Biblio

Box queries on a dataset in a multidimensional data space are a type of query which specifies a set of allowed values for each dimension. Indexing a dataset in a multidimensional Non-ordered Discrete Data Space (NDDS) for supporting efficient box queries is becoming increasingly important in many application domains such as genome sequence analysis. The BoND-tree was recently introduced as an index structure specifically designed for box queries in an NDDS. Earlier work focused on developing strategies for building an effective BoND-tree to achieve high query performance. Developing efficient and effective techniques for deleting indexed vectors from the BoND-tree remains an open issue. In this paper, we present three deletion algorithms based on different underflow handling strategies in an NDDS. Our study shows that incorporating a new BoND-tree inspired heuristic can provide improved performance compared to the traditional underflow handling heuristics in NDDSs.

Critical business applications in domains ranging from technical support to healthcare increasingly rely on large-scale, automatically constructed knowledge graphs. These applications use the results of complex queries over knowledge graphs in order to help users in taking crucial decisions such as which drug to administer, or whether certain actions are compliant with all the regulatory requirements and so on. However, these knowledge graphs constantly evolve, and the newer versions may adversely impact the results of queries that the previously taken business decisions were based on. We propose a framework based on provenance polynomials to track the impact of knowledge graph changes on arbitrary SPARQL query results. Focusing on the deletion of facts, we show how to efficiently determine the queries impacted by the change, develop ways to incrementally maintain these polynomials, and present an efficient implementation on top of RDF graph databases. Our experimental evaluation over large-scale RDF/SPARQL benchmarks show the effectiveness of our proposal.

Searching and retrieving information from the Web is a primary activity needed to monitor the development and usage of Web resources. Possible benefits include improving user experience (e.g. by optimizing query results) and enforcing data/user security (e.g. by identifying harmful websites). Motivated by the lack of ready-to-use solutions, in this paper we present a flexible and accessible toolkit for structure and content mining, able to crawl, download, extract and index resources from the Web. While being easily configurable to work in the "surface" Web, our suite is specifically tailored to explore the Tor dark Web, i.e. the ensemble of Web servers composing the world's most famous darknet. Notably, the toolkit is not just a Web scraper, but it includes two mining modules, respectively able to prepare content to be fed to an (external) semantic engine, and to reconstruct the graph structure of the explored portion of the Web. Other than discussing in detail the design, features and performance of our toolkit, we report the findings of a preliminary run over Tor, that clarify the potential of our solution.

Recent advances on the integration of control systems with state of the art information technologies have brought into play new uncertainties, not only associated with the physical world, but also from a cyber-space's perspective. In cyber-physical environments, awareness and resilience are invaluable properties. The paper focuses on the development of an architecture relying on a hierarchical multi-agent framework for resilience enhancement. This framework was evaluated on a test-bed comprising several distributed computational devices and heterogeneous communications. Results from tests prove the relevance of the proposed approach.

Recent research has proposed a moving target defense (MTD) approach that actively changes transmission line susceptance to preclude stealthy false data injection (FDI) attacks against the state estimation of a smart grid. However, existing studies were often conducted under a less adversarial setting, in that they ignore the possibility that an alert attacker can also try to detect the activation of MTD and then cancel any FDI attack until they learn the new system configuration after MTD. Indeed, in this paper, we show that this can be achieved easily by the attacker. To improve the stealthiness of MTD against the attacker, we propose a hidden MTD approach that maintains the power flows of the whole grid after MTD. We develop an algorithm to construct the hidden MTD and analyze its feasibility condition when only a subset of transmission lines can adjust susceptance. Simulations are conducted to demonstrate the effectiveness of the hidden MTD against alert attackers under realistic settings.

Traditional countermeasures to relay attacks are difficult to implement on mobile devices due to hardware limitations. Establishing proximity of a payment device and terminal is the central notion of most relay attack countermeasures, and mobile devices offer new and exciting possibilities in this area of research. One such possibility is the use of on-board sensors to measure ambient data at both the payment device and terminal, with a comparison made to ascertain whether the device and terminal are in close proximity. This project focuses on the iPhone, specifically the iPhone 6S, and the potential use of its sensors to both establish proximity to a payment terminal and protect Apple Pay against relay attacks. The iPhone contains 12 sensors in total, but constraints introduced by payment schemes mean only 5 were deemed suitable to be used for this study. A series of mock transactions and relay attack attempts are enacted using an iOS application written specifically for this study. Sensor data is recorded, and then analysed to ascertain its accuracy and suitability for both proximity detection and relay attack countermeasures.

