A distributed memory for networked livecoding performance

The symbolic and improvisational nature of Livecoding requires a shared networking framework to be flexible and extensible, while at the same time providing support for synchronisation, persistence and redundancy. Above all the framework should be robust and available across a range of platforms. This paper proposes tuple space as a suitable framework for network communication in ensemble livecoding contexts. The role of tuple space as a concurrency framework and the associated timing aspects of the tuple space model are explored through Spaces, an implementation of tuple space for the Impromptu environment.

Continuous and non-intrusive identity verification in real-time environments based on free-text keystroke dynamics

Internet services are important part of daily activities for most of us. These services come with sophisticated authentication requirements which may not be handled by average Internet users. The management of secure passwords for example creates an extra overhead which is often neglected due to usability reasons. Furthermore, password-based approaches are applicable only for initial logins and do not protect against unlocked workstation attacks. In this paper, we provide a non-intrusive identity verification scheme based on behavior biometrics where keystroke dynamics based-on free-text is used continuously for verifying the identity of a user in real-time. We improved existing keystroke dynamics based verification schemes in four aspects. First, we improve the scalability where we use a constant number of users instead of whole user space to verify the identity of target user. Second, we provide an adaptive user model which enables our solution to take the change of user behavior into consideration in verification decision. Next, we identify a new distance measure which enables us to verify identity of a user with shorter text. Fourth, we decrease the number of false results. Our solution is evaluated on a data set which we have collected from users while they were interacting with their mail-boxes during their daily activities.

Algebraic analysis of Trivium-like ciphers

Trivium is a bit-based stream cipher in the final portfolio of the eSTREAM project. In this paper, we apply the approach of Berbain et al. to Trivium-like ciphers and perform new algebraic analyses on them, namely Trivium and its reduced versions: Trivium-N, Bivium-A and Bivium-B. In doing so, we answer an open question in the literature. We demonstrate a new algebraic attack on Bivium-A. This attack requires less time and memory than previous techniques which use the F4 algorithm to recover Bivium-A's initial state. Though our attacks on Bivium-B, Trivium and Trivium-N are worse than exhaustive keysearch, the systems of equations which are constructed are smaller and less complex compared to previous algebraic analysis. Factors which can affect the complexity of our attack on Trivium-like ciphers are discussed in detail.

Detecting distributed Denial-of-Service attacks and Flash Events

This thesis investigates and develops techniques for accurately detecting Internet-based Distributed Denial-of-Service (DDoS) Attacks where an adversary harnesses the power of thousands of compromised machines to disrupt the normal operations of a Web-service provider, resulting in significant down-time and financial losses. This thesis also develops methods to differentiate these attacks from similar-looking benign surges in web-traffic known as Flash Events (FEs). This thesis also addresses an intrinsic challenge in research associated with DDoS attacks, namely, the extreme scarcity of public domain datasets (due to legal and privacy issues) by developing techniques to realistically emulate DDoS attack and FE traffic.

Improved ultra-performance liquid chromatography with electrospray ionization quadrupole-time-of-flight high-definition mass spectrometry method for the rapid analysis of the chemical constituents of a typical medical formula: Liuwei Dihuang Wan

Liuwei Dihuang Wan (LWD), a classic Chinese medicinal formulae, has been used to improve or restore declined functions related to aging and geriatric diseases, such as impaired mobility, vision, hearing, cognition and memory. It has attracted increasingly much attention as one of the most popular and valuable herbal medicines. However, the systematic analysis of the chemical constituents of LDW is difficult and thus has not been well established. In this paper, a rapid, sensitive and reliable ultra-performance liquid chromatography with electrospray ionization quadrupole time-of-flight high-definition mass spectrometry (UPLC-ESI-Q-TOF-MS) method with automated MetaboLynx analysis in positive and negative ion mode was established to characterize the chemical constituents of LDW. The analysis was performed on a Waters UPLCTM HSS T3 using a gradient elution system. MS/MS fragmentation behavior was proposed for aiding the structural identification of the components. Under the optimized conditions, a total of 50 peaks were tentatively characterized by comparing the retention time and MS data. It is concluded that a rapid and robust platform based on UPLC-ESI-Q-TOF-MS has been successfully developed for globally identifying multiple-constituents of traditional Chinese medicine prescriptions. This is the first report on systematic analysis of the chemical constituents of LDW. This article is protected by copyright. All rights reserved.

