AISC '12 Proceedings of the Tenth Australasian Information Security Conference

The Australasian Information Security Conference (AISC) 2012 was held at RMIT University in Melbourne, Australia, as a part of the Australasian Computer Science Week, January 30 - February 3, 2012. AISC grew out of the Australasian Information Security Workshop and officially changed the name to Australasian Information Security Conference in 2008. The main aim of the AISC is to provide a venue for researchers to present their work on all aspects of information security and promote collaboration between academic and industrial researchers working in this area.

Information Security and Privacy : Proceedings of the 9th Australasian Conference, ACISP 2004, Sydney, Australia, July 13-15, 2004.

Preface The 9th Australasian Conference on Information Security and Privacy (ACISP 2004) was held in Sydney, 13–15 July, 2004. The conference was sponsored by the Centre for Advanced Computing – Algorithms and Cryptography (ACAC), Information and Networked Security Systems Research (INSS), Macquarie University and the Australian Computer Society. The aims of the conference are to bring together researchers and practitioners working in areas of information security and privacy from universities, industry and government sectors. The conference program covered a range of aspects including cryptography, cryptanalysis, systems and network security. The program committee accepted 41 papers from 195 submissions. The reviewing process took six weeks and each paper was carefully evaluated by at least three members of the program committee. We appreciate the hard work of the members of the program committee and external referees who gave many hours of their valuable time. Of the accepted papers, there were nine from Korea, six from Australia, five each from Japan and the USA, three each from China and Singapore, two each from Canada and Switzerland, and one each from Belgium, France, Germany, Taiwan, The Netherlands and the UK. All the authors, whether or not their papers were accepted, made valued contributions to the conference. In addition to the contributed papers, Dr Arjen Lenstra gave an invited talk, entitled Likely and Unlikely Progress in Factoring. This year the program committee introduced the Best Student Paper Award. The winner of the prize for the Best Student Paper was Yan-Cheng Chang from Harvard University for his paper Single Database Private Information Retrieval with Logarithmic Communication. We would like to thank all the people involved in organizing this conference. In particular we would like to thank members of the organizing committee for their time and efforts, Andrina Brennan, Vijayakrishnan Pasupathinathan, Hartono Kurnio, Cecily Lenton, and members from ACAC and INSS.

Understanding users’ information behaviors through information journals

Information behavior studies in the field of Library and Information Science (LIS) generally focus on one of many aspects of information behavior: information finding, information organizing, and information using. Information seeking is further specialized into information searching, information seeking, information foraging or information sense making. Spink and Cole (2006) highlighted the lack of integration across these various approaches and models of information behavior within LIS. Often, each approach provides a different language for similar processes (Spink & Cole, 2004), and it is sometimes hard for practicing information professionals to parse the various theories and models to see how they shape and affect the provision of information resources, services, and products. An integrated model of information behaviors that explains the key dimensions of how peoples’ contextual and situational dimensions affect their information needs and behavior will help information providers and LIS researchers alike with a framework that can help “depict and explain a sequence of behaviors by referring to relevant variables, rather than merely indicating a sequence of events… while indicating something about information needs and sources” (Case, 2002). This presentation presents an integrated model of peoples’ information behaviors based on research that studied participants’ information behaviors through a detailed daily information journal maintained for two weeks.

User-representative feature selection for keystroke dynamics

Continuous user authentication with keystroke dynamics uses characters sequences as features. Since users can type characters in any order, it is imperative to find character sequences (n-graphs) that are representative of user typing behavior. The contemporary feature selection approaches do not guarantee selecting frequently-typed features which may cause less accurate statistical user-representation. Furthermore, the selected features do not inherently reflect user typing behavior. We propose four statistical based feature selection techniques that mitigate limitations of existing approaches. The first technique selects the most frequently occurring features. The other three consider different user typing behaviors by selecting: n-graphs that are typed quickly; n-graphs that are typed with consistent time; and n-graphs that have large time variance among users. We use Gunetti’s keystroke dataset and k-means clustering algorithm for our experiments. The results show that among the proposed techniques, the most-frequent feature selection technique can effectively find user representative features. We further substantiate our results by comparing the most-frequent feature selection technique with three existing approaches (popular Italian words, common n-graphs, and least frequent ngraphs). We find that it performs better than the existing approaches after selecting a certain number of most-frequent n-graphs.