Web servers use SSL/TLS to establish secure communication between clients and servers. The mechanism of SSL/TLS relies on a key pair to validate the server and to protect the confidentiality of the data. However, many websites are running on third-party servers or on cloud environments where website owners have no control over the physical servers or the software including the operating systems but still need to trust and store the private key on the servers. While it is common to store the encrypted key on the disk, the web server still need a decrypted key inside the memory during the operation. Thus, an adversary could obtain the private key residing on the web server's memory. In this paper, we propose a secure enclave for a web server running the high privilege code that handles the secret keys inside an encrypted memory area by utilizing Intel Software Guard Extension (SGX) whereas other components of the web server outside the trusted computing base are left intact. The experimental results show 19% to 38% implementation overhead depending on which cipher suite is used and how a session key is handled.

The Controller Area Network (CAN) is still the most widely employed bus in the automotive sector. Its lack of security mechanisms led to a high number of attacks and consequently several security countermeasures were proposed, i.e., authentication protocols or intrusion detection mechanisms. We discuss vulnerabilities of the CAN data link layer that can be triggered from the application level with the use of an off the shelf CAN transceiver. Namely, due to the wired-AND design of the CAN bus, dominant bits will always overwrite recessive ones, a functionality normally used to assure priority for frames with low value identifiers. We exploit this characteristic and show Denial of Service attacks both on senders and receivers based on bit injections by using bit banging to maliciously control the CAN transceiver. We demonstrate the effects and limitations of such attacks through experimental analysis and discuss possible countermeasures. In particular, these attacks may have high impact on centralized authentication mechanisms that were frequently proposed in the literature since these attacks can place monitoring nodes in a bus-off state for certain periods of time.

In this paper, we consider an attack on a string of automated vehicles, or platoons, from a game-theoretic standpoint. Game theory enables us to ask the question of optimality in an adversarial environment; what is the optimal strategy that an attacker can use to disrupt the operation of automated vehicles, considering that the defenders are also optimally trying to maintain normal operation. We formulate a zero-sum game and find optimal controllers for different game parameters. A platoon is then simulated and its closed loop stability is then evaluated in the presence of an optimal attack. It is shown that with the constraint of optimality, the attacker cannot significantly degrade the stability of a vehicle platoon in nominal cases. It is motivated that in order to have an optimal solution that is nearly unstable, the game has to be formulated almost unfairly in favor of the attacker.

Personal health records (PHR) are an emerging health information exchange model, which facilitates PHR owners to efficiently manage their health data. Typically, PHRs are outsourced and stored in third-party cloud platforms. Although, outsourcing private health data to third-party platforms is an appealing solution for PHR owners, it may lead to significant privacy concerns, because there is a higher risk of leaking private data to unauthorized parties. As a way of ensuring PHR owners' control of their outsourced PHR data, attribute based encryption (ABE) mechanisms have been considered due to the fact that such schemes facilitate a mechanism of sharing encrypted data among a set of intended recipients. However, such existing PHR solutions suffer from inflexibility and scalability issues due to the limitations associated with the adopted ABE mechanisms. To address these issues, we propose a distributed multi-authority ABE scheme and thereby we show how a patient-centric, attribute based PHR sharing scheme which can provide flexible access for both professional users such as doctors as well as personal users such as family and friends is realized. We have shown that the proposed scheme supports on-demand user revocation as well as secure under standard security assumptions. In addition, the simulation results provide evidence for the fact that our scheme can function efficiently in practice. Furthermore, we have shown that the proposed scheme can cater the access requirements associated with distributed multiuser PHR sharing environments as well as more realistic and scalable compared with similar existing PHR sharing schemes.

