Biblio

Benchmark datasets are heavily depended upon by the research community to validate theoretical findings and track progression in the state-of-the-art. NIDS dataset creation presents numerous challenges on account of the volume, heterogeneity, and complexity of network traffic, making the process labor intensive, and thus, prone to error. This paper provides a critical review of CIC-IDS-2017 and CIC-CSE-IDS-2018, datasets which have seen extensive usage in the NIDS literature, and are currently considered primary benchmarking datasets for NIDS. We report a large number of previously undocumented errors throughout the dataset creation lifecycle, including in attack orchestration, feature generation, documentation, and labeling. The errors destabilize the results and challenge the findings of numerous publications that have relied on it as a benchmark. We demonstrate the implications of these errors through several experiments. We provide comprehensive documentation to summarize the discovery of these issues, as well as a fully-recreated dataset, with labeling logic that has been reverse-engineered, corrected, and made publicly available for the first time. We demonstrate the implications of dataset errors through a series of experiments. The findings serve to remind the research community of common pitfalls with dataset creation processes, and of the need to be vigilant when adopting new datasets. Lastly, we strongly recommend the release of labeling logic for any dataset released, to ensure full transparency.

The widespread adoption of eCommerce, iBanking, and eGovernment institutions has resulted in an exponential rise in the use of web applications. Due to a large number of users, web applications have become a prime target of cybercriminals who want to steal Personally Identifiable Information (PII) and disrupt business activities. Hence, there is a dire need to audit the websites and ensure information security. In this regard, several web vulnerability scanners are employed for vulnerability assessment of web applications but attacks are still increasing day by day. Therefore, a considerable amount of research has been carried out to measure the effectiveness and limitations of the publicly available web scanners. It is identified that most of the publicly available scanners possess weaknesses and do not generate desired results. In this paper, the evaluation of publicly available web vulnerability scanners is performed against the top ten OWASP11OWASP® The Open Web Application Security Project (OWASP) is an online community that produces comprehensive articles, documentation, methodologies, and tools in the arena of web and mobile security. vulnerabilities and their performance is measured on the precision of their results. Based on these results, we proposed an Integrated Multi-Agent Blackbox Security Assessment Tool (SAT) for the security assessment of web applications. Research has proved that the vulnerabilities assessment results of the SAT are more extensive and accurate.

The increase of autonomy in autonomous surface vehicles development brings along modified and new risks and potential hazards, this in turn, introduces the need for processes and methods for ensuring that systems are acceptable for their intended use with respect to dependability and safety concerns. One approach for evaluating software requirements for claims of safety is to employ an assurance case. Much like a legal case, the assurance case lays out an argument and supporting evidence to provide assurance on the software requirements. This paper analyses safety and security requirements relating to autonomous vessels, and regulations in the automotive industry and the marine industry before proposing a generic cybersecurity and safety assurance case that takes a general graphical approach of Goal Structuring Notation (GSN).

Blockchain technology is the need of an hour for ensuring security and data privacy. However, very limited tools and documentation are available, therefore, the traditional code-centric implementation of Blockchain is challenging for programmers and developers due to inherent complexities. To overcome these challenges, in this article, a novel and efficient framework is proposed that is based on the Model-Driven Architecture. Particularly, a Meta-model (M2 level Ecore Model) is defined that contains the concepts of Blockchain technology. As a part of tool support, a tree editor (developed using Eclipse Modeling Framework) and a Sirius based graphical modeling tool with a drag-drop palette have been provided to allow modeling and visualization of simple and complex Blockchain-based scenarios for security labs in a very user-friendly manner. A Model to Text (M2T) transformation code has also been written using Acceleo language that transforms the modeled scenarios into java code for Blockchain application in the security lab. The validity of the proposed framework has been demonstrated via a case study. The results prove that our framework can be reliably used and further extended for automation and development of Blockchain-based application for security labs with simplicity.

