Biblio

As wireless networks become more pervasive, the amount of the wireless data is rapidly increasing. One of the biggest challenges of wide adoption of distributed data storage is how to store these data securely. In this work, we study the frequency-based attack, a type of attack that is different from previously well-studied ones, that exploits additional adversary knowledge of domain values and/or their exact/approximate frequencies to crack the encrypted data. To cope with frequency-based attacks, the straightforward 1-to-1 substitution encryption functions are not sufficient. We propose a data encryption strategy based on 1-to-n substitution via dividing and emulating techniques to defend against the frequency-based attack, while enabling efficient query evaluation over encrypted data. We further develop two frameworks, incremental collection and clustered collection, which are used to defend against the global frequency-based attack when the knowledge of the global frequency in the network is not available. Built upon our basic encryption schemes, we derive two mechanisms, direct emulating and dual encryption, to handle updates on the data storage for energy-constrained sensor nodes and wireless devices. Our preliminary experiments with sensor nodes and extensive simulation results show that our data encryption strategy can achieve high security guarantee with low overhead.

From the Preface

As society rushes to digitize sensitive information and services, it is imperative that we adopt adequate security protections. However, such protections fundamentally conflict with the benefits we expect from commodity computers. In other words, consumers and businesses value commodity computers because they provide good performance and an abundance of features at relatively low costs. Meanwhile, attempts to build secure systems from the ground up typically abandon such goals, and hence are seldom adopted [Karger et al. 1991, Gold et al. 1984, Ames 1981].

In this book, a revised version of my doctoral dissertation, originally written while studying at Carnegie Mellon University, I argue that we can resolve the tension between security and features by leveraging the trust a user has in one device to enable her to securely use another commodity device or service, without sacrificing the performance and features expected of commodity systems.We support this premise over the course of the following chapters.

Introduction. This chapter introduces the notion of bootstrapping trust from one device or service to another and gives an overview of how the subsequent chapters fit together.
Background and related work. This chapter focuses on existing techniques for bootstrapping trust in commodity computers, specifically by conveying information about a computer's current execution environment to an interested party. This would, for example, enable a user to verify that her computer is free of malware, or that a remote web server will handle her data responsibly. 
Bootstrapping trust in a commodity computer. At a high level, this chapter develops techniques to allow a user to employ a small, trusted, portable device to securely learn what code is executing on her local computer. While the problem is simply stated, finding a solution that is both secure and usable with existing hardware proves quite difficult.
On-demand secure code execution. Rather than entrusting a user's data to the mountain of buggy code likely running on her computer, in this chapter, we construct an on-demand secure execution environment which can perform security sensitive tasks and handle private data in complete isolation from all other software (and most hardware) on the system. Meanwhile, non-security-sensitive software retains the same abundance of features and performance it enjoys today.
Using trustworthy host data in the network. Having established an environment for secure code execution on an individual computer, this chapter shows how to extend trust in this environment to network elements in a secure and efficient manner. This allows us to reexamine the design of network protocols and defenses, since we can now execute code on end hosts and trust the results within the network.
Secure code execution on untrusted hardware. Lastly, this chapter extends the user's trust one more step to encompass computations performed on a remote host (e.g., in the cloud).We design, analyze, and prove secure a protocol that allows a user to outsource arbitrary computations to commodity computers run by an untrusted remote party (or parties) who may subject the computers to both software and hardware attacks. Our protocol guarantees that the user can both verify that the results returned are indeed the correct results of the specified computations on the inputs provided, and protect the secrecy of both the inputs and outputs of the computations. These guarantees are provided in a non-interactive, asymptotically optimal (with respect to CPU and bandwidth) manner. 

Thus, extending a user's trust, via software, hardware, and cryptographic techniques, allows us to provide strong security protections for both local and remote computations on sensitive data, while still preserving the performance and features of commodity computers.

