Political Islam and human security

In the wake of the September 11 and subsequent terrorist attacks, the academic and media commentaries on Islam the religion and Islam the basis for political ideology haves received an unprecedented high level of exposure and attention. The acts of political violence by extremist groups and the omnipresent war on terror have added fresh uncertainties to an already complex global order. Just as terrorism and counter-terrorism are locked in a mutually re-enforcing symbiosis, the sense of insecurity felt by Muslims and non-Muslims alike is mutually dependent and has the potential to escalate. This general assessment holds true for Muslims living in the Muslim world and beyond. The pervasive sense of being under attack physically and culturally by the United States and its allies has contributed to a growing unease among Muslims and re-enforced deep-seated mistrust of the ‘West’. Public articulation of such misgivings has in turn, lent credence to Western observers who posit an inherent antipathy between the West and the Muslim world. The subsequent policies that have emerged in this context of fear and mutual distrust have contributed to the vicious cycle of insecurity.

"It's about freedom": contesting dominant representations of devout Muslim women in the space of the nation

Since September 11 there has been a rise of Islamophobia in Australian public discourse, matched by a growth of racialised attacks on visibly identifiable Muslims in public space. These cultural racisms have arisen in a context where Islamic religious signifiers and practices have come to be read as signs of fundamentalism, terrorism and threat to national political traditions and cultural values. In particular, the hijab has become a symbol of these tensions, with the veiled woman being read as the embodiment of a ‘repressive and fundamentalist religion’. However, as some Muslim and feminist scholars have proposed, these readings rob Muslim women of their ability to articulate the reasons why wear the veil or engage in gendered religious practices. This paper argues that this enacts a form of disembodiment, whereby Muslim womens’ ability to comfortably inhabit their bodies and assert themselves in the public sphere is limited. In particular the paper draws upon two case studies which express this disembodiment, whilst highlighting the counter-strategies that devout Muslim women are adopting to reinsert their bodies and narratives in the national frame. The first refers to the recent media backlash which followed a public lecture held at Melbourne University by Islamic organization Hikmah Way, where the audience was segregated along gender lines. The second draws upon interviews conducted with veiled Muslim women in Sydney, following the Cronulla riot. These interviews show how Muslim women are contesting dominant representations of the hijab in western popular discourse by recoding it as a signifier of religious and national identity, and as an expression of democratic freedom.

Wave of bombings across Iraq ahead of elections

The people of Iraq have also endured bombings but on a larger scale. There are media reports saying up to thirty-one people were killed in dozens of separate explosions across different Iraqi provinces including two blasts at a checkpoint at Baghdad international airport.

This comes just days before provincial elections across Iraq, the first ballot since the withdrawal of US troops at the end of 2011. Although it is unclear who carried out the attacks different factions are increasingly stoking the fire as they vie for political power in the upcoming elections. Tawar Razaghi spoke to Senior Research Fellow, Dr Benjamin Isakhan, at the Centre for Citizenship and Globalisation at Deakin University.

The new anti-semitism

The new Anti-Semitism is a term that came into use to describe attacks on Jews across the world that erupted in the aftermath of the outbreak of Israeli-Palestinian fighting in September 2000 after the collapse of the Camp David peace talks. The conflict unleashed a wave of suicide bombings in Israel and led to Israel reoccupying Palestinian areas. This fighting triggered an outburst of antiSemitism not seen since the end of the World War II. Nearly 100 synagogues were attacked across the world in the four weeks from the end of September to October 2000; more were burnt down at any time since Kristallnacht, when Nazis attacked Jewish institutions in Germany in 1938.

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.

Towards designing privacy-preserving signature-based IDS as a service : a study and practice

With the advent of Cloud Computing, IDS as a service (IDSaaS) has been proposed as an alternative to protect a network (e.g., financial organization) from a wide range of network attacks by offloading the expensive operations such as the process of signature matching to the cloud. The IDSaaS can be roughly classified into two types: signature-based detection and anomaly-based detection. During the packet inspection, no party wants to disclose their own data especially sensitive information to others, even to the cloud provider, for privacy concerns. However, current solutions of IDSaaS have not much discussed this issue. In this work, focus on the signature-based IDSaaS, we begin by designing a promising privacy-preserving intrusion detection mechanism, the main feature of which is that the process of signature matching does not reveal any specific content of network packets by means of a fingerprint-based comparison. We further conduct a study to evaluate this mechanism under a cloud scenario and identify several open problems and issues for designing such a privacy-preserving mechanism for IDSaaS in a practical environment.

