an analysis for understanding software security requirement methodologies

IEEE Reliabil Soc, Shanghai Jiao Tong Univ

Classifying And Predicting Software Security Vulnerabilities based on Reproducibility

Security defects are common in large software systems because of their size and complexity. Although efficient development processes, testing, and maintenance policies are applied to software systems, there are still a large number of vulnerabilities that can remain, despite these measures. Some vulnerabilities stay in a system from one release to the next one because they cannot be easily reproduced through testing. These vulnerabilities endanger the security of the systems. We propose vulnerability classification and prediction frameworks based on vulnerability reproducibility. The frameworks are effective to identify the types and locations of vulnerabilities in the earlier stage, and improve the security of software in the next versions (referred to as releases). We expand an existing concept of software bug classification to vulnerability classification (easily reproducible and hard to reproduce) to develop a classification framework for differentiating between these vulnerabilities based on code fixes and textual reports. We then investigate the potential correlations between the vulnerability categories and the classical software metrics and some other runtime environmental factors of reproducibility to develop a vulnerability prediction framework. The classification and prediction frameworks help developers adopt corresponding mitigation or elimination actions and develop appropriate test cases. Also, the vulnerability prediction framework is of great help for security experts focus their effort on the top-ranked vulnerability-prone files. As a result, the frameworks decrease the number of attacks that exploit security vulnerabilities in the next versions of the software. To build the classification and prediction frameworks, different machine learning techniques (C4.5 Decision Tree, Random Forest, Logistic Regression, and Naive Bayes) are employed. The effectiveness of the proposed frameworks is assessed based on collected software security defects of Mozilla Firefox.

Adaptive security for software systems

With continuously changing operational and business needs, system security is one of the key system capabilities that need to be updated as well. Most security engineering efforts focus on engineering security requirements of software systems at design time and existing adaptive security engineering efforts require complex design-time preparation. In this chapter we discuss the needs for adaptive software security, and key efforts in this area. We then introduce a new runtime adaptive security engineering approach, which enables adapting software security capabilities at runtime based on new security objectives, risks/threats, requirements as well as newly reported vulnerabilities. We categorize the source of adaptation in terms of manual adaptation (managed by end users), and automated adaption (automatically triggered by the platform). The new platform makes use of new ideas we built for vulnerability analysis, security engineering using aspect-oriented programming, and model-driven engineering techniques.

Security metrics for object-oriented class designs

Measuring quality attributes of object-oriented designs (e.g. maintainability and performance) has been covered by a number of studies. However, these studies have not considered security as much as other quality attributes. Also, most security studies focus at the level of individual program statements. This approach makes it hard and expensive to discover and fix vulnerabilities caused by design errors. In this work, we focus on the security design of an object oriented application and define a number of security metrics. These metrics allow designers to discover and fix security vulnerabilities at an early stage, and help compare the security of various alternative designs. In particular, we propose seven security metrics to measure Data Encapsulation (accessibility) and Cohesion (interactions) of a given object-oriented class from the point of view of potential information flow.

A hierarchical security assessment model for object-oriented programs

We present a hierarchical model for assessing an object-oriented program's security. Security is quantified using structural properties of the program code to identify the ways in which `classified' data values may be transferred between objects. The model begins with a set of low-level security metrics based on traditional design characteristics of object-oriented classes, such as data encapsulation, cohesion and coupling. These metrics are then used to characterise higher-level properties concerning the overall readability and writability of classified data throughout the program. In turn, these metrics are then mapped to well-known security design principles such as `assigning the least privilege' and `reducing the size of the attack surface'. Finally, the entire program's security is summarised as a single security index value. These metrics allow different versions of the same program, or different programs intended to perform the same task, to be compared for their relative security at a number of different abstraction levels. The model is validated via an experiment involving five open source Java programs, using a static analysis tool we have developed to automatically extract the security metrics from compiled Java bytecode.