Cloud computing emerges as a new computing paradigm that aims to provide reliable, customized and quality of service guaranteed computation environments for cloud users. Applications and databases are moved to the large centralized data centers, called cloud. Due to resource virtualization, global replication and migration, the physical absence of data and machine in the cloud, the stored data in the cloud and the computation results may not be well managed and fully trusted by the cloud users. Most of the previous work on the cloud security focuses on the storage security rather than taking the computation security into consideration together. In this paper, we propose a privacy cheating discouragement and secure computation auditing protocol, or SecCloud, which is a first protocol bridging secure storage and secure computation auditing in cloud and achieving privacy cheating discouragement by designated verifier signature, batch verification and probabilistic sampling techniques. The detailed analysis is given to obtain an optimal sampling size to minimize the cost. Another major contribution of this paper is that we build a practical secure-aware cloud computing experimental environment, or SecHDFS, as a test bed to implement SecCloud. Further experimental results have demonstrated the effectiveness and efficiency of the proposed SecCloud.

An authenticated data structure (ADS) is a data structure whose operations can be carried out by an untrusted prover, the results of which a verifier can efficiently check as authentic. This is done by having the prover produce a compact proof that the verifier can check along with each operation's result. ADSs thus support outsourcing data maintenance and processing tasks to untrusted servers without loss of integrity. Past work on ADSs has focused on particular data structures (or limited classes of data structures), one at a time, often with support only for particular operations.

This paper presents a generic method, using a simple extension to a ML-like functional programming language we call λ• (lambda-auth), with which one can program authenticated operations over any data structure defined by standard type constructors, including recursive types, sums, and products. The programmer writes the data structure largely as usual and it is compiled to code to be run by the prover and verifier. Using a formalization of λ• we prove that all well-typed λ• programs result in code that is secure under the standard cryptographic assumption of collision-resistant hash functions. We have implemented λ• as an extension to the OCaml compiler, and have used it to produce authenticated versions of many interesting data structures including binary search trees, red-black+ trees, skip lists, and more. Performance experiments show that our approach is efficient, giving up little compared to the hand-optimized data structures developed previously.

Cloud storage has rapidly acquired popularity among users, constituting a seamless solution for the backup, synchronization, and sharing of large amounts of data. This technology, however, puts user data in the direct control of cloud service providers, which raises increasing security and privacy concerns related to the integrity of outsourced data, the accidental or intentional leakage of sensitive information, the profiling of user activities and so on. We present GORAM, a cryptographic system that protects the secrecy and integrity of the data outsourced to an untrusted server and guarantees the anonymity and unlinkability of consecutive accesses to such data. GORAM allows the database owner to share outsourced data with other clients, selectively granting them read and write permissions. GORAM is the first system to achieve such a wide range of security and privacy properties for outsourced storage. Technically, GORAM builds on a combination of ORAM to conceal data accesses, attribute-based encryption to rule the access to outsourced data, and zero-knowledge proofs to prove read and write permissions in a privacy-preserving manner. We implemented GORAM and conducted an experimental evaluation to demonstrate its feasibility.

Malicious applications can be introduced to attack users and services so as to gain financial rewards, individuals' sensitive information, company and government intellectual property, and to gain remote control of systems. However, traditional methods of malicious code detection, such as signature detection, behavior detection, virtual machine detection, and heuristic detection, have various weaknesses which make them unreliable. This paper presents the existing technologies of malicious code detection and a malicious code detection model is proposed based on behavior association. The behavior points of malicious code are first extracted through API monitoring technology and integrated into the behavior; then a relation between behaviors is established according to data dependence. Next, a behavior association model is built up and a discrimination method is put forth using pushdown automation. Finally, the exact malicious code is taken as a sample to carry out an experiment on the behavior's capture, association, and discrimination, thus proving that the theoretical model is viable.

