Biblio

We consider the problem of designing repair efficient distributed storage systems, which are information-theoretically secure against a passive eavesdropper that can gain access to a limited number of storage nodes. We present a framework that enables design of a broad range of secure storage codes through a joint construction of inner and outer codes. As case studies, we focus on two specific families of storage codes: (i) minimum storage regenerating (MSR) codes, and (ii) maximally recoverable (MR) codes, which are a class of locally repairable codes (LRCs). The main idea of this framework is to utilize the existing constructions of storage codes to jointly design an outer coset code and inner storage code. Finally, we present a construction of an outer coset code over small field size to secure locally repairable codes presented by Tamo and Barg for the special case of an eavesdropper that can observe any subset of nodes of maximum possible size.

Integer errors in C/C++ are caused by arithmetic operations yielding results which are unrepresentable in certain type. They can lead to serious safety and security issues. Due to the complicated semantics of C/C++ integers, integer errors are widely harbored in real-world programs and it is error-prone to repair them even for experts. An automatic tool is desired to 1) automatically generate fixes which assist developers to correct the buggy code, and 2) provide sufficient hints to help developers review the generated fixes and better understand integer types in C/C++. In this paper, we present a tool IntPTI that implements the desired functionalities for C programs. IntPTI infers appropriate types for variables and expressions to eliminate representation issues, and then utilizes the derived types with fix patterns codified from the successful human-written patches. IntPTI provides a user-friendly web interface which allows users to review and manage the fixes. We evaluate IntPTI on 7 real-world projects and the results show its competitive repair accuracy and its scalability on large code bases. The demo video for IntPTI is available at: https://youtu.be/9Tgd4A\_FgZM.

The performance, dependability, and security of cloud service systems are vital for the ongoing operation, control, and support. Thus, controlled improvement in service requires a comprehensive analysis and systematic identification of the fundamental underlying constituents of cloud using a rigorous discipline. In this paper, we introduce a framework which helps identifying areas for potential cloud service enhancements. A cloud service cannot be completed if there is a failure in any of its underlying resources. In addition, resources are kept offline for scheduled maintenance. We use redundant resources to mitigate the impact of failures/maintenance for ensuring performance and dependability; which helps enhancing security as well. For example, at least 4 replicas are required to defend the intrusion of a single instance or a single malicious attack/fault as defined by Byzantine Fault Tolerance (BFT). Data centers with high performance, dependability, and security are outsourced to the cloud computing environment with greater flexibility of cost of owing the computing infrastructure. In this paper, we analyze the effectiveness of redundant resource usage in terms of dependability metric and cost of service deployment based on the priority of service requests. The trade-off among dependability, cost, and security under different redundancy schemes are characterized through the comprehensive analytical models.

Network systems, such as transportation systems and water supply systems, play important roles in our daily life and industrial production. However, a variety of disruptive events occur during their life time, causing a series of serious losses. Due to the inevitability of disruption, we should not only focus on improving the reliability or the resistance of the system, but also pay attention to the ability of the system to response timely and recover rapidly from disruptive events. That is to say we need to pay more attention to the resilience. In this paper, we describe two resilience models, quotient resilience and integral resilience, to measure the final recovered performance and the performance cumulative process during recovery respectively. Based on these two models, we implement the optimization of the system recovery strategies after disruption, focusing on the repair sequence of the damaged components and the allocation scheme of resource. The proposed research in this paper can serve as guidance to prioritize repair tasks and allocate resource reasonably.

This paper proposes a practical time-phased model to analyze the vulnerability of power systems over a time horizon, in which the scheduled maintenance of network facilities is considered. This model is deemed as an efficient tool that could be used by system operators to assess whether how their systems become vulnerable giving a set of scheduled facility outages. The final model is presented as a single level Mixed-Integer Linear Programming (MILP) problem solvable with commercially available software. Results attained based on the well-known IEEE 24-Bus Reliability Test System (RTS) appreciate the applicability of the model and highlight the necessity of considering the scheduled facility outages in assessing the vulnerability of a power system.

Web application security has become crucially vital these days. Earlier "default allow" model was used to secure web applications but it was unable to secure web applications against plethora of attacks [1]. In contrast, more restricted security to the web applications is provided by default deny model which at first, builds a model for the particular application and then permits merely those requests that conform to that model while ignoring everything else. Besides this, a novel and effective methodology is followed that allows to analyze the validity of application requests and further results in the generation of semi structured XML cases for the web applications. Furthermore, mature and resilient XML cases are generated by employing learning techniques. This system will further be gauged by examining that XML file containing cases are in correct accordance with the XML format or not. Moreover, the distinction between malicious and non-malicious traffic is carried out carefully. Results have proved its efficacy of rule generation employing access traffic log of cross site scripting (XSS), SQL injection, HTTP Request Splitting, HTTP response splitting and Buffer overflow attacks.

