User experiences of TORPEDO: TOoltip-poweRed Phishing Email DetectiOn

We propose a concept called TORPEDO to improve phish detection by providing just-in-time and just-in-place trustworthy tooltips. These help people to identify phish links embedded in emails. TORPEDO's tooltips contain the actual URL with the domain highlighted. Link activation is delayed for a short period, giving the person time to inspect the URL before they click on a link. Furthermore, TORPEDO provides an information diagram to explain phish detection. We evaluated TORPEDO's effectiveness, as compared to the worst case “status bar” as provided by other Web email interfaces. People using TORPEDO performed significantly better in detecting phishes and identifying legitimate emails (85.17% versus 43.31% correct answers for phish). We then carried out a field study with a number of TORPEDO users to explore actual user experiences of TORPEDO. We conclude the paper by reporting on the outcome of this field study and suggest improvements based on the feedback from the field study participants

A secure searcher for end-to-end encrypted email communication

Email has become a common mode of communication for confidential personal as well as business needs. There are different approaches to authenticate the sender of an email message at the receiver‟s client and ensure that the message can be read only by the intended recipient. A typical approach is to use an email encryption standard to encrypt the message on the sender‟s client and decrypt it on the receiver‟s client for secure communication. A major drawback of this approach is that only the encrypted email messages are stored in the mail servers and the default search does not work on encrypted data. This project details an approach that could be adopted for securely searching email messages protected using end-to-end encrypted email communication. This project proposes an overall design for securely searching encrypted email messages and provides an implementation in Java based on a cryptographically secure Bloom filter technique to create a secure index. The implemented library is then integrated with an open source email client to depict its usability in a live environment. The technique and the implemented library are further evaluated for security and scalability while allowing remote storage of the created secure index. The research in this project would enhance email clients that support encrypted email transfer with a full secure search functionality

The Value of User-Visible Internet Cryptography

Cryptographic mechanisms are used in a wide range of applications, including email clients, web browsers, document and asset management systems, where typical users are not cryptography experts. A number of empirical studies have demonstrated that explicit, user-visible cryptographic mechanisms are not widely used by non-expert users, and as a result arguments have been made that cryptographic mechanisms need to be better hidden or embedded in end-user processes and tools. Other mechanisms, such as HTTPS, have cryptography built-in and only become visible to the user when a dialogue appears due to a (potential) problem. This paper surveys deployed and potential technologies in use, examines the social and legal context of broad classes of users, and from there, assesses the value and issues for those users

Machine learning approach for detection of nonTor traffic

Intrusion detection has attracted a considerable interest from researchers and industry. After many years of research the community still faces the problem of building reliable and efficient intrusion detection systems (IDS) capable of handling large quantities of data with changing patterns in real time situations. The Tor network is popular in providing privacy and security to end user by anonymizing the identity of internet users connecting through a series of tunnels and nodes. This work identifies two problems; classification of Tor traffic and nonTor traffic to expose the activities within Tor traffic that minimizes the protection of users in using the UNB-CIC Tor Network Traffic dataset and classification of the Tor traffic flow in the network. This paper proposes a hybrid classifier; Artificial Neural Network in conjunction with Correlation feature selection algorithm for dimensionality reduction and improved classification performance. The reliability and efficiency of the propose hybrid classifier is compared with Support Vector Machine and naïve Bayes classifiers in detecting nonTor traffic in UNB-CIC Tor Network Traffic dataset. Experimental results show the hybrid classifier, ANN-CFS proved a better classifier in detecting nonTor traffic and classifying the Tor traffic flow in UNB-CIC Tor Network Traffic dataset