There is an increasing need for wireless sensor networks (WSNs) to be more tightly integrated with the Internet. Several real world deployment of stand-alone wireless sensor networks exists. A number of solutions have been proposed to address the security threats in these WSNs. However, integrating WSNs with the Internet in such a way as to ensure a secure End-to-End (E2E) communication path between IPv6 enabled sensor networks and the Internet remains an open research issue. In this paper, the 6LoWPAN adaptation layer was extended to support both IPsec's Authentication Header (AH) and Encapsulation Security Payload (ESP). Thus, the communication endpoints in WSNs are able to communicate securely using encryption and authentication. The proposed AH and ESP compressed headers performance are evaluated via test-bed implementation in 6LoWPAN for IPv6 communications on IEEE 802.15.4 networks. The results confirm the possibility of implementing E2E security in IPv6 enabled WSNs to create a smooth transition between WSNs and the Internet. This can potentially play a big role in the emerging "Internet of Things" paradigm.

In this paper we present a secure and unclonable embedded system design that can target either an FPGA or an ASIC technology. The premise of the security is that the executed machine code and the executing environment (the embedded processor) will authenticate each other at a per-instruction basis using Physical Unclonable Functions (PUFs) that are built into the processor. The PUFs ensure that the execution of the binary code may only proceed if the binary is compiled with the correct intrinsic knowledge of the PUFs, and that such intrinsic knowledge is virtually unique to each processor and therefore unclonable. We will explain how to implement and integrate the PUFs into the processor's execution environment such that each instruction is authenticated and de-obfuscated on-demand and how to transform an ordinary binary executable into PUF-aware, obfuscated binaries. We will also present a prototype system on a Xilinx Spartan6-based FPGA board.

Demand Response (DR) is a promising technology for meeting the world's ever increasing energy demands without corresponding increase in energy generation, and for providing a sustainable alternative for integrating renewables into the power grid. As a result, interest in automated DR is increasing globally and has led to the development of OpenADR, an internationally recognized standard. In this paper, we propose security-enhancement mechanisms to provide DR participants with verifiable information that they can use to make informed decisions about the validity of received DR event information.

Identity management system has gained significance for any organization today for not only storing details of its employees but securing its sensitive information and safely managing access to its resources. This system being an enterprise based application has time taking deployment process, involving many complex and error prone steps. Also being globally used, its continuous running on servers lead to large carbon emissions. This paper proposes a novel architecture that integrates the Identity management system together with virtual appliance technology to reduce the overall deployment time of the system. It provides an Identity management system as pre-installed, pre-configured and ready to go solution that can be easily deployed even by a common user. The proposed architecture is implemented and the results have shown that there is decrease in deployment time and decrease in number of steps required in previous architecture. The hardware required by the application is also reduced as its deployed on virtual machine monitor platform, which can be installed on already used servers. This contributes to the green computing practices and gives costs benefits for enterprises. Also there is ease of migration of system from one server to another and the enterprises which do not want to depend on third party cloud for security and cost reasons, can easily deploy their identity management system in their own premises.
 

Smart grid is a cyber-physical system that integrates power infrastructures with information technologies. To facilitate efficient information exchange, wireless networks have been proposed to be widely used in the smart grid. However, the jamming attack that constantly broadcasts radio interference is a primary security threat to prevent the deployment of wireless networks in the smart grid. Hence, spread spectrum systems, which provide jamming resilience via multiple frequency and code channels, must be adapted to the smart grid for secure wireless communications, while at the same time providing latency guarantee for control messages. An open question is how to minimize message delay for timely smart grid communication under any potential jamming attack. To address this issue, we provide a paradigm shift from the case-by-case methodology, which is widely used in existing works to investigate well-adopted attack models, to the worst-case methodology, which offers delay performance guarantee for smart grid applications under any attack. We first define a generic jamming process that characterizes a wide range of existing attack models. Then, we show that in all strategies under the generic process, the worst-case message delay is a U-shaped function of network traffic load. This indicates that, interestingly, increasing a fair amount of traffic can in fact improve the worst-case delay performance. As a result, we demonstrate a lightweight yet promising system, transmitting adaptive camouflage traffic (TACT), to combat jamming attacks. TACT minimizes the message delay by generating extra traffic called camouflage to balance the network load at the optimum. Experiments show that TACT can decrease the probability that a message is not delivered on time in order of magnitude.

