Biblio

Responding to network security incidents requires interference with ongoing attacks to restore the security of services running on production systems. This approach prevents damage, but drastically impedes the collection of threat intelligence and the analysis of vulnerabilities, exploits, and attack strategies. We propose the live confinement of suspicious microservices into a sandbox network that allows to monitor and analyze ongoing attacks under quarantine and that retains an image of the vulnerable and open production network. A successful sandboxing requires that it happens completely transparent to and cannot be detected by an attacker. Therefore, we introduce a novel metric to measure the Quality of Deception (QoD) and use it to evaluate three proposed network deception mechanisms. Our evaluation results indicate that in our evaluation scenario in best case, an optimal QoD is achieved. In worst case, only a small downtime of approx. 3s per microservice (MS) occurs and thus a momentary drop in QoD to 70.26% before it converges back to optimum as the quarantined services are restored.

Cyber attacks against automobiles have increased over the last decade due to the expansion in attack surfaces. This is the result of modern automobiles having connections such as Bluetooth, WiFi, and other broadband services. While there has been numerous proposed solutions in the literature, none have been widely adopted as maintaining real-time message deliverability in the Controller Area Networks (CAN) outweighs proposed security solutions. Through iterative research, we have developed a solution which mitigates an attacker's impact on the CAN bus by using CAN's inherent features of arbitration, error detection and signaling, and fault confinement mechanism. The solution relies on an access controller and message priority thresholds added to the CAN data-link layer. The results provide no time delay for non-malicious traffic and mitigates bus impact of a subverted node attempting to fabricate messages at an unauthorized priority level.

The sheer size of IoT networks being deployed today presents an "attack surface" and poses significant security risks at a scale never before encountered. In other words, a single device/node in a network that becomes infected with malware has the potential to spread malware across the network, eventually ceasing the network functionality. Simply detecting and quarantining the malware in IoT networks does not guarantee to prevent malware propagation. On the other hand, use of traditional control theory for malware confinement is not effective, as most of the existing works do not consider real-time malware control strategies that can be implemented using uncertain infection information of the nodes in the network or have the containment problem decoupled from network performance. In this work, we propose a two-pronged approach, where a runtime malware detector (HaRM) that employs Hardware Performance Counter (HPC) values to detect the malware and benign applications is devised. This information is fed during runtime to a stochastic model predictive controller to confine the malware propagation without hampering the network performance. With the proposed solution, a runtime malware detection accuracy of 92.21% with a runtime of 10ns is achieved, which is an order of magnitude faster than existing malware detection solutions. Synthesizing this output with the model predictive containment strategy lead to achieving an average network throughput of nearly 200% of that of IoT networks without any embedded defense.

The effects of quantum confinement on the charge distribution in planar Double-Gate (DG) SOI (Siliconon-Insulator) MOSFETs were examined, for sub-10 nm SOI film thicknesses (tsi $łeq$ 10 nm), by modeling the potential experienced by the charge carriers as that of an an-harmonic oscillator potential, consistent with the inherent structural symmetry of nanoscale symmetric DGSOI MOSFETs. By solving the 1-D Poisson's equation using this potential, the results obtained were validated through comparisons with TCAD simulations. The present model satisfactorily predicted the electron density and channel charge density for a wide range of SOI channel thicknesses and gate voltages.

Self-assembled semiconductor quantum dots possess an intrinsic geometric symmetry due to the crystal periodic structure. In order to systematically analyze the symmetric properties of quantum dots' bound states resulting only from geometric confinement, we apply group representation theory. We label each bound state for two kinds of popular quantum dot shapes: pyramid and half ellipsoid with the irreducible representation of the corresponding symmetric groups, i.e., C4v and C2v, respectively. Our study completes all the possible irreducible representation cases of groups C4v and C2v. Using the character theory of point groups, we predict the selection rule for electric dipole induced transitions. We also investigate the impact of quantum dot aspect ratio on the symmetric properties of the state wavefunction. This research provides a solid foundation to continue exploring quantum dot symmetry reduction or broken phenomena because of strain, band-mixing and shape irregularity. The results will benefit the researchers who are interested in quantum dot symmetry related effects such as absorption or emission spectra, or those who are studying quantum dots using analytical or numerical simulation approaches.

