A Tool for Improving Privacy in Software Development

Privacy is considered a necessary requirement for software development. It is necessary to understand how certain software vulnerabilities can create problems for organizations and individuals. In this context, privacy-oriented software development plays a primary role to reduce some problems that can arise simply from individuals’ interactions software applications, even when the data being processed is not directly linked to identifiable. The loss of confidentiality, integrity, or availability at some point in the data processing, such as data theft by external attackers or the unauthorized access or use of data by employees., represent some types of cybersecurity-related privacy events. Therefore, this research work discusses the formalization of 5 key privacy elements (Privacy by Design Principles, Privacy Design Strategies, Privacy Pattern, Vulnerabilities and Context) in software development and presents a privacy tool that supports developers’ decisions to integrate privacy and security requirements in all software development phases

Intrusion detection for in-vehicle communication networks: An unsupervised kohonen SOM approach

The diffusion of embedded and portable communication devices on modern vehicles entails new security risks since in-vehicle communication protocols are still insecure and vulnerable to attacks. Increasing interest is being given to the implementation of automotive cybersecurity systems. In this work we propose an efficient and high-performing intrusion detection system based on an unsupervised Kohonen Self-Organizing Map (SOM) network, to identify attack messages sent on a Controller Area Network (CAN) bus. The SOM network found a wide range of applications in intrusion detection because of its features of high detection rate, short training time, and high versatility. We propose to extend the SOM network to intrusion detection on in-vehicle CAN buses. Many hybrid approaches were proposed to combine the SOM network with other clustering methods, such as the k-means algorithm, in order to improve the accuracy of the model. We introduced a novel distance-based procedure to integrate the SOM network with the K-means algorithm and compared it with the traditional procedure. The models were tested on a car hacking dataset concerning traffic data messages sent on a CAN bus, characterized by a large volume of traffic with a low number of features and highly imbalanced data distribution. The experimentation showed that the proposed method greatly improved detection accuracy over the traditional approach

A Kohonen SOM architecture for intrusion detection on in-vehicle communication networks

The diffusion of connected devices in modern vehicles involves a lack in security of the in-vehicle communication networks such as the controller area network (CAN) bus. The CAN bus protocol does not provide security systems to counter cyber and physical attacks. Thus, an intrusion-detection system to identify attacks and anomalies on the CAN bus is desirable. In the present work, we propose a distance-based intrusion-detection network aimed at identifying attack messages injected on a CAN bus using a Kohonen self-organizing map (SOM) network. It is a power classifier that can be trained both as supervised and unsupervised learning. SOM found broad application in security issues, but was never performed on in-vehicle communication networks. We performed two approaches, first using a supervised X-Y fused Kohonen network (XYF) and then combining the XYF network with a K-means clustering algorithm (XYF-K) in order to improve the efficiency of the network. The models were tested on an open source dataset concerning data messages sent on a CAN bus 2.0B and containing large traffic volume with a low number of features and more than 2000 different attack types, sent totally at random. Despite the complex structure of the CAN bus dataset, the proposed architectures showed a high performance in the accuracy of the detection of attack messages

SoK: Demystifying Privacy Enhancing Technologies Through the Lens of Software Developers

In the absence of data protection measures, software applications lead to privacy breaches, posing threats to end-users and software organisations. Privacy Enhancing Technologies (PETs) are technical measures that protect personal data, thus minimising such privacy breaches. However, for software applications to deliver data protection using PETs, software developers should actively and correctly incorporate PETs into the software they develop. Therefore, to uncover ways to encourage and support developers to embed PETs into software, this Systematic Literature Review (SLR) analyses 39 empirical studies on developers' privacy practices. It reports the usage of six PETs in software application scenarios. Then, it discusses challenges developers face when integrating PETs into software, ranging from intrinsic challenges, such as the unawareness of PETs, to extrinsic challenges, such as the increased development cost. Next, the SLR presents the existing solutions to address these challenges, along with the limitations of the solutions. Further, it outlines future research avenues to better understand PETs from a developer perspective and minimise the challenges developers face when incorporating PETs into software

European Privacy by Design [védés előtt]