A physical unclonable function (PUF) is an integrated circuit (IC) that serves as a hardware security primitive due to its complexity and the unpredictability between its outputs and the applied inputs. PUFs have received a great deal of research interest and significant commercial activity. Public PUFs (PPUFs) address the crucial PUF limitation of being a secret-key technology. To some extent, the first generation of PPUFs are similar to SIMulation Possible, but Laborious (SIMPL) systems and one-time hardware pads, and employ the time gap between direct execution and simulation. The second PPUF generation employs both process variation and device aging which results in matched devices that are excessively difficult to replicate. The third generation leaves the analog domain and employs reconfigurability and device aging to produce digital PPUFs. We survey representative PPUF architectures, related public protocols and trusted information flows, and related testing issues. We conclude by identifying the most important, challenging, and open PPUF-related problems.

Online social networks are attracting billions of nowadays, both on a global scale as well as in social enterprise networks. Using distributed hash tables and peer-to-peer technology allows online social networks to be operated securely and efficiently only by using the resources of the user devices, thus alleviating censorship or data misuse by a single network operator. In this paper, we address the challenges that arise in implementing reliably and conveniently to use distributed data structures, such as lists or sets, in such a distributed hash-table-based online social network. We present a secure, distributed list data structure that manages the list entries in several buckets in the distributed hash table. The list entries are authenticated, integrity is maintained and access control for single users and also groups is integrated. The approach for secure distributed lists is also applied for prefix trees and sets, and implemented and evaluated in a peer-to-peer framework for social networks. Evaluation shows that the distributed data structure is convenient and efficient to use and that the requirements on security hold.

The trusted network connection is a hot spot in trusted computing field and the trust measurement and access control technology are used to deal with network security threats in trusted network. But the trusted network connection lacks fine-grained states and real-time measurement support for the client and the authentication mechanism is difficult to apply in the trusted network connection, it is easy to cause the loss of identity privacy. In order to solve the above-described problems, this paper presents a trust measurement scheme suitable for clients in the trusted network, the scheme integrates the following attributes such as authentication mechanism, state measurement, and real-time state measurement and so on, and based on the authentication mechanism and the initial state measurement, the scheme uses the real-time state measurement as the core method to complete the trust measurement for the client. This scheme presented in this paper supports both static and dynamic measurements. Overall, the characteristics of this scheme such as fine granularity, dynamic, real-time state measurement make it possible to make more fine-grained security policy and therefore it overcomes inadequacies existing in the current trusted network connection.

Mobile cloud computing is a combination of mobile computing and cloud computing that provides a platform for mobile users to offload heavy tasks and data on the cloud, thus, helping them to overcome the limitations of their mobile devices. However, while utilizing the mobile cloud computing technology users lose physical control of their data; this ultimately calls for the need of a data security protocol. Although, numerous such protocols have been proposed,none of them consider a cloudlet based architecture. A cloudlet is a reliable, resource-rich computer/cluster which is well-connected to the internet and is available to nearby mobile devices. In this paper, we propose a data security protocol for a distributed cloud architecture having cloudlet integrated with the base station, using the property of perfect forward secrecy. Our protocol not only protects data from any unauthorized user, but also prevents exposure of data to the cloud owner.
 

Probing attacks are serious threats on integrated circuits. Security products often include a protective layer called shield that acts like a digital fence. In this article, we demonstrate a new shield structure that is cryptographically secure. This shield is based on the newly proposed SIMON lightweight block cipher and independent mesh lines to ensure the security against probing attacks of the hardware located behind the shield. Such structure can be proven secure against state-of-the-art invasive attacks. For the first time in the open literature, we describe a chip designed with a digital shield, and give an extensive report of its cost, in terms of power, metal layer(s) to sacrifice and of logic (including the logic to connect it to the CPU). Also, we explain how “Through Silicon Vias” (TSV) technology can be used for the protection against both frontside and backside probing.

