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Über dieses Buch

This book constitutes the revised selected papers of the Third International Conference on Information Systems Security and Privacy, ICISSP 2018, held in Funchal - Madeira, Portugal, in January 2018.
The 15 full papers presented were carefully reviewed and selected from a total of 71 submissions. They are dealing with topics such as data and software security; privacy and confidentiality; mobile systems security; biometric authentication; information systems security and privacy; authentication, privacy and security models; data mining and knowledge discovery; phishing; security architecture and design analysis; security testing; vulnerability analysis and countermeasures; web applications and services.

Inhaltsverzeichnis

Frontmatter

Fine-Grained Privacy Control for Fitness and Health Applications Using the Privacy Management Platform

Abstract
Due to the Internet of Things, novel types of sensors are integrated into everyday objects. A domain that benefits most is the fitness and health domain. With the advent of the so-called Smartbands—i. e., bracelets or watches with built-in sensors such as heart rate sensors, location sensors, or even glucose meters—novel fitness and health application are made possible. That way a quantified self can be created. Despite all the advantages that such applications entail, new privacy concerns arise.
These applications collect and process sensitive health data. Users are concerned by reports about privacy violations. These violations are enabled by inherent security vulnerabilities and deficiencies in the privacy systems of mobile platforms. As none of the existing privacy approaches is designed for the novel challenges arising from Smartband applications, we discuss, how the Privacy Policy Model (PPM), a fine-grained and modular expandable permission model, can be applied to this application area. This model is implemented in the Privacy Management Platform (PMP). Thus the outcomes of this work can be leveraged directly. Evaluation results underline the benefits of our work for Smartband applications.
Christoph Stach

Touch and Move: Incoming Call User Authentication

Abstract
This paper presents two methods of implicit authentication during answering an incoming call based on user behavior biometrics. Such methods allow to increase usability of authentication against common PIN or graphical password. Also, a concept of authentication system based on presented methods is proposed. The paper shows that user’s touch dynamics and movement of the hand towards the ear when accepting the call provide all necessary information for authentication and there is no need for user to enter a PIN or graphical password.
Aleksandr Eremin, Konstantin Kogos, Yana Valatskayte

Elicitation of Privacy Requirements for the Internet of Things Using ACCESSORS

Abstract
Novel smart devices are equipped with various sensors to capture context data. The Internet of Things (IoT) connects these devices with each other in order to bring together data from various domains. Due to the IoT, new application areas come up continuously. For instance, the quality of life and living can be significantly improved by installing connected and remote-controlled devices in Smart Homes. Or the treatment of chronic diseases can be made more convenient for both, patients and physicians, by using Smart Health technologies.
For this, however, a large amount of data has to be collected, shared, and combined. This gathered data provides detailed insights into the user of the devices. Therefore, privacy is a key issue for such IoT applications. As current privacy systems for mobile devices focus on a single device only, they cannot be applied to a distributed and highly interconnected environment as the IoT. Therefore, we determine the special requirements towards a permission models for the IoT. Based on this requirements specification, we introduce ACCESSORS, a data-centric permission model for the IoT and describe how to apply such a model to two promising privacy systems for the IoT, namely the Privacy Management Platform (PMP) and PATRON.
Christoph Stach, Bernhard Mitschang

A Simple Attack on CaptchaStar

Abstract
CaptchaStar is a new type of Captcha, proposed in 2016, based on shape recovery. This paper shows that the security of this Captcha is not as good as intended. More precisely, we present and implement an efficient attack on CaptchaStar with a success rate of 96%. The impact of this attack is also investigated in other scenarios as noise addition, and it continues to be very efficient. This paper is a revised version of the paper entitled How to break CaptchaStar, presented at the conference ICISSP 2018 [29].
Thomas Gougeon, Patrick Lacharme