Quality metrics for assessing security-critical computer programs

Existing secure software development principles tend to focus on coding vulnerabilities, such as buffer or integer overflows, that apply to individual program statements, or issues associated with the run-time environment, such as component isolation. Here we instead consider software security from the perspective of potential information flow through a program’s object-oriented module structure. In particular, we define a set of quantifiable "security metrics" which allow programmers to quickly and easily assess the overall security of a given source code program or object-oriented design. Although measuring quality attributes of object-oriented programs for properties such as maintainability and performance has been well-covered in the literature, metrics which measure the quality of information security have received little attention. Moreover, existing securityrelevant metrics assess a system either at a very high level, i.e., the whole system, or at a fine level of granularity, i.e., with respect to individual statements. These approaches make it hard and expensive to recognise a secure system from an early stage of development. Instead, our security metrics are based on well-established compositional properties of object-oriented programs (i.e., data encapsulation, cohesion, coupling, composition, extensibility, inheritance and design size), combined with data flow analysis principles that trace potential information flow between high- and low-security system variables. We first define a set of metrics to assess the security quality of a given object-oriented system based on its design artifacts, allowing defects to be detected at an early stage of development. We then extend these metrics to produce a second set applicable to object-oriented program source code. The resulting metrics make it easy to compare the relative security of functionallyequivalent system designs or source code programs so that, for instance, the security of two different revisions of the same system can be compared directly. This capability is further used to study the impact of specific refactoring rules on system security more generally, at both the design and code levels. By measuring the relative security of various programs refactored using different rules, we thus provide guidelines for the safe application of refactoring steps to security-critical programs. Finally, to make it easy and efficient to measure a system design or program’s security, we have also developed a stand-alone software tool which automatically analyses and measures the security of UML designs and Java program code. The tool’s capabilities are demonstrated by applying it to a number of security-critical system designs and Java programs. Notably, the validity of the metrics is demonstrated empirically through measurements that confirm our expectation that program security typically improves as bugs are fixed, but worsens as new functionality is added.

An automated tool for assessing security-critical designs and programs

This paper describes in detail our Security-Critical Program Analyser (SCPA). SCPA is used to assess the security of a given program based on its design or source code with regard to data flow-based metrics. Furthermore, it allows software developers to generate a UML-like class diagram of their program and annotate its confidential classes, methods and attributes. SCPA is also capable of producing Java source code for the generated design of a given program. This source code can then be compiled and the resulting Java bytecode program can be used by the tool to assess the program's overall security based on our security metrics.

Security assessment of code refactoring rules

Refactoring is a common approach to producing better quality software. Its impact on many software quality properties, including reusability, maintainability and performance, has been studied and measured extensively. However, its impact on the information security of programs has received relatively little attention. In this work, we assess the impact of a number of the most common code-level refactoring rules on data security, using security metrics that are capable of measuring security from the viewpoint of potential information flow. The metrics are calculated for a given Java program using a static analysis tool we have developed to automatically analyse compiled Java bytecode. We ran our Java code analyser on various programs which were refactored according to each rule. New values of the metrics for the refactored programs then confirmed that the code changes had a measurable effect on information security.

Software similarity and classification

This thesis analyses software programs in the context of their similarity to other software programs. Applications proposed and implemented include detecting malicious software and discovering security vulnerabilities.

XSOFT: estudo de reconhecimento, exploração e prevenção de vulnerabilidades de software através de uma distribuição LINUX