Three competing forces are shaping the concept of European Privacy by Design (PbD): laws and regulations, business goals and architecture designs. These forces carry their own influence in terms of ethics, economics, and technology. In this research we undertook the journey to understand the concept of European PbD. We examined its nature, application, and enforcement. We concluded that the European PbD is under-researched in two aspects: at organizational level (compared to the individual level); and mainly in the way it is enforced by authorities. We had high hopes especially with regards to the latter, and eager to bring significant scientific contribution on this field. We were interested to learn if data protection authorities are having such impacts looking at European PbD, that can pioneer new approaches to privacy preservation. This is why we elaborated on possible ways to measure their activity, in a manner that both legal and non-legal experts can understand our work. We promised a response to the research question can the enforcement of European PbD be measured and if yes, what are possible ways to do so? We conducted data analytics on quantitative and qualitative data to answer this question the best way possible. Our response is a moderate yes, the enforcement of PbD can be measured. Although, at this point, we need to settle with only good-enough ways of measure and not dwell into choosing the most optimal or best ways. One reason for this is that enforcement of PbD cases are highly customized and specific to their own circumstances. We have shown this while creating models to predict the amount of administrative fines for infringement of GDPR. Clustering these cases was a daunting task. Second reason for not delivering what could be the best way of measure is lack of data availability in Europe. This problem has its roots in the philosophical stance that the European legislator is taking on the topic of data collection within the EU. Lawmakers in Europe certainly dislike programs that collect gigantic amounts of personal data from EU citizens. Third reason is a causal link between the inconsistent approach between the data protection authorities’ practices. This is due to the different levels of competencies, reporting structures, personnel numbers, and experience in the work of data protection authorities. Looking beyond the above limitations, there are certainly ways to measure the enforcement of European PbD. Our measurements helped us formulate the following statements: a. The European PbD operates in ‘data saver’ mode: we argue that analogous to the data saving mode on mobile phones, where most applications and services get background data only via Wi-Fi connection, in Europe data collection and data processing is kept to minimal. Therefore, we argue that European PbD is in essence about data minimization. Our conviction that this concept is more oriented towards data security have been partially refuted. b. The European PbD is platform independent: we elaborated in the thesis on various infrastructures and convergent technologies that found compatibility with the PbD principles. We consider that the indeed the concept is evolutionary and technology –neutral. c. The European PbD is a tool obligation: we argue that the authorities are looking at PbD as a tool utilization obligation. In a simple language, companies should first perform a privacy impact assessment in order to find out which tools are supporting their data processing activities and then implement these, as mandated PbD. d. The European PbD is highly territorial: we reached the conclusion that enforcement of PbD is highly dependent on geographical indicators (i.e. countries and counties). The different level of privacy protection cultures are still present in Europe. On a particular level, what is commonly true across all countries is that European PbD mandates strong EU data sovereignty

Privacy Oriented Software Development

Threats to applications security are continuously evolving thanks to factors such as progress made by the attackers, release of new technologies, use of increasingly complex systems. In this scenario, it is necessary to implement both design and programming practices that guarantee the security of the code on one hand, and the privacy of the data, on the other. This paper proposes a software development approach, Privacy Oriented Software Development (POSD), that complements traditional development processes by integrating the activities needed for addressing security and privacy management in software systems. The approach is based on 5 key elements (Privacy by Design, Privacy Design Strategies, Privacy Pattern, Vulnerabilities, Context). It can be applied forward for developing new systems and backward for re-engineering an existing one. This paper presents the POSD approach in the backward mode together with an experimentation in the context of an industrial project. Results show that POSD is able to discover software vulnerabilities, identify the remediation patterns needed for addressing them in the source code and design the target architecture to be used for guiding privacy-oriented system reengineering

Integrating security and privacy in HCD-scrum

Nowadays, software development must face the challenge of integrating security and privacy elements from the earliest stages of any software development process. A correct and complete implementation starting from the requirements definition allows to significantly increase the security level of each single phase/iteration and consequently of the final system. Therefore, it is necessary to support the team throughout the software lifecycle trying to provide operational guidelines of security by design and privacy by design. Taking these aspects into account, the paper presents a Human Centered Design (HCD) approach of security and privacy-oriented software development, integrated within the Scrum agile methodology, defined as HCD-Security Scrum. The goal is to support developer decisions at all stages of software development in integrating security and privacy requirements through the formalization of key elements defined in a knowledge base, i.e., the Privacy Knowledge Base

Privacy Knowledge Base for Supporting Decision-Making in Software Development

Integrating security and privacy requirements at every stage of the software development cycle is critical to guarantee the confidentiality, integrity and availability of the system and consequently of the data. Developers need to be supported in this challenge, as many different skills are required to respond effectively to the growing number of cyber-attacks. In such a context, this research study endeavors to define the key elements that support decision-making in privacy oriented software development. A Privacy Knowledge Base (PKB) is defined to support developers’ decisions in all software development phases, and a prototype (PKB-Tool) is developed to operationally integrate privacy and security requirements into the development of new systems and the re-engineering of legacy systems. An ongoing experimentation in the context of an industrial project is presented to validate the efficacy of the 5 key elements in supporting developers in integrating privacy and security requirements in the software life cycle