Notify This: Exploiting Android Notifications for Fun and Profit

Abstract
In the era of telecommunications, where mobile phones are becoming continuously smarter, how users interact with smartphones plays a very essential role, magnified by statistics that reveal great increase in human time spent in human-smartphone interaction. Some of the basic reasons for users to use their smartphones include notifications, whose functionality has been investigated and improved over the last decade. As a result, this mechanism, namely smartphone notifications, is not only well-rounded by both OS vendors and app developers, but is also inextricably accompanying vital parts of the majority of modern mobile applications. This paper analyzes flaws in this fundamental mechanism, as found in the most widespread mobile OS to date, namely Android. After presenting forging smartphone application notifications and Denial of Service attacks to the users’ device, accomplished both locally and remotely, we conclude by proposing generic countermeasures for the security threats in question.
Efthimios Alepis

The Current State of the Holistic Privacy and Security Modelling Approach in Business Process and Software Architecture Modelling

Abstract
Modelling is central for business process and software architecture documentation and analysis. However, business processes and software architectures are specified with their own highly developed languages, methods and tools. There are approaches in the literature for modelling privacy and security issues using existing business process or architecture modelling languages to express different requirements by enriching these languages with annotations. Nevertheless, there is a lack of formalization and therefore the potential use for tool-based analyses are limited. In addition, the continuity between business and software models is not granted, but when modelling compliance requirements like privacy, traceability is very important, e.g. for compliance checks. In this contribution, approaches for modelling security and privacy in business and software models are examined. One key finding is that there is currently no comprehensive modelling approach which covers the necessary aspects and perspectives. This could include processes as well as, for example, organizational and data structure questions. In conclusion, we suggest developing a new holistic modelling approach which includes the needed aspects and with a concept for the traceability of the requirements from business models to software architecture models.
Sascha Alpers, Roman Pilipchuk, Andreas Oberweis, Ralf Reussner

A Critical Security Analysis of the Password-Based Authentication Honeywords System Under Code-Corruption Attack

Abstract
Password-based authentication is a widespread method to access into systems, thus password files are a valuable resource often target of attacks. To detect when a password file has been stolen, Juels and Rivest introduced the Honeywords System in 2013. The core idea is to store the password with a list of decoy words that are “indistinguishable” from the password, called honeywords. An adversary that obtains the password file and, by dictionary attack, retrieves the honeywords can only guess the password when attempting to log in: but any incorrect guess will set off an alarm, warning that file has been compromised. In a recent conference paper, we studied the security of the Honeywords System in a scenario where the intruder also manages to corrupt the server’s code (with certain limiting assumptions); we proposed an authentication protocol and proved it secure despite the corruption. In this extended journal version, we detail the analysis and we extend it, under the same attacker model, to the other two protocols of the original Honeywords System, the setup and change of password. We formally verify the security of both of them; further, we discuss that our design suggests a completely new approach that diverges from the original idea of the Honeywords System but indicates an alternative way to authenticate users which is robust to server’s code-corruption.
Ziya Alper Genç, Gabriele Lenzini, Peter Y. A. Ryan, Itzel Vazquez Sandoval

GenVote: Blockchain-Based Customizable and Secure Voting Platform

Abstract
Electronic voting has been popularized in recent years as an alternative to traditional voting. Even though electronic voting addresses the problems that traditional voting brings, it is not a perfect solution. Electronic voting brings its own set of concerns which include: election fraud, voter privacy, data integrity, and confidentiality. To ensure fairness in electronic voting, a centralized system is required and the complete process has to be overseen by an authority. Due to these requirements it can be very expensive to roll-out on a large scale during every voting period. Blockchain, the distributed data structure popularized by Bitcoin, can be integrated into electronic voting systems to alleviate some the problems involved with them while being cost-effective. With the use of blockchain, we propose a voting system that is easily accessible, customizable, transparent, and in-expensive. GenVote is a distributed electronic voting system that utilizes Ethereum Blockchain, smart contracts, and homomorphic encryption to achieve a transparent voting process with non-authority based tallying and voter privacy. GenVote also allows the ballot creation and voting process to be customizable with different types of ballots and logic based voting. GenVote is currently a viable solution for university-scaled elections and has been deployed on Ethereum Ropsten testing network to evaluate its viability and scalability as an electronic voting system.
Praneeth Babu Marella, Matea Milojkovic, Jordan Mohler, Gaby G. Dagher

