Biblio

The evolution of electrical grids, both in terms of enhanced ICT functionalities to improve efficiency, reliability and economics, as well as the increasing penetration of renewable redistributed energy resources, results in a more sophisticated electrical infrastructure which poses new challenges from several perspectives, including resilience and quality of service analysis. In addition, the presence of interdependencies, which more and more characterize critical infrastructures (including the power sector), exacerbates the need for advanced analysis approaches, to be possibly employed since the early phases of the system design, to identify vulnerabilities and appropriate countermeasures. In this paper, we outline an approach to model and analyze smart grids and discuss the major challenges to be addressed in stochastic model-based analysis to account for the peculiarities of the involved system elements. Representation of dynamic and flexible behavior of generators and loads, as well as representation of the complex ICT control functions required to preserve and/or re-establish electrical equilibrium in presence of changes need to be faced to assess suitable indicators of the resilience and quality of service of the smart grid.

The Internet of Things (IOT) is a network of networks where massively large numbers of objects or things are interconnected to each other through the network. The Internet of Things brings along many new possibilities of applications to improve human comfort and quality of life. Complex systems such as the Internet of Things are difficult to manage because of the emergent behaviours that arise from the complex interactions between its constituent parts. Our key contribution in the paper is a proposed multiagent web for the Internet of Things. Corresponding data management architecture is also proposed. The multiagent architecture provides autonomic characteristics for IOT making the IOT manageable. In addition, the multiagent web allows for flexible processing on heterogeneous platforms as we leverage off web protocols such as HTTP and language independent data formats such as JSON for communications between agents. The architecture we proposed enables a scalable architecture and infrastructure for a web-scale multiagent Internet of Things.
 

In the security protocols of Efficient Mesh Security Association(EMSA), the key updating strategy is an effective method to ensure the security of communication. For the existing strategy of periodic automatic key updating, the PTK(Pairwise Transit Key) is updated through the complex 4-way handshake to produce each time. Once the update frequency of the PTK is faster, it will have a greater impact on throughput and delay of the network. On this basis, we propose a new strategy of dynamic key updating to ensure the safety and performance of wireless mesh networks. In the new strategy, mesh point(MP) and mesh authenticator(MA) negotiate a random function at the initial certification, and use the PTK which is generated by the 4-way handshake as the initial seed. When the PTK updating cycle comes, both sides generate the new keys using the random function, which do not have to generate a new PTK by complex 4-way handshake. The analysis of performance compared with existing strategies showed that the dynamic key updating strategy proposed in this paper have a larger increase in delay and throughput of the network.

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.

The Internet of Things (IoT) is here, more than 10 billion units are already connected and five times more devices are expected to be deployed in the next five years. Technological standarization and the management and fostering of rapid innovation by governments are among the main challenges of the IoT. However, security and privacy are the key to make the IoT reliable and trusted. Security mechanisms for the IoT should provide features such as scalability, interoperability and lightness. This paper addresses authentication and access control in the frame of the IoT. It presents Physical Unclonable Functions (PUF), which can provide cheap, secure, tamper-proof secret keys to authentify constrained M2M devices. To be successfully used in the IoT context, this technology needs to be embedded in a standardized identity and access management framework. On the other hand, Embedded Subscriber Identity Module (eSIM) can provide cellular connectivity with scalability, interoperability and standard compliant security protocols. The paper discusses an authorization scheme for a constrained resource server taking advantage of PUF and eSIM features. Concrete IoT uses cases are discussed (SCADA and building automation).

Virtualized environments are widely thought to cause problems for software-based random number generators (RNGs), due to use of virtual machine (VM) snapshots as well as fewer and believed-to-be lower quality entropy sources. Despite this, we are unaware of any published analysis of the security of critical RNGs when running in VMs. We fill this gap, using measurements of Linux's RNG systems (without the aid of hardware RNGs, the most common use case today) on Xen, VMware, and Amazon EC2. Despite CPU cycle counters providing a significant source of entropy, various deficiencies in the design of the Linux RNG makes its first output vulnerable during VM boots and, more critically, makes it suffer from catastrophic reset vulnerabilities. We show cases in which the RNG will output the exact same sequence of bits each time it is resumed from the same snapshot. This can compromise, for example, cryptographic secrets generated after resumption. We explore legacy-compatible countermeasures, as well as a clean-slate solution. The latter is a new RNG called Whirlwind that provides a simpler, more-secure solution for providing system randomness.
 