This paper presents an overview of the research project “High-Performance Hybrid Simulation/Measurement-Based Tools for Proactive Operator Decision-Support”, performed under the auspices of the U.S. Department of Energy grant DE-OE0000628. The objective of this project is to develop software tools to provide enhanced real-time situational awareness to support the decision making and system control actions of transmission operators. The integrated tool will combine high-performance dynamic simulation with synchrophasor measurement data to assess in real time system dynamic performance and operation security risk. The project includes: (i) The development of high-performance dynamic simulation software; (ii) the development of new computationally effective measurement-based tools to estimate operating margins of a power system in real time using measurement data from synchrophasors and SCADA; (iii) the development a hybrid framework integrating measurement-based and simulation-based approaches, and (iv) the use of cutting-edge visualization technology to display various system quantities and to visually process the results of the hybrid measurement-base/simulation-based security-assessment tool. Parallelization and high performance computing are utilized to enable ultrafast transient stability analysis that can be used in a real-time environment to quickly perform “what-if” simulations involving system dynamics phenomena. EPRI's Extended Transient Midterm Simulation Program (ETMSP) is modified and enhanced for this work. The contingency analysis is scaled for large-scale contingency analysis using MPI-based parallelization. Simulations of thousands of contingencies on a high performance computing machine are performed, and results show that parallelization over contingencies with MPI provides good scalability and computational gains. Different ways to reduce the I/O bottleneck have been also exprored. Thread-parallelization of the sparse linear solve is explored also through use of the SuperLU_MT library. Based on performance profiling results for the implicit method, the majority of CPU time is spent on the integration steps. Hence, in order to further improve the ETMSP performance, a variable time step control scheme for the original trapezoidal integration method has been developed and implemented. The Adams-Bashforth-Moulton predictor-corrector method was introduced and designed for ETMSP. Test results show superior performance with this method.

In this paper we explore the potential for securing a distributed Arabic Optical Character Recognition (OCR) system via cloud computing technology in a pervasive and mobile environment. The goal of the system is to achieve full accuracy, high speed and security when taking into account large vocabularies and amounts of documents. This issue has been resolved by integrating the recognition process and the security issue with multiprocessing and distributed computing technologies.

Radio Frequency IDentification (RFID) is a technique for speedy and proficient identification system, it has been around for more than 50 years and was initially developed for improving warfare machinery. RFID technology bridges two technologies in the area of Information and Communication Technologies (ICT), namely Product Code (PC) technology and Wireless technology. This broad-based rapidly expanding technology impacts business, environment and society. The operating principle of an RFID system is as follows. The reader starts a communication process by radiating an electromagnetic wave. This wave will be intercepted by the antenna of the RFID tag, placed on the item to be identified. An induced current will be created at the tag and will activate the integrated circuit, enabling it to send back a wave to the reader. The reader redirects information to the host where it will be processed. RFID is used for wide range of applications in almost every field (Health, education, industry, security, management ...). In this review paper, we will focus on agricultural and environmental applications.

Cloud computing significantly increased the security threats because intruders can exploit the large amount of cloud resources for their attacks. However, most of the current security technologies do not provide early warnings about such attacks. This paper presents a Finite State Hidden Markov prediction model that uses an adaptive risk approach to predict multi-staged cloud attacks. The risk model measures the potential impact of a threat on assets given its occurrence probability. The attacks prediction model was integrated with our autonomous cloud intrusion detection framework (ACIDF) to raise early warnings about attacks to the controller so it can take proactive corrective actions before the attacks pose a serious security risk to the system. According to our experiments on DARPA 2000 dataset, the proposed prediction model has successfully fired the early warning alerts 39.6 minutes before the launching of the LLDDoS1.0 attack. This gives the auto response controller ample time to take preventive measures.