Improving web database search incorporating users query information

The growing importance and need of data processing for information extraction is vital for Web databases. Due to the sheer size and volume of databases, retrieval of relevant information as needed by users has become a cumbersome process. Information seekers are faced by information overloading - too many result sets are returned for their queries. Moreover, too few or no results are returned if a specific query is asked. This paper proposes a ranking algorithm that gives higher preference to a user’s current search and also utilizes profile information in order to obtain the relevant results for a user’s query.

An examination of keystroke dynamics for continuous user authentication

Most current computer systems authorise the user at the start of a session and do not detect whether the current user is still the initial authorised user, a substitute user, or an intruder pretending to be a valid user. Therefore, a system that continuously checks the identity of the user throughout the session is necessary without being intrusive to end-user and/or effectively doing this. Such a system is called a continuous authentication system (CAS). Researchers have applied several approaches for CAS and most of these techniques are based on biometrics. These continuous biometric authentication systems (CBAS) are supplied by user traits and characteristics. One of the main types of biometric is keystroke dynamics which has been widely tried and accepted for providing continuous user authentication. Keystroke dynamics is appealing for many reasons. First, it is less obtrusive, since users will be typing on the computer keyboard anyway. Second, it does not require extra hardware. Finally, keystroke dynamics will be available after the authentication step at the start of the computer session. Currently, there is insufficient research in the CBAS with keystroke dynamics field. To date, most of the existing schemes ignore the continuous authentication scenarios which might affect their practicality in different real world applications. Also, the contemporary CBAS with keystroke dynamics approaches use characters sequences as features that are representative of user typing behavior but their selected features criteria do not guarantee features with strong statistical significance which may cause less accurate statistical user-representation. Furthermore, their selected features do not inherently incorporate user typing behavior. Finally, the existing CBAS that are based on keystroke dynamics are typically dependent on pre-defined user-typing models for continuous authentication. This dependency restricts the systems to authenticate only known users whose typing samples are modelled. This research addresses the previous limitations associated with the existing CBAS schemes by developing a generic model to better identify and understand the characteristics and requirements of each type of CBAS and continuous authentication scenario. Also, the research proposes four statistical-based feature selection techniques that have highest statistical significance and encompasses different user typing behaviors which represent user typing patterns effectively. Finally, the research proposes the user-independent threshold approach that is able to authenticate a user accurately without needing any predefined user typing model a-priori. Also, we enhance the technique to detect the impostor or intruder who may take over during the entire computer session.

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.

Non-intrusive continuous user behaviour analysis using computerized systems

There are different ways to authenticate humans, which is an essential prerequisite for access control. The authentication process can be subdivided into three categories that rely on something someone i) knows (e.g. password), and/or ii) has (e.g. smart card), and/or iii) is (biometric features). Besides classical attacks on password solutions and the risk that identity-related objects can be stolen, traditional biometric solutions have their own disadvantages such as the requirement of expensive devices, risk of stolen bio-templates etc. Moreover, existing approaches provide the authentication process usually performed only once initially. Non-intrusive and continuous monitoring of user activities emerges as promising solution in hardening authentication process: iii-2) how so. behaves. In recent years various keystroke dynamic behavior-based approaches were published that are able to authenticate humans based on their typing behavior. The majority focuses on so-called static text approaches, where users are requested to type a previously defined text. Relatively few techniques are based on free text approaches that allow a transparent monitoring of user activities and provide continuous verification. Unfortunately only few solutions are deployable in application environments under realistic conditions. Unsolved problems are for instance scalability problems, high response times and error rates. The aim of this work is the development of behavioral-based verification solutions. Our main requirement is to deploy these solutions under realistic conditions within existing environments in order to enable a transparent and free text based continuous verification of active users with low error rates and response times.