The technology of vehicle video detecting and tracking has been playing an important role in the ITS (Intelligent Transportation Systems) field during recent years. The occlusion phenomenon among vehicles is one of the most difficult problems related to vehicle tracking. In order to handle occlusion, this paper proposes an effective solution that applied Markov Random Field (MRF) to the traffic images. The contour of the vehicle is firstly detected by using background subtraction, then numbers of blocks with vehicle's texture and motion information are filled inside each vehicle. We extract several kinds of information of each block to process the following tracking. As for each occlusive block two groups of clique functions in MRF model are defined, which represents spatial correlation and motion coherence respectively. By calculating each occlusive block's total energy function, we finally solve the attribution problem of occlusive blocks. The experimental results show that our method can handle occlusion problems effectively and track each vehicle continuously.
 

This paper develops an opposition-based learning harmony search algorithm with mutation (OLHS-M) for solving global continuous optimization problems. The proposed method is different from the original harmony search (HS) in three aspects. Firstly, opposition-based learning technique is incorporated to the process of improvisation to enlarge the algorithm search space. Then, a new modified mutation strategy is instead of the original pitch adjustment operation of HS to further improve the search ability of HS. Effective self-adaptive strategy is presented to fine-tune the key control parameters (e.g. harmony memory consideration rate HMCR, and pitch adjustment rate PAR) to balance the local and global search in the evolution of the search process. Numerical results demonstrate that the proposed algorithm performs much better than the existing improved HS variants that reported in recent literature in terms of the solution quality and the stability.

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.

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.

Using heterogeneous clouds has been considered to improve performance of big-data analytics for healthcare platforms. However, the problem of the delay when transferring big-data over the network needs to be addressed. The purpose of this paper is to analyze and compare existing cloud computing environments (PaaS, IaaS) in order to implement middleware services. Understanding the differences and similarities between cloud technologies will help in the interconnection of healthcare platforms. The paper provides a general overview of the techniques and interfaces for cloud computing middleware services, and proposes a cloud architecture for healthcare. Cloud middleware enables heterogeneous devices to act as data sources and to integrate data from other healthcare platforms, but specific APIs need to be developed. Furthermore, security and management problems need to be addressed, given the heterogeneous nature of the communication and computing environment. The present paper fills a gap in the electronic healthcare register literature by providing an overview of cloud computing middleware services and standardized interfaces for the integration with medical devices.

Physical-layer authentication techniques exploit the unique properties of the wireless medium to enhance traditional higher-level authentication procedures. We propose to reduce the higher-level authentication overhead by using a state-of-the-art multi-target tracking technique based on Gaussian processes. The proposed technique has the additional advantage that it is capable of automatically learning the dynamics of the trusted user's channel response and the time-frequency fingerprint of intruders. Numerical simulations show very low intrusion rates, and an experimental validation using a wireless test bed with programmable radios demonstrates the technique's effectiveness.

Physical-layer authentication techniques exploit the unique properties of the wireless medium to enhance traditional higher-level authentication procedures. We propose to reduce the higher-level authentication overhead by using a state-of-the-art multi-target tracking technique based on Gaussian processes. The proposed technique has the additional advantage that it is capable of automatically learning the dynamics of the trusted user's channel response and the time-frequency fingerprint of intruders. Numerical simulations show very low intrusion rates, and an experimental validation using a wireless test bed with programmable radios demonstrates the technique's effectiveness.

A novel physical layer authentication scheme is proposed in this paper by exploiting the time-varying carrier frequency offset (CFO) associated with each pair of wireless communications devices. In realistic scenarios, radio frequency oscillators in each transmitter-and-receiver pair always present device-dependent biases to the nominal oscillating frequency. The combination of these biases and mobility-induced Doppler shift, characterized as a time-varying CFO, can be used as a radiometric signature for wireless device authentication. In the proposed authentication scheme, the variable CFO values at different communication times are first estimated. Kalman filtering is then employed to predict the current value by tracking the past CFO variation, which is modeled as an autoregressive random process. To achieve the proposed authentication, the current CFO estimate is compared with the Kalman predicted CFO using hypothesis testing to determine whether the signal has followed a consistent CFO pattern. An adaptive CFO variation threshold is derived for device discrimination according to the signal-to-noise ratio and the Kalman prediction error. In addition, a software-defined radio (SDR) based prototype platform has been developed to validate the feasibility of using CFO for authentication. Simulation results further confirm the effectiveness of the proposed scheme in multipath fading channels.
 

