Algorithmic Diversity for Software Security

Software diversity protects against a modern-day exploits such as code-reuse attacks. When an attacker designs a code-reuse attack on an example executable, it relies on replicating the target environment. With software diversity, the attacker cannot reliably replicate their target. This is a security benefit which can be applied to massive-scale software distribution. When applied to large-scale communities, an invested attacker may perform analysis of samples to improve the chances of a successful attack (M. Franz). We present a general NOP-insertion algorithm which can be expanded and customized for security, performance, or other costs. We demonstrate an improvement in security so that a code-reuse attack based on any one variant has minimal chances of success on another and analyse the costs of this method. Alternately, the variants may be customized to meet performance or memory overhead constraints. Deterministic diversification allows for the flexibility to balance these needs in a way that doesn't exist in a random online method

Vulnerability anti-patterns:a timeless way to capture poor software practices (Vulnerabilities)

There is a distinct communication gap between the software engineering and cybersecurity communities when it comes to addressing reoccurring security problems, known as vulnerabilities. Many vulnerabilities are caused by software errors that are created by software developers. Insecure software development practices are common due to a variety of factors, which include inefficiencies within existing knowledge transfer mechanisms based on vulnerability databases (VDBs), software developers perceiving security as an afterthought, and lack of consideration of security as part of the software development lifecycle (SDLC). The resulting communication gap also prevents developers and security experts from successfully sharing essential security knowledge. The cybersecurity community makes their expert knowledge available in forms including vulnerability databases such as CAPEC and CWE, and pattern catalogues such as Security Patterns, Attack Patterns, and Software Fault Patterns. However, these sources are not effective at providing software developers with an understanding of how malicious hackers can exploit vulnerabilities in the software systems they create. As developers are familiar with pattern-based approaches, this paper proposes the use of Vulnerability Anti-Patterns (VAP) to transfer usable vulnerability knowledge to developers, bridging the communication gap between security experts and software developers. The primary contribution of this paper is twofold: (1) it proposes a new pattern template – Vulnerability Anti-Pattern – that uses anti-patterns rather than patterns to capture and communicate knowledge of existing vulnerabilities, and (2) it proposes a catalogue of Vulnerability Anti-Patterns (VAP) based on the most commonly occurring vulnerabilities that software developers can use to learn how malicious hackers can exploit errors in software

Persistent issues in encryption software: A heuristic and cognitive walkthrough

The support information accompanying security software can be difficult to understand by end-users, who have little knowledge in cyber security. One mechanism for ensuring the integrity and confidentiality of information is encryption software. Unfortunately, software usability issues can hinder an end-user’s capability to properly utilise the security features effectively. To date there has been little research in investigating the usability of encryption software and proposing solutions for improving them. This research paper analysed the usability of encryption software targeting end-users. The research identified several issues that could impede the ability of a novice end-user to adequately utilise the encryption software. A set of proposed recommendations are suggested to improve encryption software which could be empirically verified through further research

The Effect of Security Education and Expertise on Security Assessments: the Case of Software Vulnerabilities

In spite of the growing importance of software security and the industry demand for more cyber security expertise in the workforce, the effect of security education and experience on the ability to assess complex software security problems has only been recently investigated. As proxy for the full range of software security skills, we considered the problem of assessing the severity of software vulnerabilities by means of a structured analysis methodology widely used in industry (i.e. the Common Vulnerability Scoring System (\CVSS) v3), and designed a study to compare how accurately individuals with background in information technology but different professional experience and education in cyber security are able to assess the severity of software vulnerabilities. Our results provide some structural insights into the complex relationship between education or experience of assessors and the quality of their assessments. In particular we find that individual characteristics matter more than professional experience or formal education; apparently it is the \emph{combination} of skills that one owns (including the actual knowledge of the system under study), rather than the specialization or the years of experience, to influence more the assessment quality. Similarly, we find that the overall advantage given by professional expertise significantly depends on the composition of the individual security skills as well as on the available information.Comment: Presented at the Workshop on the Economics of Information Security (WEIS 2018), Innsbruck, Austria, June 201

A UML-based static verification framework for security

Secure software engineering is a new research area that has been proposed to address security issues during the development of software systems. This new area of research advocates that security characteristics should be considered from the early stages of the software development life cycle and should not be added as another layer in the system on an ad-hoc basis after the system is built. In this paper, we describe a UML-based Static Verification Framework (USVF) to support the design and verification of secure software systems in early stages of the software development life-cycle taking into consideration security and general requirements of the software system. USVF performs static verification on UML models consisting of UML class and state machine diagrams extended by an action language. We present an operational semantics of UML models, define a property specification language designed to reason about temporal and general properties of UML state machines using the semantic domains of the former, and implement the model checking process by translating models and properties into Promela, the input language of the SPIN model checker. We show that the methodology can be applied to the verification of security properties by representing the main aspects of security, namely availability, integrity and confidentiality, in the USVF property specification language