The advancement of technology in the creation of new tools to solve problems such as information storage generates proportionally developing methods that search for security flaws or breaches that compromise said information. The need to periodically generate security reports on database managers is given by the complexity and number of attacks that can be carried out today. This project seeks to carry out an evaluation of the security of NoSQL database managers. The work methodology is developed according to the order of the objectives, it begins by synthesizing the types of vulnerabilities, attacks and protection schemes limited to MongoDB, Redis and Apache Cassandra. Once established, a prototype of a web system that stores information with a non-relational database will be designed on which a series of attacks defined by a test plan will be applied seeking to add, consult, modify or eliminate information. Finally, a report will be presented that sets out the attacks carried out, the way in which they were applied, the results, possible countermeasures, security advantages and disadvantages for each manager and the conclusions obtained. Thus, it is possible to select which tool is more convenient to use for a person or organization in a particular case. The results showed that MongoDB is more vulnerable to NoSQL injection attacks, Redis is more vulnerable to attacks registered in the CVE and that Cassandra is more complex to use but is less vulnerable.

Digital forensics is concerned with identifying, reporting and responding to security breaches. It is about how to acquire, analyze and report digital evidence and using the technical skills, discovering the traces of Cyber Crime. The field of digital forensics is in high demand due to the constant threats of data breaches and information hacks. Digital Forensics is utilized in the identification and elimination of crimes in any controversy where evidence is preserved in online space. This is the use of specialized techniques for retrieval, authentication and electronic data analysis. Computer forensics deals with the identification, preservation, analysis, documentation and presentation of digital evidence. The paper has analyzed the present-day trends that includes IoT forensics, cloud forensics, network forensics and social media forensics. Recent researches have shown a wide range of threats and cyber-attacks, which requires forensic investigators and forensics scientists to simplify the digital world. Hence, all our research gives a clear view of digital forensics which could be of a great help in forensic investigation. In this research paper we have discussed about the need and way to preserve the digital evidence, so that it is not compromised at any point in time and an unalter evidence can be presented before the court of law.

In this fast-running world, machine communication plays a vital role. To compete with this world, human-machine interaction is a necessary thing. To enhance this, Natural Language Processing technique is used widely. Using this technique, we can reduce the interaction gap between the machine and human. Till now, many such applications are developed which are using this technique.This tool deals with the various methods which are used for development of grammar error correction. These methods include rule-based method, classifier-based method and machine translation-based method. Also, models regarding the Natural Language Processing (NLP) pipeline are trained and implemented in this project accordingly. Additionally, the tool can also perform speech to text operation.

Python libraries are widely used for machine learning and scientific computing tasks today. APIs in Python libraries are deprecated due to feature enhancements and bug fixes in the same way as in other languages. These deprecated APIs are discouraged from being used in further software development. Manually detecting and replacing deprecated APIs is a tedious and time-consuming task due to the large number of API calls used in the projects. Moreover, the lack of proper documentation for these deprecated APIs makes the task challenging. To address this challenge, we propose an algorithm and a tool APIScanner that automatically detects deprecated APIs in Python libraries. This algorithm parses the source code of the libraries using abstract syntax tree (ASTs) and identifies the deprecated APIs via decorator, hard-coded warning or comments. APIScanner is a Visual Studio Code Extension that highlights and warns the developer on the use of deprecated API elements while writing the source code. The tool can help developers to avoid using deprecated API elements without the execution of code. We tested our algorithm and tool on six popular Python libraries, which detected 838 of 871 deprecated API elements. Demo of APIScanner: https://youtu.be/1hy\_ugf-iek. Documentation, tool, and source code can be found here: https://rishitha957.github.io/APIScanner.

A successful application of an Internet of Things (IoT) based network depends on the accurate and successful delivery of a large amount of data collected from numerous sources. However, the highly dynamic nature of IoT network prevents the establishment of clear security perimeters and hampers the understanding of security aspects. Risk assessment in such networks requires good situational awareness with respect to security. Therefore, a comprehensive view of data propagation including information on security controls can improve security analysis and risk assessment in each layer of data propagation in an IoT architecture. Documentation of metadata is already used in data provenance to identify who generates which data, how, and when. However, documentation of security information is not seen as relevant for data provenance graphs. In this paper, we discuss the importance of adding security metadata in a data provenance graph. We propose a novel IoT Provenance model, Prov-IoT, which documents the history of data records considering data processing and aggregation along with security metadata to enable a foundation for trust in data. The model portrays a comprehensive framework and outlines the identification of information to be included in designing a security-aware provenance graph. This can be beneficial for uncovering system fault or intrusion. Also, it can be useful for decision-based systems for security analysis and risk estimation. We design an associated class diagram for the Prov-IoT model. Finally, we use an IoT healthcare example scenario to demonstrate the impact of the proposed model.

