Keynote : Detection of and defense against distributed denial-of-service (DDoS) attacks

Distributed denial-of-service (DDoS) attacks typically exhaust bandwidth, processing capacity, or memory of a targeted machine, service or network. Despite enormous efforts in combating DDoS attacks in the past decade, DDoS attacks are still a serious threat to the security of cyberspace. In this talk I shall outline the recent efforts of my research group in detection of and defence against DDoS attacks. In particular, this talk will concentrate on the following three critical issues related to DDoS attacks: (1) Traceback of DDoS attacks; (2) Detection of low-rate DDoS attacks; and (3) Discriminating DDoS attacks from flash crowds.

Kinect crowd interaction

Most of the state-of-the-art commercial simulation software mainly focuses on providing realistic animations and convincing artificial intelligence to avatars in the scenario. However, works on how to trigger the events and avatar reactions in the scenario in a natural and intuitive way are less noticed and developed. Typical events are usually triggered by predefined timestamps. Once the events are set, there is no easy way to interactively generate new events while the scene is running and therefore difficult to dynamically affect the avatar reactions. Based on this situation, we propose a framework to use human gesture as input to trigger events within a DI-Guy simulation scenario in real-time, which could greatly help users to control events and avatar reactions in the scenario. By implementing such a framework, we will be able to identify user’s intentions interactively and ensure that the avatars make corresponding reactions.

Flash-floods : genre subversion and the abject erotic in Dorothy Porter’s The monkey’s mask and El Dorado

When discussing her verse novels, Dorothy Porter explicitly stated that she loved to ‘write bad’. This paper will argue that it was Porter’s engagement with the verse novel form and genre subversion, most notably seen with her detective and crime thriller verse novels The monkey’s mask and El Dorado, that allows for a destabilisation of traditionally established genre conventions, which in turn provide a narrative foundation for Porter’s use of abject erotic imagery.

In both The monkey’s mask and El Dorado there are several types of ‘bodies’ to be examined: the body of the verse narrative, the bodies of the characters subjected to crime, the body of poetry that is referred to as evidence, and the abject eroticised body. Extending upon the studies of Rose Lucas (1997) and Fleur Diamond (1999), this paper contends that it is Porter’s engagement with the abject erotic, as informed by Julia Kristeva’s (1982) theory of the abject and Johanna Blakley’s (1995) discussion of the abject in relation to eroticism, that allows Porter to subvert the phallocentric limitations upheld through the crime fiction genre and offer an alternative representation for lesbian sexuality and desire.

Patchwork-based stereo audio watermarking against de-synchronization attack

Audio watermarking schemes using patchworkbased algorithm have good robustness against majority of the watermarking attacks. However, these watermarking schemes are vulnerable to de-synchronization attack. This paper proposes a patchwork-based watermarking scheme for stereo audio signals to address this problem. To improve the robustness, the proposed method exploits the similarities of both channels in the stereo audio signals. Given a stereo audio signal, we first compute the discrete cosine transform (DCT) of both channels, which gives two sets of DCT coefficients. Then DCT segments are formed form DCT coefficients belong to a certain frequency range. The DCT segment formation is determined by a pseudonoise (PN) sequence which acts as a secret key. Then watermark bits are embedded into DCT segments by modifying the DCT coefficients. In the decoding process the secret key is used to extract the watermark bits embedded in the DCT segments. Simulation results illustrate the effectiveness of the proposed method against de-synchronization attack, compared to latest patchwork-based audio watermarking scheme. Besides, the proposed algorithm also gives better robustness against other conventional attacks.

A modified moment-based image watermarking method robust to cropping attack

Developing a watermarking method that is robust to cropping attack is a challenging task in image watermarking. The moment-based watermarking schemes show good robustness to common signal processing attacks and some geometric attacks but are sensitive to cropping attack. In this paper, we modify the moment-based approach to deal with cropping attack. Firstly, we find the probability density function (pdf) of the pixel value distribution from the original image. Secondly, we reshape and normalize the pdf of the pixel value distribution (PPVD) to form a two dimensional image. Then, the moment invariants are calculated from the PPVD image. Since PPVD is insensitive to cropping, the proposed method is robust to cropping attack. Besides, it also has high robustness against other common attacks. Experimental results demonstrate the effectiveness of the proposed method.