The consistency of crash involvement recall across time

Introduction Road safety researchers rely heavily on self-report data to explore the aetiology of crash risk. However, researchers consistently acknowledge a range of limitations associated with this methodological approach (e.g., self-report bias), which has been hypothesised to reduce the predictive efficacy of scales. Although well researched in other areas, one important factor often neglected in road safety studies is the fallibility of human memory. Given accurate recall is a key assumption in many studies, the validity and consistency of self-report data warrants investigation. The aim of the current study was to examine the consistency of self-report data of crash history and details of the most recent reported crash on two separate occasions. Materials & Method A repeated measures design was utilised to examine the self-reported crash involvement history of 214 general motorists over a two month period. Results A number of interesting discrepancies were noted in relation to number of lifetime crashes reported by the participants and the descriptions of their most recent crash across the two occasions. Of the 214 participants who reported having been involved in a crash, 35 (22.3%) reported a lower number of lifetime crashes as Time 2, than at Time 1. Of the 88 drivers who reported no change in number of lifetime crashes, 10 (11.4%) described a different most recent crash. Additionally, of the 34 reporting an increase in the number of lifetime crashes, 29 (85.3%) of these described the same crash on both occasions. Assessed as a whole, at least 47.1% of participants made a confirmed mistake at Time 1 or Time 2. Conclusions These results raise some doubt in regard to the accuracy of memory recall across time. Given that self-reported crash involvement is the predominant dependent variable used in the majority of road safety research, this issue warrants further investigation. Replication of the study with a larger sample size that includes multiple recall periods would enhance understanding into the significance of this issue for road safety methodology.

Identifying the unknown in user space memory

This thesis is a study of how the contents of volatile memory on the Windows operating system can be better understood and utilised for the purposes of digital forensic investigations. It proposes several techniques to improve the analysis of memory, with a focus on improving the detection of unknown code such as malware. These contributions allow the creation of a more complete reconstruction of the state of a computer at acquisition time, including whether or not the computer has been infected by malicious code.

Algebraic analysis of Trivium-like ciphers

Trivium is a bit-based stream cipher in the final portfolio of the eSTREAM project. In this paper, we apply the algebraic attack approach of Berbain et al. to Trivium-like ciphers and perform new analyses on them. We demonstrate a new algebraic attack on Bivium-A. This attack requires less time and memory than previous techniques to recover Bivium-A's initial state. Though our attacks on Bivium-B, Trivium and Trivium-N are worse than exhaustive keysearch, the systems of equations which are constructed are smaller and less complex compared to previous algebraic analyses. We also answer an open question posed by Berbain et al. on the feasibility of applying their technique on Trivium-like ciphers. Factors which can affect the complexity of our attack on Trivium-like ciphers are discussed in detail. Analysis of Bivium-B and Trivium-N are omitted from this manuscript. The full paper is available on the IACR ePrint Archive.

The resistance of PRESENT-80 against related-key differential attacks

We examine the security of the 64-bit lightweight block cipher PRESENT-80 against related-key differential attacks. With a computer search we are able to prove that for any related-key differential characteristic on full-round PRESENT-80, the probability of the characteristic only in the 64-bit state is not higher than 2−64. To overcome the exponential (in the state and key sizes) computational complexity of the search we use truncated differences, however as the key schedule is not nibble oriented, we switch to actual differences and apply early abort techniques to prune the tree-based search. With a new method called extended split approach we are able to make the whole search feasible and we implement and run it in real time. Our approach targets the PRESENT-80 cipher however,with small modifications can be reused for other lightweight ciphers as well.