Inter-networked control systems make smart buildings increasingly efficient but can lead to severe operational disruptions and infrastructure damage. It is vital the security state of smart buildings is properly assessed so that thorough and cost effective risk management can be established. This paper uniquely reports on an actual risk assessment performed in 2018 on one of the world's most densely monitored, state-of-the-art, smart buildings. From our observations, we suggest that current practice may be inadequate due to a number of challenges and deficiencies, including the lack of a recognised smart building risk assessment methodology. As a result, the security posture of many smart buildings may not be as robust as their risk assessments suggest. Crucially, we highlight a number of key recommendations for a more comprehensive risk assessment process for smart buildings. As a whole, we believe this practical experience report will be of interest to a range of smart building stakeholders.

This paper describes a method for classifying onion sites. According to the results of the research, the most spread model of site in onion space is built. To create such a model, a specially trained neural network is used. The classification of neural network is based on five different categories such as using authentication system, corporate email, readable URL, feedback and type of onion-site. The statistics of the most spread types of websites in Dark Net are given.

A well-defined structure is essential in all software development, thus providing an avenue for smooth execution of the processes involved during various software development phases. One of the potential benefits provided by a well-defined structure is systematic reuse of software artifacts. Requirements pattern approach provides guidelines and modality that enables a systematic way of specifying and documenting requirements, which in turn supports a systematic reuse. Although there is a great deal of research concerning requirements pattern in the literature, the research focuses are not on requirement engineering (RE) activities of SPLE. In this paper, we proposed a software requirement pattern (SRP) structure based on RePa Requirements Pattern Template, which was adapted to best suit RE activities in SPLE. With this requirement pattern structure, RE activities such as elicitation and identification of common and variable requirements as well as the specification, documentation, and reuse in SPLE could be substantially improved.

This paper presents a case study on the use and implementation of the Qualified Digital Signature. Problematics such as the degree of use, security and authenticity of Qualified Digital Signature and the publication and dissemination of documents signed in digital format are analyzed. In order to support the case study, a methodology was adopted that included interviews with municipalities that are part of the Intermunicipal Community of the region of Leiria and a computer application was developed that allowed to analyze the documents available in the institutional websites of the municipalities, the ones that were digitally signed. The results show that institutional websites are already providing documentation with Qualified Digital Signature and that the level of trust and authenticity regarding their use is considered to be mostly very positive.

With the emergence of biometric technology in various applications, such as access control (e.g. mobile lock/unlock), financial transaction (e.g. Alibaba smile-to-pay) and time attendance, the development of biometric system attracts increasingly interest to the developers. Despite a sound biometric system gains the security assurance and great usability, it is a rather challenging task to develop an effective biometric system. For instance, many public available biometric APIs do not provide sufficient instructions / precise documentations on the usage of biometric APIs. Many developers are struggling in implementing these APIs in various tasks. Moreover, quick update on biometric-based algorithms (e.g. feature extraction and matching) may propagate to APIs, which leads to potential confusion to the system developers. Hence, we conduct an empirical study to the problems that the developers currently encountered while implementing the biometric APIs as well as the issues that need to be addressed when developing biometric systems using these APIs. We manually analyzed a total of 500 biometric API-related posts from various online media such as Stack Overflow and Neurotechnology. We reveal that 1) most of the problems encountered are related to the lack of precise documentation on the biometric APIs; 2) the incompatibility of biometric APIs cross multiple implementation environments.

Often, analysts have to face a challenging situation when formally verifying the implementation of a security protocol: they need to build a model of the protocol from only poorly or not documented code, and with little or no help from the developers to better understand it. Security protocols implementations frequently use services provided by libraries coded in the C programming language; automatic tools for codelevel reverse engineering offer good support to comprehend the behavior of code in object-oriented languages but are ineffective to deal with libraries in C. Here we propose a systematic, yet human-dependent approach, which combines the capabilities of state-of-the-art tools in order to help the analyst to retrieve, step by step, the security protocol specifications from a library in C. Those specifications can then be used to create the formal model needed to carry out the analysis.