Memristors are an attractive option for use in future memory architectures due to their non-volatility, high density and low power operation. Notwithstanding these advantages, memristors and memristor-based memories are prone to high defect densities due to the non-deterministic nature of nanoscale fabrication. The typical approach to fault detection and diagnosis in memories entails testing one memory cell at a time. This is time consuming and does not scale for the dense, memristor-based memories. In this paper, we integrate solutions for detecting and locating faults in memristors, and ensure post-silicon recovery from memristor failures. We propose a hybrid diagnosis scheme that exploits sneak-paths inherent in crossbar memories, and uses March testing to test and diagnose multiple memory cells simultaneously, thereby reducing test time. We also provide a repair mechanism that prevents faults in the memory from being activated. The proposed schemes enable and leverage sneak paths during fault detection and diagnosis modes, while still maintaining a sneak-path free crossbar during normal operation. The proposed hybrid scheme reduces fault detection and diagnosis time by ~44%, compared to traditional March tests, and repairs the faulty cell with minimal overhead.
 

The EIIM model for ER allows for creation and maintenance of persistent entity identity structures. It accomplishes this through a collection of batch configurations that allow updates and asserted fixes to be made to the Identity knowledgebase (IKB). The model also provides a batch IR configuration that provides no maintenance activity but instead allows access to the identity information. This batch IR configuration is limited in a few ways. It is driven by the same rules used for maintaining the IKB, has no inherent method to identity "close" matches, and can only identify and return the positive matches. Through the decoupling of this configuration and its movements into an interactive role under the umbrella of an Identity Management Service, a more robust access method can be provided for the use of identity information. This more robust access to the information improved the quality of the information along multiple Information Quality dimensions.

In this paper, we consider the security of exact-repair regenerating codes operating at the minimum-storage-regenerating (MSR) point. The security requirement (introduced in Shah et. al.) is that no information about the stored data file must be leaked in the presence of an eavesdropper who has access to the contents of ℓ1 nodes as well as all the repair traffic entering a second disjoint set of ℓ2 nodes. We derive an upper bound on the size of a data file that can be securely stored that holds whenever ℓ2 ≤ d - k + 1. This upper bound proves the optimality of the product-matrix-based construction of secure MSR regenerating codes by Shah et. al.

Information is increasing quickly, database owners have tendency to outsource their data to an external service provider called Cloud Computing. Using Cloud, clients can remotely store their data without burden of local data storage and maintenance. However, such service provider is untrusted, therefore there are some challenges in data security: integrity, availability and confidentiality. Since integrity and availability are prerequisite conditions of the existence of a system, we mainly focus on them rather than confidentiality. To ensure integrity and availability, researchers have proposed network coding-based POR (Proof of Retrievability) schemes that enable the servers to demonstrate whether the data is retrievable or not. However, most of network coding-based POR schemes are inefficient in data checking and also cannot prevent a common attack in POR: small corruption attack. In this paper, we propose a new network coding-based POR scheme using dispersal code in order to reduce cost in checking phase and also to prevent small corruption attack.

This paper addresses a robust methodology for developing a statistically sound, robust prognostic condition index and encapsulating this index as a series of highly accurate, transparent, human-readable rules. These rules can be used to further understand degradation phenomena and also provide transparency and trust for any underlying prognostic technique employed. A case study is presented on a wind turbine gearbox, utilising historical supervisory control and data acquisition (SCADA) data in conjunction with a physics of failure model. Training is performed without failure data, with the technique accurately identifying gearbox degradation and providing prognostic signatures up to 5 months before catastrophic failure occurred. A robust derivation of the Mahalanobis distance is employed to perform outlier analysis in the bivariate domain, enabling the rapid labelling of historical SCADA data on independent wind turbines. Following this, the RIPPER rule learner was utilised to extract transparent, human-readable rules from the labelled data. A mean classification accuracy of 95.98% of the autonomously derived condition was achieved on three independent test sets, with a mean kappa statistic of 93.96% reported. In total, 12 rules were extracted, with an independent domain expert providing critical analysis, two thirds of the rules were deemed to be intuitive in modelling fundamental degradation behaviour of the wind turbine gearbox.

In this paper, we consider the security of exact-repair regenerating codes operating at the minimum-storage-regenerating (MSR) point. The security requirement (introduced in Shah et. al.) is that no information about the stored data file must be leaked in the presence of an eavesdropper who has access to the contents of ℓ1 nodes as well as all the repair traffic entering a second disjoint set of ℓ2 nodes. We derive an upper bound on the size of a data file that can be securely stored that holds whenever ℓ2 ≤ d - k + 1. This upper bound proves the optimality of the product-matrix-based construction of secure MSR regenerating codes by Shah et. al.