4,202 research outputs found
A comprehensive meta-analysis of cryptographic security mechanisms for cloud computing
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The concept of cloud computing offers measurable computational or information resources as a service over the Internet. The major motivation behind the cloud setup is economic benefits, because it assures the reduction in expenditure for operational and infrastructural purposes. To transform it into a reality there are some impediments and hurdles which are required to be tackled, most profound of which are security, privacy and reliability issues. As the user data is revealed to the cloud, it departs the protection-sphere of the data owner. However, this brings partly new security and privacy concerns. This work focuses on these issues related to various cloud services and deployment models by spotlighting their major challenges. While the classical cryptography is an ancient discipline, modern cryptography, which has been mostly developed in the last few decades, is the subject of study which needs to be implemented so as to ensure strong security and privacy mechanisms in today’s real-world scenarios. The technological solutions, short and long term research goals of the cloud security will be described and addressed using various classical cryptographic mechanisms as well as modern ones. This work explores the new directions in cloud computing security, while highlighting the correct selection of these fundamental technologies from cryptographic point of view
Secure Identification in Social Wireless Networks
The applications based on social networking have brought revolution towards social life and are continuously gaining popularity among the Internet users. Due to the advanced computational resources offered by the innovative hardware and nominal subscriber charges of network operators, most of the online social networks are transforming into the mobile domain by offering exciting applications and games exclusively designed for users on the go. Moreover, the mobile devices are considered more personal as compared to their desktop rivals, so there is a tendency among the mobile users to store sensitive data like contacts, passwords, bank account details, updated calendar entries with key dates and personal notes on their devices.
The Project Social Wireless Network Secure Identification (SWIN) is carried out at Swedish Institute of Computer Science (SICS) to explore the practicality of providing the secure mobile social networking portal with advanced security features to tackle potential security threats by extending the existing methods with more innovative security technologies. In addition to the extensive background study and the determination of marketable use-cases with their corresponding security requirements, this thesis proposes a secure identification design to satisfy the security dimensions for both online and offline peers. We have implemented an initial prototype using PHP Socket and OpenSSL library to simulate the secure identification procedure based on the proposed design. The design is in compliance with 3GPP‟s Generic Authentication Architecture (GAA) and our implementation has demonstrated the flexibility of the solution to be applied independently for the applications requiring secure identification. Finally, the thesis provides strong foundation for the advanced implementation on mobile platform in future
SHE based Non Interactive Privacy Preserving Biometric Authentication Protocols
Being unique and immutable for each person, biometric signals are widely used in access control systems. While biometric recognition appeases concerns about password's theft or loss, at the same time it raises concerns about individual privacy. Central servers store several enrolled biometrics, hence security against theft must be provided during biometric transmission and against those who have access to the database. If a server's database is compromised, other systems using the same biometric templates could also be compromised as well. One solution is to encrypt the stored templates. Nonetheless, when using traditional cryptosystem, data must be decrypted before executing the protocol, leaving the database vulnerable. To overcame this problem and protect both the server and the client, biometrics should be processed while encrypted. This is possible by using secure two-party computation protocols, mainly based on Garbled Circuits (GC) and additive Homomorphic Encryption (HE). Both GC and HE based solutions are efficient yet interactive, meaning that the client takes part in the computation. Instead in this paper we propose a non-interactive protocol for privacy preserving biometric authentication based on a Somewhat Homomorphic Encryption (SHE) scheme, modified to handle integer values, and also suggest a blinding method to protect the system from spoofing attacks. Although our solution is not as efficient as the ones based on GC or HE, the protocol needs no interaction, moving the computation entirely on the server side and leaving only inputs encryption and outputs decryption to the client
Privately Connecting Mobility to Infectious Diseases via Applied Cryptography
Human mobility is undisputedly one of the critical factors in infectious
disease dynamics. Until a few years ago, researchers had to rely on static data
to model human mobility, which was then combined with a transmission model of a
particular disease resulting in an epidemiological model. Recent works have
consistently been showing that substituting the static mobility data with
mobile phone data leads to significantly more accurate models. While prior
studies have exclusively relied on a mobile network operator's subscribers'
aggregated data, it may be preferable to contemplate aggregated mobility data
of infected individuals only. Clearly, naively linking mobile phone data with
infected individuals would massively intrude privacy. This research aims to
develop a solution that reports the aggregated mobile phone location data of
infected individuals while still maintaining compliance with privacy
expectations. To achieve privacy, we use homomorphic encryption, zero-knowledge
proof techniques, and differential privacy. Our protocol's open-source
implementation can process eight million subscribers in one and a half hours.