Conventional cellular systems are dimensioned according to a worst case scenario, and they are designed to ensure ubiquitous coverage with an always-present wireless channel irrespective of the spatial and temporal demand of service. A more energy conscious approach will require an adaptive system with a minimum amount of overhead that is available at all locations and all times but becomes functional only when needed. This approach suggests a new clean slate system architecture with a logical separation between the ability to establish availability of the network and the ability to provide functionality or service. Focusing on the physical layer frame of such an architecture, this paper discusses and formulates the overhead reduction that can be achieved in next generation cellular systems as compared with the Long Term Evolution (LTE). Considering channel estimation as a performance metric whilst conforming to time and frequency constraints of pilots spacing, we show that the overhead gain does not come at the expense of performance degradation.
 

Novel Internet services are emerging around an increasing number of sensors and actuators in our surroundings, commonly referred to as smart devices. Smart devices, which form the backbone of the Internet of Things (IoT), enable alternative forms of user experience by means of automation, convenience, and efficiency. At the same time new security and safety issues arise, given the Internet-connectivity and the interaction possibility of smart devices with human's proximate living space. Hence, security is a fundamental requirement of the IoT design. In order to remain interoperable with the existing infrastructure, we postulate a security framework compatible to standard IP-based security solutions, yet optimized to meet the constraints of the IoT ecosystem. In this ongoing work, we first identify necessary components of an interoperable secure End-to-End communication while incorporating Public-key Cryptography (PKC). To this end, we tackle involved computational and communication overheads. The required components on the hardware side are the affordable hardware acceleration engines for cryptographic operations and on the software side header compression and long-lasting secure sessions. In future work, we focus on integration of these components into a framework and the evaluation of an early prototype of this framework.

Novel Internet services are emerging around an increasing number of sensors and actuators in our surroundings, commonly referred to as smart devices. Smart devices, which form the backbone of the Internet of Things (IoT), enable alternative forms of user experience by means of automation, convenience, and efficiency. At the same time new security and safety issues arise, given the Internet-connectivity and the interaction possibility of smart devices with human's proximate living space. Hence, security is a fundamental requirement of the IoT design. In order to remain interoperable with the existing infrastructure, we postulate a security framework compatible to standard IP-based security solutions, yet optimized to meet the constraints of the IoT ecosystem. In this ongoing work, we first identify necessary components of an interoperable secure End-to-End communication while incorporating Public-key Cryptography (PKC). To this end, we tackle involved computational and communication overheads. The required components on the hardware side are the affordable hardware acceleration engines for cryptographic operations and on the software side header compression and long-lasting secure sessions. In future work, we focus on integration of these components into a framework and the evaluation of an early prototype of this framework.

As recently shown in 2013, Android-driven smartphones and tablet PCs are vulnerable to so-called cold boot attacks. With physical access to an Android device, forensic memory dumps can be acquired with tools like FROST that exploit the remanence effect of DRAM to read out what is left in memory after a short reboot. While FROST can in some configurations be deployed to break full disk encryption, encrypted user partitions are usually wiped during a cold boot attack, such that a post-mortem analysis of main memory remains the only source of digital evidence. Therefore, we provide an in-depth analysis of Android's memory structures for system and application level memory. To leverage FROST in the digital investigation process of Android cases, we provide open-source Volatility plugins to support an automated analysis and extraction of selected Dalvik VM memory structures.

This paper proposes an analysis method of power grids vulnerability based on complex networks. The method effectively combines the degree and betweenness of nodes or lines into a new index. Through combination of the two indexes, the new index can help to analyze the vulnerability of power grids. Attacking the line of the new index can obtain a smaller size of the largest cluster and global efficiency than that of the pure degree index or betweenness index. Finally, the fault simulation results of IEEE 118 bus system show that the new index can reveal the vulnerability of power grids more effectively.

The Philips audio fingerprint[1] has been used for years, but its robustness against external noise has not been studied accurately. This paper shows the Philips fingerprint is noise resistant, and is capable of recognizing music that is corrupted by noise at a -4 to -7 dB signal to noise ratio. In addition, the drawbacks of the Philips fingerprint are addressed by utilizing a “Power Mask” in conjunction with the Philips fingerprint during the matching process. This Power Mask is a weight matrix given to the fingerprint bits, which allows mismatched bits to be penalized according to their relevance in the fingerprint. The effectiveness of the proposed fingerprint was evaluated by experiments using a database of 1030 songs and 1184 query files that were heavily corrupted by two types of noise at varying levels. Our experiments show the proposed method has significantly improved the noise resistance of the standard Philips fingerprint.