A new kind of Square Lattice Photonic Crystal Fiber (SLPCF) is proposed, the first ring is formed by elliptical holes filled with ethanol. To regulate the dispersion and the confinement loss we put a circular air-holes with small diameters into the third ring of the cladding area. The diameter of the core is arranged as d2=2*A-d, where A is the pitch and d diameter of the air-holes. After simulations, we got a dispersion low as 0.0494 (ps/Km. nm) and a confinement loss also low as 2.6×10-7(dB/m) at a wavelength of 1.55 $μ$m. At 0.8 $μ$m we obtained a nonlinearity high as 60.95 (1/km. w) and a strong guiding light. Also, we compare the filled ethanol elliptical holes with the air filled elliptical holes of our proposed square lattice photonic crystal fiber. We use as a simulation method in this manuscript the two-dimensional FDTD method. The utilization of the proposed fiber is in the telecommunication transmission because of its low dispersion and low loss at the c-band and in the nonlinear applications.

To promote InGaP solar cell efficiency toward the theoretical limit, one promising approach is to incorporate multiple quantum wells (MQWs) into the InGaP host and improve its open-circuit voltage by facilitating radiative carrier recombination owing to carrier confinement. In this research, we demonstrate numerically that a strain-balanced (SB) In1-xGaxP/In1-yGayP MQW enhances confined carrier density while degrades the effective carrier mobility. However, a smart design of the MQW structure is possible by considering quantitatively the trade-off between carrier confinement effect and carrier transport, and MQW can be advantageous over the InGaP bulk material for boosting photovoltaic efficiency.

When vertically aligned carbon nanotube arrays (CNT forests) are heated by optical, electrical, or any other means, heat confinement in the lateral directions (i.e. perpendicular to the CNTs' axes), which stems from the anisotropic structure of the forest, is expected to play an important role. It has been found that, in spite of being primarily conductive along the CNTs' axes, focusing a laser beam on the sidewall of a CNT forest can lead to a highly localized hot region-an effect known as ``Heat Trap''-and efficient thermionic emission. This unusual heat confinement phenomenon has applications where the spread of heat has to be minimized, but electrical conduction is required, notably in energy conversion (e.g. vacuum thermionics and thermoelectrics). However, despite its strong scientific and practical importance, the existence and role of the lateral heat confinement in the Heat Trap effect have so far been elusive. In this work, for the first time, by using a rotating elliptical laser beam, we directly observe the existence of this lateral heat confinement and its corresponding effects on the unusual temperature rise during the Heat Trap effect.

Internet of Things (IoT) offers new opportunities for business, technology and science but it also raises new challenges in terms of security and privacy, mainly because of the inherent characteristics of this environment: IoT devices come from a variety of manufacturers and operators and these devices suffer from constrained resources in terms of computation, communication and storage. In this paper, we address the problem of trust establishment for IoT and propose a security solution that consists of a secure bootstrap mechanism for device identification as well as a message attestation mechanism for aggregate response validation. To achieve both security requirements, we approach the problem in a confined environment, named SubNets of Things (SNoT), where various devices depend on it. In this context, devices are uniquely and securely identified thanks to their environment and their role within it. Additionally, the underlying message authentication technique features signature aggregation and hence, generates one compact response on behalf of all devices in the subnet.

A tracking flow is a flow between an end user and a Web tracking service. We develop an extensive measurement methodology for quantifying at scale the amount of tracking flows that cross data protection borders, be it national or international, such as the EU28 border within which the General Data Protection Regulation (GDPR) applies. Our methodology uses a browser extension to fully render advertising and tracking code, various lists and heuristics to extract well known trackers, passive DNS replication to get all the IP ranges of trackers, and state-of-the art geolocation. We employ our methodology on a dataset from 350 real users of the browser extension over a period of more than four months, and then generalize our results by analyzing billions of web tracking flows from more than 60 million broadband and mobile users from 4 large European ISPs. We show that the majority of tracking flows cross national borders in Europe but, unlike popular belief, are pretty well confined within the larger GDPR jurisdiction. Simple DNS redirection and PoP mirroring can increase national confinement while sealing almost all tracking flows within Europe. Last, we show that cross boarder tracking is prevalent even in sensitive and hence protected data categories and groups including health, sexual orientation, minors, and others.

Millimeter Wave (mmWave) networks can deliver multi-Gbps wireless links that use extremely narrow directional beams. This provides us with a new way to exploit spatial reuse in order to scale network throughput. In this work, we present MilliNet, the first millimeter wave network that can exploit dense spatial reuse to allow many links to operate in parallel in a confined space and scale the wireless throughput with the number of clients. Results from a 60 GHz testbed show that MilliNet can deliver a total wireless network data rate of more than 38 Gbps for 10 clients which is 5.8× higher than current 802.11 mmWave standards.