Additionally, we provide a legal analysis of our solution with regards to the
EU General Data Protection Regulation.Comment: Added differentlial privacy experiments and new benchmark
A Novel Framework for Big Data Security Infrastructure Components
Big data encompasses enormous data and management of huge data collected from various sources like online social media contents, log files, sensor records, surveys and online transactions. It is essential to provide new security models, concerns and efficient security designs and approaches for confronting security and privacy aspects of the same. This paper intends to provide initial analysis of the security challenges in Big Data. The paper introduces the basic concepts of Big Data and its enormous growth rate in terms of pita and zettabytes. A model framework for Big Data Infrastructure Security Components Framework (BDAF) is proposed that includes components like Security Life Cycle, Fine-grained data-centric access control policies, the Dynamic Infrastructure Trust Bootstrap Protocol (DITBP). The framework allows deploying trusted remote virtualised data processing environment and federated access control and identity management
CamFlow: Managed Data-sharing for Cloud Services
A model of cloud services is emerging whereby a few trusted providers manage
the underlying hardware and communications whereas many companies build on this
infrastructure to offer higher level, cloud-hosted PaaS services and/or SaaS
applications. From the start, strong isolation between cloud tenants was seen
to be of paramount importance, provided first by virtual machines (VM) and
later by containers, which share the operating system (OS) kernel. Increasingly
it is the case that applications also require facilities to effect isolation
and protection of data managed by those applications. They also require
flexible data sharing with other applications, often across the traditional
cloud-isolation boundaries; for example, when government provides many related
services for its citizens on a common platform. Similar considerations apply to
the end-users of applications. But in particular, the incorporation of cloud
services within `Internet of Things' architectures is driving the requirements
for both protection and cross-application data sharing.
These concerns relate to the management of data. Traditional access control
is application and principal/role specific, applied at policy enforcement
points, after which there is no subsequent control over where data flows; a
crucial issue once data has left its owner's control by cloud-hosted
applications and within cloud-services. Information Flow Control (IFC), in
addition, offers system-wide, end-to-end, flow control based on the properties
of the data. We discuss the potential of cloud-deployed IFC for enforcing
owners' dataflow policy with regard to protection and sharing, as well as
safeguarding against malicious or buggy software. In addition, the audit log
associated with IFC provides transparency, giving configurable system-wide
visibility over data flows. [...]Comment: 14 pages, 8 figure
LightChain: A DHT-based Blockchain for Resource Constrained Environments
As an append-only distributed database, blockchain is utilized in a vast
variety of applications including the cryptocurrency and Internet-of-Things
(IoT). The existing blockchain solutions have downsides in communication and
storage efficiency, convergence to centralization, and consistency problems. In
this paper, we propose LightChain, which is the first blockchain architecture
that operates over a Distributed Hash Table (DHT) of participating peers.
LightChain is a permissionless blockchain that provides addressable blocks and
transactions within the network, which makes them efficiently accessible by all
the peers. Each block and transaction is replicated within the DHT of peers and
is retrieved in an on-demand manner. Hence, peers in LightChain are not
required to retrieve or keep the entire blockchain. LightChain is fair as all
of the participating peers have a uniform chance of being involved in the
consensus regardless of their influence such as hashing power or stake.
LightChain provides a deterministic fork-resolving strategy as well as a
blacklisting mechanism, and it is secure against colluding adversarial peers
attacking the availability and integrity of the system. We provide mathematical
analysis and experimental results on scenarios involving 10K nodes to
demonstrate the security and fairness of LightChain. As we experimentally show
in this paper, compared to the mainstream blockchains like Bitcoin and
Ethereum, LightChain requires around 66 times less per node storage, and is
around 380 times faster on bootstrapping a new node to the system, while each
LightChain node is rewarded equally likely for participating in the protocol
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