The Industrial Control System (ICS) and Supervisory Control and Data Acquisition (SCADA) systems are the backbones for monitoring and supervising factories, power grids, water distribution systems, nuclear plants, and other critical infrastructures. These systems are installed by third party contractors, maintained by site engineers, and operate for a long time. This makes tracing the documentation of the systems' changes and updates challenging since some of their components' information (type, manufacturer, model, etc.) may not be up-to-date, leading to possibly unaccounted security vulnerabilities in the systems. Device recognition is useful first step in vulnerability identification and defense augmentation, but due to the lack of full traceability in case of legacy ICS/SCADA systems, the typical device recognition based on document inspection is not applicable. In this paper, we propose a hybrid approach involving the mix of communication-patterns and passive-fingerprinting to identify the unknown devices' types, manufacturers, and models. The algorithm uses the ICS/SCADA devices's communication-patterns to recognize the control hierarchy levels of the devices. In conjunction, certain distinguishable features in the communication-packets are used to recognize the device manufacturer, and model. We have implemented this hybrid approach in Python, and tested on traffic data from a water treatment SCADA testbed in Singapore (iTrust).

Potentially dangerous cryptography errors are well-documented in many applications. Conventional wisdom suggests that many of these errors are caused by cryptographic Application Programming Interfaces (APIs) that are too complicated, have insecure defaults, or are poorly documented. To address this problem, researchers have created several cryptographic libraries that they claim are more usable, however, none of these libraries have been empirically evaluated for their ability to promote more secure development. This paper is the first to examine both how and why the design and resulting usability of different cryptographic libraries affects the security of code written with them, with the goal of understanding how to build effective future libraries. We conducted a controlled experiment in which 256 Python developers recruited from GitHub attempt common tasks involving symmetric and asymmetric cryptography using one of five different APIs. We examine their resulting code for functional correctness and security, and compare their results to their self-reported sentiment about their assigned library. Our results suggest that while APIs designed for simplicity can provide security benefits - reducing the decision space, as expected, prevents choice of insecure parameters - simplicity is not enough. Poor documentation, missing code examples, and a lack of auxiliary features such as secure key storage, caused even participants assigned to simplified libraries to struggle with both basic functional correctness and security. Surprisingly, the availability of comprehensive documentation and easy-to-use code examples seems to compensate for more complicated APIs in terms of functionally correct results and participant reactions, however, this did not extend to security results. We find it particularly concerning that for about 20% of functionally correct tasks, across libraries, participants believed their code was secure when it was not. Our results suggest that while ne- cryptographic libraries that want to promote effective security should offer a simple, convenient interface, this is not enough: they should also, and perhaps more importantly, ensure support for a broad range of common tasks and provide accessible documentation with secure, easy-to-use code examples.

Increasing interest in cyber-physical systems with integrated computational and physical capabilities that can interact with humans can be identified in research and practice. Since these systems can be classified as safety- and security-critical systems the need for safety and security assurance and certification will grow. Moreover, these systems are typically characterized by fragmentation, interconnectedness, heterogeneity, short release cycles, cross organizational nature and high interference between safety and security requirements. These properties combined with the assurance of compliance to multiple standards, carrying out certification and re-certification, and the lack of an approach to model, document and integrate safety and security requirements represent a major challenge. In order to address this gap we developed a domain agnostic approach to model security and safety requirements in an integrated view to support certification processes during design and run-time phases of cyber-physical systems.

Despite the abundance of information security guidelines, system developers have difficulties implementing technical solutions that are reasonably secure. Security patterns are one possible solution to help developers reuse security knowledge. The challenge is that it takes experts to develop security patterns. To address this challenge, we need a framework to identify and assess patterns and pattern application practices that are accessible to non-experts. In this paper, we narrowly define what we mean by patterns by focusing on requirements patterns and the considerations that may inform how we identify and validate patterns for knowledge reuse. We motivate this discussion using examples from the requirements pattern literature and theory in cognitive psychology.