Crowd detection from still images

The analysis of human crowds has widespread uses from law enforcement to urban engineering and traffic management. All of these require a crowd to first be detected, which is the problem addressed in this paper. Given an image, the algorithm we propose segments it into crowd and non-crowd regions. The main idea is to capture two key properties of crowds: (i) on a narrow scale, its basic element should look like a human (only weakly so, due to low resolution, occlusion, clothing variation etc.), while (ii) on a larger scale, a crowd inherently contains repetitive appearance elements. Our method exploits this by building a pyramid of sliding windows and quantifying how “crowd-like” each level of the pyramid is using an underlying statistical model based on quantized SIFT features. The two aforementioned crowd properties are captured by the resulting feature vector of window responses, describing the degree of crowd-like appearance around an image location as the surrounding spatial extent is increased.

An attack-resistant hybrid data-privatization method with low information loss

We examine a recent proposal for data-privatization by testing it against well-known attacks, we show that all of these attacks successfully retrieve a relatively large (and unacceptable) portion of the original data. We then indicate how the data-privatization method examined can be modified to assist it to withstand these attacks and compare the performance of the two approaches. We also show that the new method has better privacy and lower information loss than the former method.

A recognition tool for transient ischaemic attack

Background: Scoring systems exist to assist rapid identification of acute stroke but not for the more challenging diagnosis of transient ischaemic attack (TIA). Aim: To develop a clinical scoring system to assist with diagnosis of TIA. Methods: We developed and validated a clinical scoring system for identification of TIA patients. Logistic regression analysis was employed. Results: Our development cohort comprised 3216 patients. The scoring system included nine clinically useful predictive variables. After adjustment to reflect the greater seriousness of missing true TIA patients (a 2:1 cost ratio), 97% of TIA and 24% of non-TIA patients were accurately identified. Our results were confirmed during prospective validation. Conclusions: This simple scoring system performs well and could be used to facilitate accurate detection of TIA.

Neighbourhood-pair attack in social network data publishing

Vertex re-identification is one of the significant and challenging problems in social network. In this paper, we show a new type of vertex reidentification attack called neighbourhood-pair attack. This attack utilizes the neighbourhood topologies of two connected vertices. We show both theoretically and empirically that this attack is possible on anonymized social network and has higher re-identification rate than the existing structural attacks.

Packet faking attack: a novel attack and detection mechanism in OppNets

 Security is a major challenge in Opportunistic Networks (OppNets) due to its characteristics of being an open medium with dynamic topology, there is neither a centralized management nor clear lines of defence. A packet dropping attack is one of the major security threats in OppNets as neither source nodes nor destination nodes have any knowledge of when or where a packet will be dropped. In this paper, we present a novel attack and detection mechanism against a special type of packet dropping where the malicious node drops one packet or more and injects a new fake packet instead. Our novel detection mechanism is very powerful and has very high accuracy. It relies on a very simple yet powerful idea; the creation time of each packet. Significant results show this robust mechanism achieves a very high accuracy and detection rate.

Analysis of insiders attack mitigation strategies

Insider threat has become a serious information security issues within organizations. In this paper, we analyze the problem of insider threats with emphases on the Cloud computing platform. Security is one of the major anxieties when planning to adopt the Cloud. This paper will contribute towards the conception of mitigation strategies that can be relied on to solve the malicious insider threats. While Cloud computing relieves organizations from the burden of the data management and storage costs, security in general and the malicious insider threats in particular is the main concern in cloud environments. We will analyses the existing mitigation strategies to reduce malicious insiders threats in Cloud computing.

Social media conflict: platforms for racial vilification, or acts of provocation and citizenship?

Although racism remains an issue for social media sites such as YouTube, this focus often overshadows the site’s productive capacity to generate ‘agonistic publics’ from which expressions of cultural citizenship and solidarity might emerge. This paper examines these issues through two case studies: the recent proliferation of mobile phone video recordings of racist rants on public transport, and racist interactions surrounding the performance of a Maori ‘flash mob’ haka in New Zealand that was recorded and uploaded to YouTube. We contrast these incidents as they are played out primarily through social media, with the case of Australian Football League player Adam Goodes and the broadcast media reaction to a racial slur aimed against him by a crowd member during the AFL’s Indigenous Round. We discuss the prevalence of vitriolic exchange and racial bigotry, but also, and more importantly, the productive and equally aggressive defence of more inclusive and tolerant forms of cultural identification that play out across these different media forms. Drawing on theories of cultural citizenship along with the political theory of Chantal Mouffe, we point to the capacities of YouTube as ‘platform’, and to social media practices, in facilitating ground-up antiracism and generating dynamic, contested and confronting micropublics.