Predicate encryption with various properties

Predicate encryption (PE) is a new primitive which supports exible control over access to encrypted data. In PE schemes, users' decryption keys are associated with predicates f and ciphertexts encode attributes a that are specified during the encryption procedure. A user can successfully decrypt if and only if f(a) = 1. In this thesis, we will investigate several properties that are crucial to PE. We focus on expressiveness of PE, Revocable PE and Hierarchical PE (HPE) with forward security. For all proposed systems, we provide a security model and analysis using the widely accepted computational complexity approach. Our first contribution is to explore the expressiveness of PE. Existing PE supports a wide class of predicates such as conjunctions of equality, comparison and subset queries, disjunctions of equality queries, and more generally, arbitrary combinations of conjunctive and disjunctive equality queries. We advance PE to evaluate more expressive predicates, e.g., disjunctive comparison or disjunctive subset queries. Such expressiveness is achieved at the cost of computational and space overhead. To improve the performance, we appropriately revise the PE to reduce the computational and space cost. Furthermore, we propose a heuristic method to reduce disjunctions in the predicates. Our schemes are proved in the standard model. We then introduce the concept of Revocable Predicate Encryption (RPE), which extends the previous PE setting with revocation support: private keys can be used to decrypt an RPE ciphertext only if they match the decryption policy (defined via attributes encoded into the ciphertext and predicates associated with private keys) and were not revoked by the time the ciphertext was created. We propose two RPE schemes. Our first scheme, termed Attribute- Hiding RPE (AH-RPE), offers attribute-hiding, which is the standard PE property. Our second scheme, termed Full-Hiding RPE (FH-RPE), offers even stronger privacy guarantees, i.e., apart from possessing the Attribute-Hiding property, the scheme also ensures that no information about revoked users is leaked from a given ciphertext. The proposed schemes are also proved to be secure under well established assumptions in the standard model. Secrecy of decryption keys is an important pre-requisite for security of (H)PE and compromised private keys must be immediately replaced. The notion of Forward Security (FS) reduces damage from compromised keys by guaranteeing confidentiality of messages that were encrypted prior to the compromise event. We present the first Forward-Secure Hierarchical Predicate Encryption (FS-HPE) that is proved secure in the standard model. Our FS-HPE scheme offers some desirable properties: time-independent delegation of predicates (to support dynamic behavior for delegation of decrypting rights to new users), local update for users' private keys (i.e., no master authority needs to be contacted), forward security, and the scheme's encryption process does not require knowledge of predicates at any level including when those predicates join the hierarchy.

The security and privacy of usage policies and provenance logs in an Information Accountability Framework

The potential benefits of shared eHealth records systems are promising for the future of improved healthcare. However, the uptake of such systems is hindered by concerns over the security and privacy of patient information. The use of Information Accountability and so called Accountable-eHealth (AeH) systems has been proposed to balance the privacy concerns of patients with the information needs of healthcare professionals. However, a number of challenges remain before AeH systems can become a reality. Among these is the need to protect the information stored in the usage policies and provenance logs used by AeH systems to define appropriate use of information and hold users accountable for their actions. In this paper, we discuss the privacy and security issues surrounding these accountability mechanisms, define valid access to the information they contain, discuss solutions to protect them, and verify and model an implementation of the access requirements as part of an Information Accountability Framework.

The security and privacy of usage policies and provenance logs in an Information Accountability Framework

The potential benefits of shared eHealth records systems are promising for the future of improved healthcare. However, the uptake of such systems is hindered by concerns over the security and privacy of patient information. The use of Information Accountability and so called Accountable-eHealth (AeH) systems has been proposed to balance the privacy concerns of patients with the information needs of healthcare professionals. However, a number of challenges remain before AeH systems can become a reality. Among these is the need to protect the information stored in the usage policies and provenance logs used by AeH systems to define appropriate use of information and hold users accountable for their actions. In this paper, we discuss the privacy and security issues surrounding these accountability mechanisms, define valid access to the information they contain, discuss solutions to protect them, and verify and model an implementation of the access requirements as part of an Information Accountability Framework.

Privacy invasive geo-mashups : privacy 2.0 and the limits of first generation information privacy laws

Online technological advances are pioneering the wider distribution of geospatial information for general mapping purposes. The use of popular web-based applications, such as Google Maps, is ensuring that mapping based applications are becoming commonplace amongst Internet users which has facilitated the rapid growth of geo-mashups. These user generated creations enable Internet users to aggregate and publish information over specific geographical points. This article identifies privacy invasive geo-mashups that involve the unauthorized use of personal information, the inadvertent disclosure of personal information and invasion of privacy issues. Building on Zittrain’s Privacy 2.0, the author contends that first generation information privacy laws, founded on the notions of fair information practices or information privacy principles, may have a limited impact regarding the resolution of privacy problems arising from privacy invasive geo-mashups. Principally because geo-mashups have different patterns of personal information provision, collection, storage and use that reflect fundamental changes in the Web 2.0 environment. The author concludes by recommending embedded technical and social solutions to minimize the risks arising from privacy invasive geo-mashups that could lead to the establishment of guidelines for the general protection of privacy in geo-mashups.