Cryptanalysis of LASH

We show that the LASH-x hash function is vulnerable to attacks that trade time for memory, including collision attacks as fast as 2(4x/11) and preimage attacks as fast as 2(4x/7). Moreover, we briefly mention heuristic lattice based collision attacks that use small memory but require very long messages that are expected to find collisions much faster than 2 x/2. All of these attacks exploit the designers’ choice of an all zero IV. We then consider whether LASH can be patched simply by changing the IV. In this case, we show that LASH is vulnerable to a 2(7x/8) preimage attack. We also show that LASH is trivially not a PRF when any subset of input bytes is used as a secret key. None of our attacks depend upon the particular contents of the LASH matrix – we only assume that the distribution of elements is more or less uniform.

Time-domain hydroelastic analysis of a flexible marine structure using state-space models

This article deals with time-domain hydroelastic analysis of a marine structure. The convolution terms associated with fluid memory effects are replaced by an alternative state-space representation, the parameters of which are obtained by using realization theory. The mathematical model established is validated by comparison to experimental results of a very flexible barge. Two types of time-domain simulations are performed: dynamic response of the initially inert structure to incident regular waves and transient response of the structure after it is released from a displaced condition in still water. The accuracy and the efficiency of the simulations based on the state-space model representations are compared to those that integrate the convolutions.

Time- vs. frequency-domain identification of parametric radiation force models for marine structures at zero speed

The dynamics describing the motion response of a marine structure in waves can be represented within a linear framework by the Cummins Equation. This equation contains a convolution term that represents the component of the radiation forces associated with fluid memory effects. Several methods have been proposed in the literature for the identification of parametric models to approximate and replace this convolution term. This replacement can facilitate the model implementation in simulators and the analysis of motion control designs. Some of the reported identification methods consider the problem in the time domain while other methods consider the problem in the frequency domain. This paper compares the application of these identification methods. The comparison is based not only on the quality of the estimated models, but also on the ease of implementation, ease of use, and the flexibility of the identification method to incorporate prior information related to the model being identified. To illustrate the main points arising from the comparison, a particular example based on the coupled vertical motion of a modern containership vessel is presented.

Methodology for developing real-time motorway traffic risk identification models using individual-vehicle data

Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

Integrating object locations in the memory representation of a spatial layout

The present study investigated how object locations learned separately are integrated and represented as a single spatial layout in memory. Two experiments were conducted in which participants learned a room-sized spatial layout that was divided into two sets of five objects. Results suggested that integration across sets was performed efficiently when it was done during initial encoding of the environment but entailed cost in accuracy when it was attempted at the time of memory retrieval. These findings suggest that, once formed, spatial representations in memory generally remain independent and integrating them into a single representation requires additional cognitive processes.

Characterising and predicting cyber attacks using the Cyber Attacker Model Profile (CAMP)

Purpose Ethnographic studies of cyber attacks typically aim to explain a particular profile of attackers in qualitative terms. The purpose of this paper is to formalise some of the approaches to build a Cyber Attacker Model Profile (CAMP) that can be used to characterise and predict cyber attacks. Design/methodology/approach The paper builds a model using social and economic independent or predictive variables from several eastern European countries and benchmarks indicators of cybercrime within the Australian financial services system. Findings The paper found a very strong link between perceived corruption and GDP in two distinct groups of countries – corruption in Russia was closely linked to the GDP of Belarus, Moldova and Russia, while corruption in Lithuania was linked to GDP in Estonia, Latvia, Lithuania and Ukraine. At the same time corruption in Russia and Ukraine were also closely linked. These results support previous research that indicates a strong link between been legitimate economy and the black economy in many countries of Eastern Europe and the Baltic states. The results of the regression analysis suggest that a highly skilled workforce which is mobile and working in an environment of high perceived corruption in the target countries is related to increases in cybercrime even within Australia. It is important to note that the data used for the dependent and independent variables were gathered over a seven year time period, which included large economic shocks such as the global financial crisis. Originality/value This is the first paper to use a modelling approach to directly show the relationship between various social, economic and demographic factors in the Baltic states and Eastern Europe, and the level of card skimming and card not present fraud in Australia.