Exploiting code mobility for dynamic binary obfuscation

Software protection aims at protecting the integrity of software applications deployed on un-trusted hosts and being subject to illegal analysis. Within an un-trusted environment a possibly malicious user has complete access to system resources and tools in order to analyze and tamper with the application code. To address this research problem, we propose a novel binary obfuscation approach based on the deployment of an incomplete application whose code arrives from a trusted network entity as a flow of mobile code blocks which are arranged in memory with a different customized memory layout. This paper presents our approach to contrast reverse engineering by defeating static and dynamic analysis, and discusses its effectivenes

Design and Freeform Fabrication of Deployable Structures with Lattice Skins

Frontier environments—such as battlefields, hostile territories, remote locations, or outer space—drive the need for lightweight, deployable structures that can be stored in a compact configuration and deployed quickly and easily in the field. We introduce the concept of lattice skins to enable the design, solid freeform fabrication (SFF), and deployment of customizable structures with nearly arbitrary surface profile and lightweight multi-functionality. Using Duraform FLEX® material in a selective laser sintering machine, large deployable structures are fabricated in a nominal build chamber by either virtually collapsing them into a condensed form or decomposing them into smaller parts. Before fabrication, lattice sub-skins are added strategically beneath the surface of the part. The lattices provide elastic energy for folding and deploying the structure or constrain expansion upon application of internal air pressure. Nearly arbitrary surface profiles are achievable and internal space is preserved for subsequent usage. In this paper, we present the results of a set of experimental and computational models that are designed to provide proof of concept for lattice skins as a deployment mechanism in SFF and to demonstrate the effect of lattice structure on deployed shape.Mechanical Engineerin

An ESPC algorithm based approach to solve inventory deployment problem

Global competitiveness has enforced the hefty industries to become more customized. To compete in the market they are targeting the customers who want exotic products, and faster and reliable deliveries. Industries are exploring the option of satisfying a portion of their demand by converting strategically placed products, this helps in increasing the variability of product produced by them in short lead time. In this paper, authors have proposed a new hybrid evolutionary algorithm named Endosymbiotic-Psychoclonal (ESPC) algorithm to determine the amount and type of product to stock as a semi product in inventory. In the proposed work the ability of previously proposed Psychoclonal algorithm to exploit the search space has been increased by making antibodies and antigen more cooperative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results obtained, are compared with other evolutionary algorithms such as Genetic Algorithm (GA) and Simulated Annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained, and convergence time required to reach the optimal /near optimal value of the solution

Stochastic make-to-stock inventory deployment problem: an endosymbiotic psychoclonal algorithm based approach

Integrated steel manufacturers (ISMs) have no specific product, they just produce finished product from the ore. This enhances the uncertainty prevailing in the ISM regarding the nature of the finished product and significant demand by customers. At present low cost mini-mills are giving firm competition to ISMs in terms of cost, and this has compelled the ISM industry to target customers who want exotic products and faster reliable deliveries. To meet this objective, ISMs are exploring the option of satisfying part of their demand by converting strategically placed products, this helps in increasing the variability of product produced by the ISM in a short lead time. In this paper the authors have proposed a new hybrid evolutionary algorithm named endosymbiotic-psychoclonal (ESPC) to decide what and how much to stock as a semi-product in inventory. In the proposed theory, the ability of previously proposed psychoclonal algorithms to exploit the search space has been increased by making antibodies and antigen more co-operative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results compared with other evolutionary algorithms such as genetic algorithms (GA) and simulated annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained and convergence time required to reach the optimal/near optimal value of the solution

Adaptive online deployment for resource constrained mobile smart clients

Nowadays mobile devices are more and more used as a platform for applications. Contrary to prior generation handheld devices configured with a predefined set of applications, today leading edge devices provide a platform for flexible and customized application deployment. However, these applications have to deal with the limitations (e.g. CPU speed, memory) of these mobile devices and thus cannot handle complex tasks. In order to cope with the handheld limitations and the ever changing device context (e.g. network connections, remaining battery time, etc.) we present a middleware solution that dynamically offloads parts of the software to the most appropriate server. Without a priori knowledge of the application, the optimal deployment is calculated, that lowers the cpu usage at the mobile client, whilst keeping the used bandwidth minimal. The information needed to calculate this optimum is gathered on the fly from runtime information. Experimental results show that the proposed solution enables effective execution of complex applications in a constrained environment. Moreover, we demonstrate that the overhead from the middleware components is below 2%