Although virtual reality hardware is now widely available, the uptake of real walking is hindered by the fact that it requires often impractically large amounts of physical space. To address this, we present VirtualSpace, a novel system that allows overloading multiple users immersed in different VR experiences into the same physical space. VirtualSpace accomplishes this by containing each user in a subset of the physical space at all times, which we call tiles; app-invoked maneuvers then shuffle tiles and users across the entire physical space. This allows apps to move their users to where their narrative requires them to be while hiding from users that they are confined to a tile. We show how this enables VirtualSpace to pack four users into 16m2. In our study we found that VirtualSpace allowed participants to use more space and to feel less confined than in a control condition with static, pre-allocated space.

The growing number of devices we interact with require a convenient yet secure solution for user identification, authorization and authentication. Current approaches are cumbersome, susceptible to eavesdropping and relay attacks, or energy inefficient. In this paper, we propose a body-guided communication mechanism to secure every touch when users interact with a variety of devices and objects. The method is implemented in a hardware token worn on user's body, for example in the form of a wristband, which interacts with a receiver embedded inside the touched device through a body-guided channel established when the user touches the device. Experiments show low-power (uJ/bit) operation while achieving superior resilience to attacks, with the received signal at the intended receiver through the body channel being at least 20dB higher than that of an adversary in cm range.

SEAndroid is a mandatory access control (MAC) framework that can confine faulty applications on Android. Nevertheless, the effectiveness of SEAndroid enforcement depends on the employed policy. The growing complexity of Android makes it difficult for policy engineers to have complete domain knowledge on every system functionality. As a result, policy engineers sometimes craft over-permissive and ineffective policy rules, which unfortunately increased the attack surface of the Android system and have allowed multiple real-world privilege escalation attacks. We propose SPOKE, an SEAndroid Policy Knowledge Engine, that systematically extracts domain knowledge from rich-semantic functional tests and further uses the knowledge for characterizing the attack surface of SEAndroid policy rules. Our attack surface analysis is achieved by two steps: 1) It reveals policy rules that cannot be justified by the collected domain knowledge. 2) It identifies potentially over-permissive access patterns allowed by those unjustified rules as the attack surface. We evaluate SPOKE using 665 functional tests targeting 28 different categories of functionalities developed by Samsung Android Team. SPOKE successfully collected 12,491 access patterns for the 28 categories as domain knowledge, and used the knowledge to reveal 320 unjustified policy rules and 210 over-permissive access patterns defined by those rules, including one related to the notorious libstagefright vulnerability. These findings have been confirmed by policy engineers.

Context-sensitive graph grammars have been rigorous formalisms for specifying visual programming languages, as they possess sufficient expressive powers and intuitive forms. Efficient parsing mechanisms are essential to these formalisms. However, the existent parsing algorithms are either inefficient or confined to a minority of graph grammars. This paper introduces the notion of partial precedence, defines the partial precedence graph of a graph grammar and theoretically unveils the existence of a valid parsing path conforming to the topological orderings of the partial precedence graph. Then, it provides algorithms for computing the partial precedence graph and presents an approach to improving general parsing algorithms with the graph based on the drawn conclusion. It is shown that the approach can considerably improve the efficiency of general parsing algorithms.

Enabled by artificial intelligence techniques, we are witnessing the rise of a new paradigm of computational creativity support: mixed-initiative creative interfaces put human and computer in a tight interactive loop where each suggests, produces, evaluates, modifies, and selects creative outputs in response to the other. This paradigm could broaden and amplify creative capacity for all, but has so far remained mostly confined to artificial intelligence for game content generation, and faces many unsolved interaction design challenges. This workshop therefore convenes CHI and game researchers to advance mixed-initiative approaches to creativity support.