A Detailed Analysis of the CICIDS2017 Data Set

Abstract
The likelihood of suffering damage from an attack is obvious with the exponential growth in the size of computer networks and the internet. Meanwhile, intrusion detection systems (IDSs) and intrusion prevention systems (IPSs) are one of the most important defensive tools against the ever more sophisticated and ever-growing frequency of network attacks. Anomaly-based research in intrusion detection systems suffers from inaccurate deployment, analysis and evaluation due to the lack of an adequate dataset. A number of datasets such as DARPA98, KDD99, ISC2012, and ADFA13 have been used by the researchers to evaluate the performance of their proposed intrusion detection and intrusion prevention approaches. Based on our study of 16 datasets since 1998, many are out of date and unreliable. There are various shortcomings: lack of traffic diversity and volume, incomplete attack coverage, anonymized packet information and payload which does not reflect the current reality, or they lack some feature set and metadata. This paper focused on CICIDS2017 as the last updated IDS dataset that contains benign and seven common attack network flows, which meets real world criteria and is publicly available. It also evaluates the effectiveness of a set of network traffic features and machine learning algorithms to indicate the best set of features for detecting an attack category. Furthermore, we define the concept of superfeatures which are high quality derived features using a dimension reduction algorithm. We show that the random forest algorithm as one of our best performing algorithm can achieve better results with superfeatures versus top selected features.
Iman Sharafaldin, Arash Habibi Lashkari, Ali A. Ghorbani

Personalising Security Education: Factors Influencing Individual Awareness and Compliance

Abstract
Security education and awareness are frequently overlooked for users in both workplace and personal contexts, and even where some level of provision is offered it is rarely done in a manner that is matched specifically to the needs of the audience. However, by personalising the provision, and making the presentation and messaging more appropriate to the individuals receiving it, there is a greater chance of achieving understanding, engagement, and resultant compliance. This paper examines the gap that exists between the typical and desirable provision of security education. It highlights baseline areas of security literacy that ought to be applicable to all users, but then illustrates how variations in individuals’ understanding of threshold concepts could complicate the task of delivering the related education. It is proposed that security education should be more tailored, recognising factors such as the user’s role, prior knowledge, learning style, and current perception of security, in order to deliver a more personalised security education plan that is framed towards individual circumstances and can be delivered in a manner that suits their needs.
Ismini Vasileiou, Steven Furnell

Managing Cybersecurity Break-ins Using Bluetooth Low Energy Devices to Verify Attackers: A Practical Study

Abstract
We present a novel solution in tracking the behaviour of an attacker and limiting their ability to compromise a cybersecurity system. The solution is based on combining a decoy with a real system, in which a BLE controller will be embedded in the middle of the system, thereby acting like a fob that opens and closes the access of the server’s BLE. If the first server wants to communicate with the second server, the BLE must be activated by the BLE controller in order for both servers to communicate with one another. This is a relatively low-cost solution and our aim is to lower the interruption to the live system, capture the attacker’s position, and limit the damages the attacker can do to a live system. A second related goal is to lower the attacker’s opportunity to detect that they are being monitored. A third goal is to gather evidence of the attacker’s actions that can be used for further investigation. This work is significant in that it is implemented within a real physical system for testing and evaluation using Raspberry PI and Arduino boards to replicate servers that communicate wirelessly. Adding a specifically-designed Encryption Block Cycle Cipher can protect legitimate users and redirect attackers to a honeypot system. Several custom programs were written from scratch to monitor the attacker’s behaviour and Bluetooth Low Energy is enlisted to verify users. When the device was disassembled, all of the Raspberry PI, which run the Linux servers, were discontinued and unable to communicate with other devices.
Kenneth C. K. Wong, Aaron Hunter