Existing probabilistic privacy enforcement approaches permit the execution of a program that processes sensitive data only if the information it leaks is within the bounds specified by a given policy. Thus, to extract any information, users must manually design a program that satisfies the policy. In this work, we present a novel synthesis approach that automatically transforms a program into one that complies with a given policy. Our approach consists of two ingredients. First, we phrase the problem of determining the amount of leaked information as Bayesian inference, which enables us to leverage existing probabilistic programming engines. Second, we present two synthesis procedures that add uncertainty to the program's outputs as a way of reducing the amount of leaked information: an optimal one based on SMT solving and a greedy one with quadratic running time. We implemented and evaluated our approach on 10 representative programs from multiple application domains. We show that our system can successfully synthesize a permissive enforcement mechanism for all examples.

Mature push button tools have emerged for checking trace properties (e.g. secrecy or authentication) of security protocols. The case of indistinguishability-based privacy properties (e.g. ballot privacy or anonymity) is more complex and constitutes an active research topic with several recent propositions of techniques and tools. We explore a novel approach based on type systems and provide a (sound) type system for proving equivalence of protocols, for a bounded or an unbounded number of sessions. The resulting prototype implementation has been tested on various protocols of the literature. It provides a significant speed-up (by orders of magnitude) compared to tools for a bounded number of sessions and complements in terms of expressiveness other state-of-the-art tools, such as ProVerif and Tamarin: e.g., we show that our analysis technique is the first one to handle a faithful encoding of the Helios e-voting protocol in the context of an untrusted ballot box.

As system of systems (SoS) models become increasingly complex and interconnected a new approach is needed to capture the effects of humans within the SoS. Many real-life events have shown the detrimental outcomes of failing to account for humans in the loop. This research introduces a novel and cross-disciplinary methodology for modeling humans interacting with technologies to perform tasks within an SoS specifically within a layered physical security system use case. Metrics and formulations developed for this new way of looking at SoS termed sociotechnical SoS allow for the quantification of the interplay of effectiveness and efficiency seen in detection theory to measure the ability of a physical security system to detect and respond to threats. This methodology has been applied to a notional representation of a small military Forward Operating Base (FOB) as a proof-of-concept.

In any sufficiently complex software system there are experts, having a deeper understanding of parts of the system than others. However, it is not always clear who these experts are and which particular parts of the system they can provide help with. We propose a framework to elicit the expertise of developers and recommend experts by analyzing complexity measures over time. Furthermore, teams can detect those parts of the software for which currently no, or only few experts exist and take preventive actions to keep the collective code knowledge and ownership high. We employed the developed approach at a medium-sized company. The results were evaluated with a survey, comparing the perceived and the computed expertise of developers. We show that aggregated code metrics can be used to identify experts for different software components. The identified experts were rated as acceptable candidates by developers in over 90% of all cases.

The expeditious expansion of the networking technologies have remarkably driven the usage of the distributedcomputing as well as services, such as task offloading to the cloud. However, security and privacy concerns are restricting the implementations of cloud computing because of the threats from both outsiders and insiders. The primary alternative of protecting users' data is developing a Fully Homomorphic Encryption (FHE) scheme, which can cover both data protections and data processing in the cloud. Despite many previous attempts addressing this approach, none of the proposed work can simultaneously satisfy two requirements that include the non-noise accuracy and an efficiency execution. This paper focuses on the issue of FHE design and proposes a novel FHE scheme, which is called Optimal Fully Homomorphic Encryption (O-FHE). Our approach utilizes the properties of the Kronecker Product (KP) and designs a mechanism of achieving FHE, which consider both accuracy and efficiency. We have assessed our scheme in both theoretical proofing and experimental evaluations with the confirmed and exceptional results.

Emerging cyber-physical systems (CPS) often require collecting end users' data to support data-informed decision making processes. There has been a long-standing argument as to the tradeoff between privacy and data utility. In this paper, we adopt a multiparametric programming approach to rigorously study conditions under which data utility has to be sacrificed to protect privacy and situations where free-lunch privacy can be achieved, i.e., data can be concealed without hurting the optimality of the decision making underlying the CPS. We formalize the concept of free-lunch privacy, and establish various results on its existence, geometry, as well as efficient computation methods. We propose the free-lunch privacy mechanism, which is a pragmatic mechanism that exploits free-lunch privacy if it exists with the constant guarantee of optimal usage of data. We study the resilience of this mechanism against attacks that attempt to infer the parameter of a user's data generating process. We close the paper by a case study on occupancy-adaptive smart home temperature control to demonstrate the efficacy of the mechanism.