This work aims to give greater visibility to the issue of software security, due to people talk a lot in security conferences, that much of both IT (Information Technology) staff and, more specifically, IS (Information Security) staff does not know this, and, thanks to the spread of the mobile computing and of the cloud computing, this lack of deeper knowledge on this subject is increasingly becoming worrisome. It aims too, make applications to be developed in a security manner, priorizing the security of the information processed. It attempts to demonstrate the secure coding techniques, the principles of software security, the means to identify software vulnerabilities, the cutting-edge software exploitation techniques and the mechanisms of mitigation. Nowadays, the security guys are in charge of the most of the security tests in applications, audits and pentests, and it is undeniable that the so-called security experts, most often come from computer network field, having few experience in software development and programming. Therefore, the development process does not consider the security issue, thanks to the lack of knowledge on the subject by the developer, and the security tests could be improved whether security experts had a greater know-how on application development. Given this problem, the goal here is to integrate information security with software development, spreading out the process of secure software development. To achieve this, a Linux distribution with proof of concept applicati... (Complete abstract click electronic access below)

Guía para el desarrollo de software seguro

El presente Trabajo de Fin de Grado (TFG) es el resultado de la necesidad de la seguridad en la construcción del software ya que es uno de los mayores problemas con que se enfrenta hoy la industria debido a la baja calidad de la misma tanto en software de Sistema Operativo, como empotrado y de aplicaciones. La creciente dependencia de software para que se hagan trabajos críticos significa que el valor del software ya no reside únicamente en su capacidad para mejorar o mantener la productividad y la eficiencia. En lugar de ello, su valor también se deriva de su capacidad para continuar operando de forma fiable incluso de cara de los eventos que la amenazan. La capacidad de confiar en que el software seguirá siendo fiable en cualquier circunstancia, con un nivel de confianza justificada, es el objetivo de la seguridad del software. Seguridad del software es importante porque muchas funciones críticas son completamente dependientes del software. Esto hace que el software sea un objetivo de valor muy alto para los atacantes, cuyos motivos pueden ser maliciosos, penales, contenciosos, competitivos, o de naturaleza terrorista. Existen fuentes muy importantes de mejores prácticas, métodos y herramientas para mejorar desde los requisitos en sus aspectos no funcionales, ciclo de vida del software seguro, pasando por la dirección de proyectos hasta su desarrollo, pruebas y despliegue que debe ser tenido en cuenta por los desarrolladores. Este trabajo se centra fundamentalmente en elaborar una guía de mejores prácticas con la información existente CERT, CMMI, Mitre, Cigital, HP, y otras fuentes. También se plantea desarrollar un caso práctico sobre una aplicación dinámica o estática con el fin de explotar sus vulnerabilidades.---ABSTRACT---This Final Project Grade (TFG) is the result of the need for security in software construction as it is one of the biggest problems facing the industry today due to the low quality of it both OS software, embedded software and applications software. The increasing reliance on software for critical jobs means that the value of the software no longer resides solely in its capacity to improve or maintain productivity and efficiency. Instead, its value also stems from its ability to continue to operate reliably even when facing events that threaten it. The ability to trust that the software will remain reliable in all circumstances, with justified confidence level is the goal of software security. The security in software is important because many critical functions are completely dependent of the software. This makes the software to be a very high value target for attackers, whose motives may be by a malicious, by crime, for litigating, by competitiveness or by a terrorist nature. There are very important sources of best practices, methods and tools to improve the requirements in their non-functional aspects, the software life cycle with security in mind, from project management to its phases (development, testing and deployment) which should be taken into account by the developers. This paper focuses primarily on developing a best practice guide with existing information from CERT, CMMI, Mitre, Cigital, HP, and other organizations. It also aims to develop a case study on a dynamic or static application in order to exploit their vulnerabilities.

