BlackWatch:increasing attack awareness within web applications

Web applications are relied upon by many for the services they provide. It is essential that applications implement appropriate security measures to prevent security incidents. Currently, web applications focus resources towards the preventative side of security. Whilst prevention is an essential part of the security process, developers must also implement a level of attack awareness into their web applications. Being able to detect when an attack is occurring provides applications with the ability to execute responses against malicious users in an attempt to slow down or deter their attacks. This research seeks to improve web application security by identifying malicious behaviour from within the context of web applications using our tool BlackWatch. The tool is a Python-based application which analyses suspicious events occurring within client web applications, with the objective of identifying malicious patterns of behaviour. This approach avoids issues typically encountered with traditional web application firewalls. Based on the results from a preliminary study, BlackWatch was effective at detecting attacks from both authenticated, and unauthenticated users. Furthermore, user tests with developers indicated BlackWatch was user friendly, and was easy to integrate into existing applications. Future work seeks to develop the BlackWatch solution further for public release

Investigating Automatic Static Analysis Results to Identify Quality Problems: an Inductive Study

Background: Automatic static analysis (ASA) tools examine source code to discover "issues", i.e. code patterns that are symptoms of bad programming practices and that can lead to defective behavior. Studies in the literature have shown that these tools find defects earlier than other verification activities, but they produce a substantial number of false positive warnings. For this reason, an alternative approach is to use the set of ASA issues to identify defect prone files and components rather than focusing on the individual issues. Aim: We conducted an exploratory study to investigate whether ASA issues can be used as early indicators of faulty files and components and, for the first time, whether they point to a decay of specific software quality attributes, such as maintainability or functionality. Our aim is to understand the critical parameters and feasibility of such an approach to feed into future research on more specific quality and defect prediction models. Method: We analyzed an industrial C# web application using the Resharper ASA tool and explored if significant correlations exist in such a data set. Results: We found promising results when predicting defect-prone files. A set of specific Resharper categories are better indicators of faulty files than common software metrics or the collection of issues of all issue categories, and these categories correlate to different software quality attributes. Conclusions: Our advice for future research is to perform analysis on file rather component level and to evaluate the generalizability of categories. We also recommend using larger datasets as we learned that data sparseness can lead to challenges in the proposed analysis proces

APIs and Your Privacy

Application programming interfaces, or APIs, have been the topic of much recent discussion. Newsworthy events, including those involving Facebook’s API and Cambridge Analytica obtaining information about millions of Facebook users, have highlighted the technical capabilities of APIs for prominent websites and mobile applications. At the same time, media coverage of ways that APIs have been misused has sparked concern for potential privacy invasions and other issues of public policy. This paper seeks to educate consumers on how APIs work and how they are used within popular websites and mobile apps to gather, share, and utilize data. APIs are used in mobile games, search engines, social media platforms, news and shopping websites, video and music streaming services, dating apps, and mobile payment systems. If a third-party company, like an app developer or advertiser, would like to gain access to your information through a website you visit or a mobile app or online service you use, what data might they obtain about you through APIs and how? This report analyzes 11 prominent online services to observe general trends and provide you an overview of the role APIs play in collecting and distributing information about consumers. For example, how might your data be gathered and shared when using your Facebook account login to sign up for Venmo or to access the Tinder dating app? How might advertisers use Pandora’s API when you are streaming music? After explaining what APIs are and how they work, this report categorizes and characterizes different kinds of APIs that companies offer to web and app developers. Services may offer content-focused APIs, feature APIs, unofficial APIs, and analytics APIs that developers of other apps and websites may access and use in different ways. Likewise, advertisers can use APIs to target a desired subset of a service’s users and possibly extract user data. This report explains how websites and apps can create user profiles based on your online behavior and generate revenue from advertiser-access to their APIs. The report concludes with observations on how various companies and platforms connecting through APIs may be able to learn information about you and aggregate it with your personal data from other sources when you are browsing the internet or using different apps on your smartphone or tablet. While the paper does not make policy recommendations, it demonstrates the importance of approaching consumer privacy from a broad perspective that includes first parties and third parties, and that considers the integral role of APIs in today’s online ecosystem

How to Find Suitable Ontologies Using an Ontology-based WWW Broker

Knowledge reuse by means of outologies now faces three important problems: (1) there are no standardized identifying features that characterize ontologies from the user point of view; (2) there are no web sites using the same logical organization, presenting relevant information about ontologies; and (3) the search for appropriate ontologies is hard, time-consuming and usually fruitless. To solve the above problems, we present: (1) a living set of features that allow us to characterize ontologies from the user point of view and have the same logical organization; (2) a living domain ontology about ontologies (called ReferenceOntology) that gathers, describes and has links to existing ontologies; and (3) (ONTO)2Agent, the ontology-based www broker about ontologies that uses the Reference Ontology as a source of its knowledge and retrieves descriptions of ontologies that satisfy a given set of constraints. (ONTO)~Agent is available at http://delicias.dia.fi.upm.es/REFERENCE ONTOLOGY