Existing distributed asynchronous graph processing systems employ checkpointing to capture globally consistent snapshots and rollback all machines to most recent checkpoint to recover from machine failures. In this paper we argue that recovery in distributed asynchronous graph processing does not require the entire execution state to be rolled back to a globally consistent state due to the relaxed asynchronous execution semantics. We define the properties required in the recovered state for it to be usable for correct asynchronous processing and develop CoRAL, a lightweight checkpointing and recovery algorithm. First, this algorithm carries out confined recovery that only rolls back graph execution states of the failed machines to affect recovery. Second, it relies upon lightweight checkpoints that capture locally consistent snapshots with a reduced peak network bandwidth requirement. Our experiments using real-world graphs show that our technique recovers from failures and finishes processing 1.5x to 3.2x faster compared to the traditional asynchronous checkpointing and recovery mechanism when failures impact 1 to 6 machines of a 16 machine cluster. Moreover, capturing locally consistent snapshots significantly reduces intermittent high peak bandwidth usage required to save the snapshots – the average reduction in 99th percentile bandwidth ranges from 22% to 51% while 1 to 6 snapshot replicas are being maintained.

Fast, accurate three dimensional reconstructions of plasma equilibria, crucial for physics interpretation of fusion data generated within confinement devices like stellarators/ tokamaks, are computationally very expensive and routinely require days, even weeks, to complete using serial approaches. Here, we present a parallel implementation of the three dimensional plasma reconstruction code, V3FIT. A formal analysis to identify the performance bottlenecks and scalability limits of this new parallel implementation, which combines both task and data parallelism, is presented. The theoretical findings are supported by empirical performance results on several thousands of processor cores of a Cray XC30 supercomputer. Parallel V3FIT is shown to deliver over 40X speedup, enabling fusion scientists to carry out three dimensional plasma equilibrium reconstructions at unprecedented scales in only a few hours (instead of in days/weeks) for the first time.

A semi-analytical model for internal optical losses at high power in a 1.5 μm laser diode with strong n-doping in the n-side of the optical confinement layer is created. The model includes intervalence band absorption by holes supplied by both current flow and two-photon absorption. The resulting losses are shown to be substantially lower than those in a similar, but weakly doped structure. Thus a significant improvement in the output power and efficiency by strong n-doping is predicted.

Despite the continuous shrinking of the transistor dimensions, advanced modeling tools going beyond the ballistic limit of transport are still critically needed to ensure accurate device investigations. For that purpose we present here a straight-forward approach to include phonon confinement effects into dissipative quantum transport calculations based on the effective mass approximation (EMA) and the k·p method. The idea is to scale the magnitude of the deformation potentials describing the electron-phonon coupling to obtain the same low-field mobility as with full-band simulations and confined phonons. This technique is validated by demonstrating that after adjusting the mobility value of n- and p-type silicon nanowire transistors, the resulting EMA and k·p I-V characteristics agree well with those derived from full-band studies.

We show high confinement thermally tunable, low loss (0.27 ± 0.04 dB/cm) Si3N4waveguides that are 42 cm long. We show that this platform can enable the miniaturization of traditionally bulky active OCT components.

We have presented a unique PT-VCSEL arrangement which experimentally demonstrates the process of optically controlled current confinement. Lessons learned will be transferred to future generations of solitary device which will be optimized with respect to the degree of confinement (depending on the parameters of the PT, in particular the current gain), threshold current and electro-optic efficiency.

We demonstrate high-speed operation of ultracompact electroabsorption modulators based on epsilon-near-zero confinement in indium oxide (In$_\textrm2$$_\textrm3$\$) on silicon using field-effect carrier density tuning. Additionally, we discuss strategies to enhance modulator performance and reduce confinement-related losses by introducing high-mobility conducting oxides such as cadmium oxide (CdO).

We present sandbox mining, a technique to confine an application to resources accessed during automatic testing. Sandbox mining first explores software behavior by means of automatic test generation, and extracts the set of resources accessed during these tests. This set is then used as a sandbox, blocking access to resources not used during testing. The mined sandbox thus protects against behavior changes such as the activation of latent malware, infections, targeted attacks, or malicious updates. The use of test generation makes sandbox mining a fully automatic process that can be run by vendors and end users alike. Our BOXMATE prototype requires less than one hour to extract a sandbox from an Android app, with few to no confirmations required for frequently used functionality.

Touch input promises intuitive interactions with digital content as it employs our experience of manipulating physical objects: digital content can be rotated, scaled, and translated using direct manipulation gestures. However, the reliance on analog also confines the scope of direct physical manipulation: the physical world provides no mechanism to interact with digital abstract content. As such, applications on touchscreen devices either only include limited functionalities or fallback on the traditional form-filling paradigm, which is tedious, slow, and error prone for touch input. My research focuses on designing a new UI framework to enable complex functionalities on touch screen devices by expanding direct physical manipulation to abstract content via objectification. I present two research projects, objectification of attributes and selection, which demonstrate considerable promises.