Monitoring Data Integrity in Big Data Analytics Services

Enabled by advances in Cloud technologies, Big Data Analytics Services (BDAS) can improve many processes and identify extra information from previously untapped data sources. As our experience with BDAS and its benefits grows and technology for obtaining even more data improves, BDAS becomes ever more important for many different domains and for our daily lives. Most efforts in improving BDAS technologies have focused on scaling and efficiency issues. However, an equally important property is that of security, especially as we increasingly use public Cloud infrastructures instead of private ones. In this paper we present our approach for strengthening BDAS security by modifying the popular Spark infrastructure so as to monitor at run-time the integrity of data manipulated. In this way, we can ensure that the results obtained by the complex and resource-intensive computations performed on the Cloud are based on correct data and not data that have been tampered with or modified through faults in one of the many and complex subsystems of the overall system

AMISEC: Leveraging Redundancy and Adaptability to Secure AmI Applications

Security in Ambient Intelligence (AmI) poses too many challenges due to the inherently insecure nature of wireless sensor nodes. However, there are two characteristics of these environments that can be used effectively to prevent, detect, and confine attacks: redundancy and continuous adaptation. In this article we propose a global strategy and a system architecture to cope with security issues in AmI applications at different levels. Unlike in previous approaches, we assume an individual wireless node is vulnerable. We present an agent-based architecture with supporting services that is proven to be adequate to detect and confine common attacks. Decisions at different levels are supported by a trust-based framework with good and bad reputation feedback while maintaining resistance to bad-mouthing attacks. We also propose a set of services that can be used to handle identification, authentication, and authorization in intelligent ambients. The resulting approach takes into account practical issues, such as resource limitation, bandwidth optimization, and scalability

Link-time smart card code hardening

This paper presents a feasibility study to protect smart card software against fault-injection attacks by means of link-time code rewriting. This approach avoids the drawbacks of source code hardening, avoids the need for manual assembly writing, and is applicable in conjunction with closed third-party compilers. We implemented a range of cookbook code hardening recipes in a prototype link-time rewriter and evaluate their coverage and associated overhead to conclude that this approach is promising. We demonstrate that the overhead of using an automated link-time approach is not significantly higher than what can be obtained with compile-time hardening or with manual hardening of compiler-generated assembly code

An autonomous GNSS anti-spoofing technique

open3siIn recent years, the problem of Position, Navigation and Timing (PNT) resiliency has received significant attention due to an increasing awareness on threats and the vulnerability of the current GNSS signals. Several proposed solutions make uses of cryptography to protect against spoofing. A limitation of cryptographic techniques is that they introduce a communication and processing computation overhead and may impact the performance in terms of availability and continuity for GNSS users. This paper introduces autonomous non cryptographic antispoofing mechanisms, that exploit semi-codeless receiver techniques to detect spoofing for signals with a component making use of spreading code encryption.openCaparra, Gianluca; Wullems, Christian; Ioannides, Rigas T.Caparra, Gianluca; Wullems, Christian; Ioannides, Rigas T

Enhancement Data Security in Cloud Computing: Issues and Challenges

Cloud Computing can save an organization’s time and money but trusting the system is very much important because the real asset of any organization is the data which they share in the cloud to use the needed service by putting it directly in the relational database. No organization can transfer its data or information to a third party until a bridge of trust is built. This paper provides a concise and all roun小d analysis on data security and privacy protection issues associated with computing across all stages of data life cycle. It argues that, in contrast to the traditional solution where unauthorized third party can access organizational data illegally which raises a serious concern since data is scattered at different places all over the globe. The security concerns of users need to be addressed to make cloud environment safe and trustworthy. Every cloud provider solves this by encrypting data using encryption algorithm which is inadequate. The paper concludes by recommending that in addition to the traditional methods, the security of  cloud computing can also be enhanced through authentication using thumb print, face, voice and image identification. Keywords: Cloud computing, Information Technology, Data Integrity, Authentication, Security and Challenges