Data storage in cloud should come along with high safety and confidentiality. It is accountability of cloud service provider to guarantee the availability and security of client data. There exist various alternatives for storage services but confidentiality and complexity solutions for database as a service are still not satisfactory. Proposed system gives alternative solution for database as a service that integrates benefits of different services along with advance encryption techniques. It yields possibility of applying concurrency on encrypted data. This alternative provides supporting facility to connect dispersed clients with elimination of intermediate proxy by which simplicity can acquired. Performance of proposed system evaluated on basis of theoretical analyses.

The prevalence of mobile devices and location-based services (LBS) has generated great concerns regarding the LBS users' privacy, which can be compromised by statistical analysis of their movement patterns. A number of algorithms have been proposed to protect the privacy of users in such systems, but the fundamental underpinnings of such remain unexplored. Recently, the concept of perfect location privacy was introduced and its achievability was studied for anonymization-based LBS systems, where user identifiers are permuted at regular intervals to prevent identification based on statistical analysis of long time sequences. In this paper, we significantly extend that investigation by incorporating the other major tool commonly employed to obtain location privacy: obfuscation, where user locations are purposely obscured to protect their privacy. Since anonymization and obfuscation reduce user utility in LBS systems, we investigate how location privacy varies with the degree to which each of these two methods is employed. We provide: (1) achievability results for the case where the location of each user is governed by an i.i.d. process; (2) converse results for the i.i.d. case as well as the more general Markov Chain model. We show that, as the number of users in the network grows, the obfuscation-anonymization plane can be divided into two regions: in the first region, all users have perfect location privacy; and, in the second region, no user has location privacy.

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.

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).

The Border Gateway Protocol (BGP) has been used for decades as the de facto protocol to exchange reachability information among networks in the Internet. However, little is known about how this protocol is used to restrict reachability to selected destinations, e.g., that are under attack. While such a feature, BGP blackholing, has been available for some time, we lack a systematic study of its Internet-wide adoption, practices, and network efficacy, as well as the profile of blackholed destinations. In this paper, we develop and evaluate a methodology to automatically detect BGP blackholing activity in the wild. We apply our method to both public and private BGP datasets. We find that hundreds of networks, including large transit providers, as well as about 50 Internet exchange points (IXPs) offer blackholing service to their customers, peers, and members. Between 2014–2017, the number of blackholed prefixes increased by a factor of 6, peaking at 5K concurrently blackholed prefixes by up to 400 Autonomous Systems. We assess the effect of blackholing on the data plane using both targeted active measurements as well as passive datasets, finding that blackholing is indeed highly effective in dropping traffic before it reaches its destination, though it also discards legitimate traffic. We augment our findings with an analysis of the target IP addresses of blackholing. Our tools and insights are relevant for operators considering offering or using BGP blackholing services as well as for researchers studying DDoS mitigation in the Internet.

We have formalized the functional specification of HMAC-DRBG (NIST 800-90A), and we have proved its cryptographic security-that its output is pseudorandom–using a hybrid game-based proof. We have also proved that the mbedTLS implementation (C program) correctly implements this functional specification. That proof composes with an existing C compiler correctness proof to guarantee, end-to-end, that the machine language program gives strong pseudorandomness. All proofs (hybrid games, C program verification, compiler, and their composition) are machine-checked in the Coq proof assistant. Our proofs are modular: the hybrid game proof holds on any implementation of HMAC-DRBG that satisfies our functional specification. Therefore, our functional specification can serve as a high-assurance reference.

The paper introduces a smart system developed with sensors that is useful for internal and external security. The system is useful for people living in houses, apartments, high officials, bank, and offices. The system is developed in two phases one for internal security like home another is external security like open areas, streets. The system is consist of a mobile application, capacitive sensing, smart routing these valuable features to ensure safety of life and wealth. This security system is wireless sensor based which is an effective alternative of cctv cameras and other available security systems. Efficiency of this system is developed after going through practical studies and prototyping. The end result explains the feasibility rate, positive impact factor, reliability of the system. More research is possible in future based on this system this research explains that.