On Building a Visualisation Tool for Access Control Policies

Abstract
An access control policy usually consists of a structured set of rules describing when an access to a resource should be permitted or denied, based on the attributes of the different entities involved in the access request. A policy containing a large number of rules and attributes can be hard to navigate, making policy editing and fixing a complex task. In some contexts, visualisation techniques are known to be helpful when dealing with similar amounts of complexity; however, finding a useful visual representation is a long process that requires observation, supposition, testing and refinement. In this paper, we report on the design process for a visualisation tool for access control policies, which led to the tool VisABAC. We first present a comprehensive survey of the existing literature, followed by the description of the participatory design for VisABAC. We then describe VisABAC itself, a tool that implements Logic Circle Packing to pursue the reduction of cognitive load on Access Control Policies. VisABAC is a web-page component, developed in Javascript using the D3.js library, and easily usable without any particular setup. Finally, we present a testing methodology that we developed to prove usability by conducting a controlled experiment with 32 volunteers; we asked them to change some attribute values in order to obtain a given decision for a policy and measured the time taken by participant to conduct these tasks (the faster, the better). We obtained a small to medium effect size (\(d=0.44\)) that indicates that VisABAC is a promising tool for authoring and editing access control policies.
Charles Morisset, David Sanchez

Survey and Guidelines for the Design and Deployment of a Cyber Security Label for SMEs

Abstract
Cyber Security risks and attacks are on the rise, especially at the light of the recent events in the geopolitical landscape. Cyber attacks are not longer targeting big organisations such as governments, institutions or global companies. Smaller businesses and even citizens are now also being hit by cyber attacks, either directly or as a result of side effects. At the same time, the regulation and legislative pressure to prevent cyber attacks is increasing, especially in Europe. In order to protect Small and Medium Enterprises (SMEs), different labels, specific standards or practical guidelines are being developed. This papers makes a comparative survey of such initiatives with the aim to initiate such an approach in Belgium in a consistent way with other existing approaches and also to enable longer term convergence with a possible European scheme. Our goal is to reach enough SMEs with a basic level of cyber security and engage them in continuous improvement to keep a sustainable but efficient level of security. At a more practical level, we report about how to set up the overall organisational structures, basic management processes and some supporting tools.
Christophe Ponsard, Jeremy Grandclaudon

Privacy Preserving Collaborative Agglomerative Hierarchical Clustering Construction

Abstract
Sharing information brought by governments, companies, and individuals, has created fabulous opportunities for knowledge-based decision making. However, the main challenge in collaborative data analysis returns back to the privacy of sensitive data. In current study, we propose a general framework which can be exploited as a secure tool for constructing any agglomerative hierarchical clustering algorithm over partitioned data. We assume that data is distributed between two (or more) parties either horizontally or vertically, such that for mutual benefits the participated parties are interested in obtaining the clusters’ structure on whole data, but for privacy concerns, they are not willing to share the original datasets. To this end, in this study, we propose general algorithms based on secure scalar product and secure hamming distance to securely compute the desired criteria for shaping the clusters’ scheme. Our proposed approach covers the private construction of all possible agglomerative hierarchical clustering algorithms on distributed datasets, including both numerical and categorical data.
Mina Sheikhalishahi, Mona Hamidi, Fabio Martinelli

Insights into Unsupervised Holiday Detection from Low-Resolution Smart Metering Data

Abstract
Recently, first methods for holiday detection from unsupervised low-resolution smart metering data have been presented. However, due to the unsupervised nature of the problem, previous work only applied the algorithms on a few typical cases and lacks a systematic validation. This paper systematically validates the existing algorithm by visual inspection and shows that numerous cases exist, where implicit assumptions are not met and the methods fail. Moreover, it proposes a new, very simple rule-based method which is in principle able to overcome these problems. This method should be seen as a first step towards improvement, since it is not automated and needs a moderate amount of human intervention for each household.
Günther Eibl, Sebastian Burkhart, Dominik Engel

Backmatter

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