A hierarchical PCA-based anomaly detection model

A hierarchical intrusion detection model is proposed to detect both anomaly and misuse attacks. In order to further speed up the training and testing, PCA-based feature extraction algorithm is used to reduce the dimensionality of the data. A PCA-based algorithm is used to filter normal data out in the upper level. The experiment results show that PCA can reduce noise in the original data set and the PCA-based algorithm can reach the desirable performance.

A general cloud firewall framework with dynamic resource allocation

Cloud is becoming a dominant computing platform. However, we see few work on how to protect cloud data centers. As a cloud usually hosts many different type of applications, the traditional packet level firewall mechanism is not suitable for cloud platforms in case of complex attacks. It is necessary to perform anomaly detection at the event level. Moreover, protecting objects are more diverse than the traditional firewall. Motivated by this, we propose a general framework of cloud firewall, which features event level detection chain with dynamic resource allocation. We establish a mathematical model for the proposed framework. Moreover, a linear resource investment function is proposed for economical dynamical resource allocation for cloud firewalls. A few conclusions have been extracted for the reference of cloud service providers and designers.

Robust patchwork-based watermarking method for stereo audio signals

This paper presents a patchwork-based watermarking method for stereo audio signals, which exploits the similarity of the two sound channels of stereo signals. Given a segment of stereo signal, we first compute the discrete Fourier transforms (DFTs) of the two sound channels, which yields two sets of DFT coefficients. The DFT coefficients corresponding to certain frequency range are divided into multiple subsegment pairs and a criterion is proposed to select those suitable for watermark embedding. Then a watermark is embedded into the selected subsegment pairs by modifying their DFT coefficients. The exact way of modification is determined by a secret key, the watermark to be embedded, and the DFT coefficients themselves. In the decoding process, the subsegment pairs containing watermarks are identified by another criterion. Then the secret key is used to extract the watermark from the watermarked subsegments. Compared to the existing patchwork methods for audio watermarking, the proposed method does not require knowledge of which segments of the watermarked audio signal contain watermarks and is more robust to conventional attacks.

Time correlated anomaly detection based on inferences

Anomaly detection techniques are used to find the presence of anomalous activities in a network by comparing traffic data activities against a "normal" baseline. Although it has several advantages which include detection of "zero-day" attacks, the question surrounding absolute definition of systems deviations from its "normal" behaviour is important to reduce the number of false positives in the system. This study proposes a novel multi-agent network-based framework known as Statistical model for Correlation and Detection (SCoDe), an anomaly detection framework that looks for timecorrelated anomalies by leveraging statistical properties of a large network, monitoring the rate of events occurrence based on their intensity. SCoDe is an instantaneous learning-based anomaly detector, practically shifting away from the conventional technique of having a training phase prior to detection. It does acquire its training using the improved extension of Exponential Weighted Moving Average (EWMA) which is proposed in this study. SCoDe does not require any previous knowledge of the network traffic, or network administrators chosen reference window as normal but effectively builds upon the statistical properties from different attributes of the network traffic, to correlate undesirable deviations in order to identify abnormal patterns. The approach is generic as it can be easily modified to fit particular types of problems, with a predefined attribute, and it is highly robust because of the proposed statistical approach. The proposed framework was targeted to detect attacks that increase the number of activities on the network server, examples which include Distributed Denial of Service (DDoS) and, flood and flash-crowd events. This paper provides a mathematical foundation for SCoDe, describing the specific implementation and testing of the approach based on a network log file generated from the cyber range simulation experiment of the industrial partner of this project.