In recent years, Attribute Based Access Control (ABAC) has evolved as the preferred logical access control methodology in the Department of Defense and Intelligence Community, as well as many other agencies across the federal government. Gartner recently predicted that “by 2020, 70% of enterprises will use attribute-based access control (ABAC) as the dominant mechanism to protect critical assets, up from less that 5% today.” A definition and introduction to ABAC can be found in NIST Special Publication 800-162, Guide to Attribute Based Access Control (ABAC) Definition and Considerations and Intelligence Community Policy Guidance (ICPG) 500.2, Attribute-Based Authorization and Access Management. Within ABAC, attributes are used to make critical access control decisions, yet standards for attribute assurance have just started to be researched and documented. This presentation outlines factors influencing attributes that an authoritative body must address when standardizing attribute assurance and proposes some notional implementation suggestions for consideration. Attribute Assurance brings a level of confidence to attributes that is similar to levels of assurance for authentication (e.g., guidelines specified in NIST SP 800-63 and OMB M-04-04). There are three principal areas of interest when considering factors related to Attribute Assurance. Accuracy establishes the policy and technical underpinnings for semantically and syntactically correct descriptions of Subjects, Objects, or Environmental conditions. Interoperability considers different standards and protocols used for secure sharing of attributes between systems in order to avoid compromising the integrity and confidentiality of the attributes or exposing vulnerabilities in provider or relying systems or entities. Availability ensures that the update and retrieval of attributes satisfy the application to which the ABAC system is applied. In addition, the security and backup capability of attribute repositories need to be considered. Similar to a Level of Assurance (LOA), a Level of Attribute Assurance (LOAA) assures a relying party that the attribute value received from an Attribute Provider (AP) is accurately associated with the subject, resource, or environmental condition to which it applies. An Attribute Provider (AP) is any person or system that provides subject, object (or resource), or environmental attributes to relying parties regardless of transmission method. The AP may be the original, authoritative source (e.g., an Applicant). The AP may also receive information from an authoritative source for repacking or store-and-forward (e.g., an employee database) to relying parties or they may derive the attributes from formulas (e.g., a credit score). Regardless of the source of the AP's attributes, the same standards should apply to determining the LOAA. As ABAC is implemented throughout government, attribute assurance will be a critical, limiting factor in its acceptance. With this presentation, we hope to encourage dialog between attribute relying parties, attribute providers, and federal agencies that will be defining standards for ABAC in the immediate future.
 

Network virtualization sits firmly on the Internet evolutionary path allowing researchers to experiment with novel clean-slate designs over the production network and practitioners to manage multi-tenants infrastructures in a flexible and scalable manner. In such scenarios, isolation between virtual networks is often intended as purely logical: this is the case of address space isolation or flow space isolation. This approach neglects the effect that network virtualization has on resource allocation network-wide. In this work we investigate the price paid by a purely logical approach in terms of performance degradation. This performance loss is paid by the actual users of a multi-tenants datacenter network. We propose a solution to this problem leveraging on a new network virtualization primitive, namely an online link utilization feedback mechanism. It provides each tenant with the necessary information to make efficient use of network resources. We evaluate our solution trough a real implementation exploiting the OpenFlow protocol. Empirical results confirm that the proposed scheme is able to support tenants in exploiting virtualized network resources effectively.
 

Identity verification plays an important role in creating trust in the economic system. It can, and should, be done in a way that doesn't decrease individual privacy.

In the paper a programmable management framework for SDN networks is presented. The concept is in-line with SDN philosophy - it can be programmed from scratch. The implemented management functions can be case dependent. The concept introduces a new node in the SDN architecture, namely the SDN manager. In compliance with the latest trends in network management the approach allows for embedded management of all network nodes and gradual implementation of management functions providing their code lifecycle management as well as the ability to on-the-fly code update. The described concept is a bottom-up approach, which key element is distributed execution environment (PDEE) that is based on well-established technologies like OSGI and FIPA. The described management idea has strong impact on the evolution of the SDN architecture, because the proposed distributed execution environment is a generic one, therefore it can be used not only for the management, but also for distributing of control or application functions.
 

The dynamic nature of the Web 2.0 and the heavy obfuscation of web-based attacks complicate the job of the traditional protection systems such as Firewalls, Anti-virus solutions, and IDS systems. It has been witnessed that using ready-made toolkits, cyber-criminals can launch sophisticated attacks such as cross-site scripting (XSS), cross-site request forgery (CSRF) and botnets to name a few. In recent years, cyber-criminals have targeted legitimate websites and social networks to inject malicious scripts that compromise the security of the visitors of such websites. This involves performing actions using the victim browser without his/her permission. This poses the need to develop effective mechanisms for protecting against Web 2.0 attacks that mainly target the end-user. In this paper, we address the above challenges from information flow control perspective by developing a framework that restricts the flow of information on the client-side to legitimate channels. The proposed model tracks sensitive information flow and prevents information leakage from happening. The proposed model when applied to the context of client-side web-based attacks is expected to provide a more secure browsing environment for the end-user.