查看更多>>摘要：During the rise of cloud computing, activist programmers created blockchain. Now blockchain has the potential to transform the existing cloud applications.
查看更多>>摘要：The Internet of Things (IoT) has already reshaped and transformed our lives in many ways, ranging from how we communicate with people or manage our health to how we drive our cars and manage our homes. With the rapid development of the IoT ecosystem in a wide range of applications, IoT devices and data are going to be traded as commodities in the marketplace in the near future, similar to cloud services or physical objects. Developing such a trading platform has previously been identified as one of the key grand challenges in the integration of IoT and data science. Deployment of such a platform raises concerns about the security and privacy of data and devices since their ownership is hard to trace and manage without a central trusted authority. A central trusted authority is not a viable solution for a fully decentralized and distributed IoT ecosystem with a large number of distributed device vendors and consumers. Blockchain, as a decentralized system, removes the requirement for a trusted thirdparty by allowing participants to verify data correctness and ensure its immutability. IoT devices can use blockchain to register themselves and organize, store, and share streams of data effectively and reliably. We demonstrate the applicability of blockchain to IoT devices and data management with an aim of providing end-to-end trust for trading. We also give a brief introduction to the topics and challenges for future research toward developing a trustworthy trading platform for IoT ecosystems.
David A. MalufRaghuram S. SudhaakarKim-Kwang Raymond Choo
24-32页
查看更多>>摘要：Although todays average cloud computing environment may incorporate security in most aspects of its design and infrastructure, the mere operation of the network exposes it to attacks. A typical attack starts with probing for weaknesses and/or vulnerabilities that can be exploited. And it is at this stage that the battle seems to be already lost, as the average network is insufficiently equipped-mostly for economic reasons-to even know that they are under probing, let alone thwart an attack. In many cases, cloud systems are caught unaware of situations where friends turn into foes, nullifying established security measures. Threats will always dwell on new (previously unknown) methods to compromise established security measures (i.e., a rat race between defenders and attackers, particularly well-resourced attackers). These methods largely fall outside the adapted models used by current security measures that protect cloud-based systems. After-the-fact analysis has driven security researchers to extend models to include assumptions about newly discovered threat(s). Solutions are then designed to deter these new threats. These models may also be generalized with additional measures mapping futuristic predictions-these are also referred to as known-unknowns.
查看更多>>摘要：When dealing with big biometric data, data reduction becomes a challenge. This article proposes a novel big biometric data reduction solution in the cloud environment, including a big biometric data reduction approach based on tensor decomposition, an incremental big biometric tensor reduction approach, and a secure big biometric data reduction approach, which can significantly reduce big biometric data.
查看更多>>摘要：Cloud-connected mobile applications are becoming a popular solution for ubiquitous access to online services, such as cloud data storage platforms. The adoption of such applications has brought security and privacy implications that are making individuals hesitant to migrate sensitive data to the Cloud; thus, new secure authentication protocols are needed. In this paper, we propose a continuous authentication approach integrating physical (face) and behavioral (touch and hand movements) biometrics to control user access to Cloud-based mobile services, going beyond one-off login. Experimental results show the security-usability tradeoff achieved by our approach.
Maria De MarsicoEugenio NemmiBardh PrenkajGabriele Saturni...
58-69页
查看更多>>摘要：This article presents a novel approach to extend cloud computing from company services to consumer biometrics. The proposed system recognizes the person at the door, allowing entrance or denying it according to the recognition result. Very little processing is required locally, and biometrics is implemented as a service.
查看更多>>摘要：This article describes new ideas for applying security procedures to data and service management in cloud and fog computing. Management in cloud computing is presented in connection with cognitive systems supporting management tasks and securing important data. The application of cognitive and biometric features allows creation of personalized procedures oriented at particular users or a group of protocol participants.
查看更多>>摘要：The cloud-assisted Internet of Things (IoT) provides a promising solution to data booming problems for the ability constraints of individual objects. However, with the leverage of cloud, IoT faces new security challenges for data mutuality between two parties, which is introduced for the first time in this paper and not currently addressed by traditional approaches. We investigate a secure cloud-assisted IoT data managing method to protect data confidentiality when collecting, storing, and accessing IoT data while limiting to effects of IoT scalability. We further present numerical results to show that the method is practical.
查看更多>>摘要：Cloud computing is too often seen as a tactical way to reduce costs, when its most important benefit is as a strategic way to grow revenues. Such revenue growth can come about in a variety of ways, such as through faster innovation of new products, processes, and customer interactions; identifying more customers and closing more purchases; and improving customer relationships through more targeted offers and better service and experiences. Companies that clearly understand the relative magnitude of cost savings and revenue growth and orient themselves toward the latter will better exploit the cloud and related technologies such as big data, artificial intelligence (AI), the Internet of Things, and blockchain, and thus strengthen their competitive advantage and customer value.
NETL
NSTL
IEEE