DDoS attack detection at local area networks using information theoretical metrics

DDoS attacks are one of the major threats to Internet services. Sophisticated hackers are mimicking the features of legitimate network events, such as flash crowds, to fly under the radar. This poses great challenges to detect DDoS attacks. In this paper, we propose an attack feature independent DDoS flooding attack detection method at local area networks. We employ flow entropy on local area network routers to supervise the network traffic and raise potential DDoS flooding attack alarms when the flow entropy drops significantly in a short period of time. Furthermore, information distance is employed to differentiate DDoS attacks from flash crowds. In general, the attack traffic of one DDoS flooding attack session is generated by many bots from one botnet, and all of these bots are executing the same attack program. As a result, the similarity among attack traffic should higher than that among flash crowds, which are generated by many random users. Mathematical models have been established for the proposed detection strategies. Analysis based on the models indicates that the proposed methods can raise the alarm for potential DDoS flooding attacks and can differentiate DDoS flooding attacks from flash crowds with conditions. The extensive experiments and simulations confirmed the effectiveness of our proposed detection strategies.

Offline grouping proof protocol for RFID systems

Several grouping proof protocols have been proposed over the years but they are either found to be vulnerable to certain attacks or do not comply with EPC Class-1 Gen-2 (C1G2) standard because they use hash functions or other complex encryption schemes. Also, synchronization of keys, forward security, proving simultaneity, creating dependence, detecting illegitimate tags, eliminating unwanted tag processing and denial-of-proof (DoP) attacks have not been fully addressed by many. Our protocol addresses these important gaps and is based on Quadratic Residues property where the tags are only required to use XOR, 128-bit Pseudo Random Number Generators (PRNG) and Modulo (MOD) operations which can be easily implemented on low-cost passive tags and hence achieves EPC C1G2 compliance.

Privacy preserving for tagging recommender systems

Tagging recommender systems allow Internet users to annotate resources with personalized tags. The connection among users, resources and these annotations, often called afolksonomy, permits users the freedom to explore tags, and to obtain recommendations. Releasing these tagging datasets accelerates both commercial and research work on recommender systems. However, adversaries may re-identify a user and her/his sensitivity information from the tagging dataset using a little background information. Recently, several private techniques have been proposed to address the problem, but most of them lack a strict privacy notion, and can hardly resist the number of possible attacks. This paper proposes an private releasing algorithm to perturb users' profile in a strict privacy notion, differential privacy, with the goal of preserving a user's identity in a tagging dataset. The algorithm includes three privacy preserving operations: Private Tag Clustering is used to shrink the randomized domain and Private Tag Selection is then applied to find the most suitable replacement tags for the original tags. To hide the numbers of tags, the third operation, Weight Perturbation, finally adds Lap lace noise to the weight of tags We present extensive experimental results on two real world datasets, Delicious and Bibsonomy. While the personalization algorithmis successful in both cases.

RFID tags : grouping proof with forward security

Several grouping proof protocols have been proposed over the years but they are either found to be vulnerable to certain attacks or do not comply with EPC Class-1 Gen-2 (C1G2) standard because they use hash functions or other complex encryption schemes. Among other requirements, synchronization of keys, forward security, dependence, detecting illegitimate tags, eliminating unwanted tag processing and denial-of-proof (DoP) attacks have not been fully addressed by many. Our protocol addresses these important gaps and is based on simple XOR encryption and 128-bit Pseudo Random Number Generators (PRNG), operations that are easily implemented on low-cost passive tags and hence achieves EPC C1G2 compliance.

Secure ownership transfer in multi-tag/multi-owner passive RFID systems

In this paper we propose a secure ownership transfer protocol for a multi-tag and multi-owner RFID environment. Most of the existing work in this area do not comply with the EPC Global Class-1 Gen-2 (C1G2) standard since they use expensive hash operations or sophisticated encryption schemes that cannot be implemented on low-cost passive tags that are highly resource constrained. Our work aims to fill this gap by proposing a protocol based on simple XOR and 128-bit Pseudo Random Number Generators (PRNG), operations that can be easily implemented on low-cost passive RFID tags. The protocol thus achieves EPC C1G2 compliance while meeting the security requirements. Also, our protocol provides additional protection using a blind-factor to prevent tracking attacks.