This paper proposes a security architecture for an IoT transparent middleware. Focused on bringing real life objects to the virtual realm, the proposed architecture is deployable and comprises protection measures based on existent technologies for security such as AES, TLS and oAuth. This way, privacy, authenticity, integrity and confidentiality on data exchange services are integrated to provide security for generated smart objects and for involved users and services in a reliable and deployable manner.

With the rapid advancement in technology and the growing complexities in the interaction of these technologies and networks, it is even more important for countries and organizations to gain sustainable security advantage. Security advantage refers to the ability to manage and respond to threats and vulnerabilities with a proactive security posture. This is accomplished through effectively planning, managing, responding to and recovering from threats and vulnerabilities. However not many organizations and even countries, especially in the developing world, have been able to equip themselves with the necessary and sufficient know-how or ability to integrate knowledge and capabilities to achieve security advantage within their environment. Having a structured set of requirements or indicators to aid in progressively attaining different levels of maturity and capabilities is one important method to determine the state of cybersecurity readiness. The research introduces the Cybersecurity Capability Maturity Model (CM2), a 6-step process of progressive development of cybersecurity maturity and knowledge integration that ranges from a state of limited awareness and application of security controls to pervasive optimization of the protection of critical assets.

We survey the state-of-the-art on the Internet-of-Things (IoT) from a wireless communications point of view, as a result of the European FP7 project BUTLER which has its focus on pervasiveness, context-awareness and security for IoT. In particular, we describe the efforts to develop so-called (wireless) enabling technologies, aimed at circumventing the many challenges involved in extending the current set of domains (“verticals”) of IoT applications towards a “horizontal” (i.e. integrated) vision of the IoT. We start by illustrating current research effort in machine-to-machine (M2M), which is mainly focused on vertical domains, and we discuss some of them in details, depicting then the necessary horizontal vision for the future intelligent daily routine (“Smart Life”). We then describe the technical features of the most relevant heterogeneous communications technologies on which the IoT relies, under the light of the on-going M2M service layer standardization. Finally we identify and present the key aspects, within three major cross-vertical categories, under which M2M technologies can function as enablers for the horizontal vision of the IoT.

The emerging paradigm of cloud computing, e.g., Amazon Elastic Compute Cloud (EC2), promises a highly flexible yet robust environment for large-scale applications. Ideally, while multiple virtual machines (VM) share the same physical resources (e.g., CPUs, caches, DRAM, and I/O devices), each application should be allocated to an independently managed VM and isolated from one another. Unfortunately, the absence of physical isolation inevitably opens doors to a number of security threats. In this paper, we demonstrate in EC2 a new type of security vulnerability caused by competition between virtual I/O workloads-i.e., by leveraging the competition for shared resources, an adversary could intentionally slow down the execution of a targeted application in a VM that shares the same hardware. In particular, we focus on I/O resources such as hard-drive throughput and/or network bandwidth-which are critical for data-intensive applications. We design and implement Swiper, a framework which uses a carefully designed workload to incur significant delays on the targeted application and VM with minimum cost (i.e., resource consumption). We conduct a comprehensive set of experiments in EC2, which clearly demonstrates that Swiper is capable of significantly slowing down various server applications while consuming a small amount of resources.

In cloud data center, shared storage with good management is a main structure used for the storage of virtual machines (VM). In this paper, we proposed Hybrid VM storage (HVSTO), a privacy preserving shared storage system designed for the virtual machine storage in large-scale cloud data center. Unlike traditional shared storage, HVSTO adopts a distributed structure to preserve privacy of virtual machines, which are a threat in traditional centralized structure. To improve the performance of I/O latency in this distributed structure, we use a hybrid system to combine solid state disk and distributed storage. From the evaluation of our demonstration system, HVSTO provides a scalable and sufficient throughput for the platform as a service infrastructure.