A Cloud-based Framework for Security Analysis of Browser Extensions

In today's internet world, web browsers are an integral part of our day-to-day activities. Therefore, web browser security is a serious concern for all of us. Browsers can be breached in different ways. Because of the over privileged access, extensions are responsible for many security issues. Browser vendors try to keep safe extensions in their official extension galleries. However, their security control measures are not always effective and adequate. The distribution of unsafe extensions through different social engineering techniques is also a very common practice. Therefore, before installation, users should thoroughly analyze the security of browser extensions. Extensions are not only available for desktop browsers, but many mobile browsers, for example, Firefox for Android and UC browser for Android, are also furnished with extension features. Mobile devices have various resource constraints in terms of computational capabilities, power, network bandwidth, etc. Hence, conventional extension security analysis techniques cannot be efficiently used by end users to examine mobile browser extension security issues. To overcome the inadequacies of the existing approaches, we propose CLOUBEX, a CLOUd-based security analysis framework for both desktop and mobile Browser EXtensions. This framework uses a client-server architecture model. In this framework, compute-intensive security analysis tasks are generally executed in a high-speed computing server hosted in a cloud environment. CLOUBEX is also enriched with a number of essential features, such as client-side analysis, requirements-driven analysis, high performance, and dynamic decision making. At present, the Firefox extension ecosystem is most susceptible to different security attacks. Hence, the framework is implemented for the security analysis of the Firefox desktop and Firefox for Android mobile browser extensions. A static taint analysis is used to identify malicious information flows in the Firefox extensions. In CLOUBEX, there are three analysis modes. A dynamic decision making algorithm assists us to select the best option based on some important parameters, such as the processing speed of a client device and network connection speed. Using the best analysis mode, performance and power consumption are improved significantly. In the future, this framework can be leveraged for the security analysis of other desktop and mobile browser extensions, too.

Five ways to hack and cheat with bring-your-own-device electronic examinations

Bring-your-own-device electronic examinations (BYOD e-exams) are a relatively new type of assessment where students sit an in-person exam under invigilated conditions with their own laptop. Special software restricts student access to prohibited computer functions and files, and provides access to any resources or software the examiner approves. In this study, the decades-old computer security principle that ‘software security depends on hardware security’ is applied to a range of BYOD e-exam tools. Five potential hacks are examined, four of which are confirmed to work against at least one BYOD e-exam tool. The consequences of these hacks are significant, ranging from removal of the exam paper from the venue through to receiving live assistance from an outside expert. Potential mitigation strategies are proposed; however, these are unlikely to completely protect the integrity of BYOD e-exams. Educational institutions are urged to balance the additional affordances of BYOD e-exams for examiners against the potential affordances for cheaters.

User Behavioral Modeling of Web-based Systems for Continuous User Authentication

Authentication plays an important role in how we interact with computers, mobile devices, the web, etc. The idea of authentication is to uniquely identify a user before granting access to system privileges. For example, in recent years more corporate information and applications have been accessible via the Internet and Intranet. Many employees are working from remote locations and need access to secure corporate files. During this time, it is possible for malicious or unauthorized users to gain access to the system. For this reason, it is logical to have some mechanism in place to detect whether the logged-in user is the same user in control of the user's session. Therefore, highly secure authentication methods must be used. We posit that each of us is unique in our use of computer systems. It is this uniqueness that is leveraged to "continuously authenticate users" while they use web software. To monitor user behavior, n-gram models are used to capture user interactions with web-based software. This statistical language model essentially captures sequences and sub-sequences of user actions, their orderings, and temporal relationships that make them unique by providing a model of how each user typically behaves. Users are then continuously monitored during software operations. Large deviations from "normal behavior" can possibly indicate malicious or unintended behavior. This approach is implemented in a system called Intruder Detector (ID) that models user actions as embodied in web logs generated in response to a user's actions. User identification through web logs is cost-effective and non-intrusive. We perform experiments on a large fielded system with web logs of approximately 4000 users. For these experiments, we use two classification techniques; binary and multi-class classification. We evaluate model-specific differences of user behavior based on coarse-grain (i.e., role) and fine-grain (i.e., individual) analysis. A specific set of metrics are used to provide valuable insight into how each model performs. Intruder Detector achieves accurate results when identifying legitimate users and user types. This tool is also able to detect outliers in role-based user behavior with optimal performance. In addition to web applications, this continuous monitoring technique can be used with other user-based systems such as mobile devices and the analysis of network traffic.