Developing and evaluating a five minute phishing awareness video

Confidence tricksters have always defrauded the unwary. The computer era has merely extended their range and made it possible for them to target anyone in the world who has an email address. Nowadays, they send phishing messages that are specially crafted to deceive. Improving user awareness has the potential to reduce their effectiveness. We have previously developed and empirically-validated phishing awareness programmes. Our programmes are specifically designed to neutralize common phish-related misconceptions and teach people how to detect phishes. Many companies and individuals are already using our programmes, but a persistent niggle has been the amount of time required to complete the awareness programme. This paper reports on how we responded by developing and evaluating a condensed phishing awareness video that delivered phishing awareness more efficiently. Having watched our video, participants in our evaluation were able to detect phishing messages significantly more reliably right after watching the video (compared to before watching the video). This ability was also demonstrated after a retention period of eight weeks after first watching the video

Understanding and Identifying Vulnerabilities Related to Architectural Security Tactics

To engineer secure software systems, software architects elicit the system\u27s security requirements to adopt suitable architectural solutions. They often make use of architectural security tactics when designing the system\u27s security architecture. Security tactics are reusable solutions to detect, resist, recover from, and react to attacks. Since security tactics are the building blocks of a security architecture, flaws in the adoption of these tactics, their incorrect implementation, or their deterioration during software maintenance activities can lead to vulnerabilities, which we refer to as tactical vulnerabilities . Although security tactics and their correct adoption/implementation are crucial elements to achieve security, prior works have not investigated the architectural context of vulnerabilities. Therefore, this dissertation presents a research work whose major goals are: (i) to identify common types of tactical vulnerabilities, (ii) to investigate tactical vulnerabilities through in-depth empirical studies, and (iii) to develop a technique that detects tactical vulnerabilities caused by object deserialization. First, we introduce the Common Architectural Weakness Enumeration (CAWE), which is a catalog that enumerates 223 tactical vulnerability types. Second, we use this catalog to conduct an empirical study using vulnerability reports from large-scale open-source systems. Among our findings, we observe that Improper Input Validation was the most reoccurring vulnerability type. This tactical vulnerability type is caused by not properly implementing the Validate Inputs tactic. Although prior research focused on devising automated (or semi-automated) techniques for detecting multiple instances of improper input validation (e.g., SQL Injection and Cross-Site Scripting) one of them got neglected, which is the untrusted deserialization of objects. Unlike other input validation problems, object deserialization vulnerabilities exhibit a set of characteristics that are hard to handle for effective vulnerability detection. We currently lack a robust approach that can detect untrusted deserialization problems. Hence, this dissertation introduces DODO untrusteD ObjectDeserialization detectOr), a novel program analysis technique to detect deserialization vulnerabilities. DODO encompasses a sound static analysis of the program to extract potentially vulnerable paths, an exploit generation engine, and a dynamic analysis engine to verify the existence of untrusted object deserialization. Our experiments showed that DODO can successfully infer possible vulnerabilities that could arise at runtime during object deserialization

Attribute-Based, Usefully Secure Email

A secure system that cannot be used by real users to secure real-world processes is not really secure at all. While many believe that usability and security are diametrically opposed, a growing body of research from the field of Human-Computer Interaction and Security (HCISEC) refutes this assumption. All researchers in this field agree that focusing on aligning usability and security goals can enable the design of systems that will be more secure under actual usage. We bring to bear tools from the social sciences (economics, sociology, psychology, etc.) not only to help us better understand why deployed systems fail, but also to enable us to accurately characterize the problems that we must solve in order to build systems that will be secure in the real world. Trust, a critically important facet of any socio-technical secure system, is ripe for analysis using the tools provided for us by the social sciences. There are a variety of scopes in which issues of trust in secure systems can be stud- ied. We have chosen to focus on how humans decide to trust new correspondents. Current secure email systems such as S/MIME and PGP/MIME are not expressive enough to capture the real ways that trust flows in these sorts of scenarios. To solve this problem, we begin by applying concepts from social science research to a variety of such cases from interesting application domains; primarily, crisis management in the North American power grid. We have examined transcripts of telephone calls made between grid manage- ment personnel during the August 2003 North American blackout and extracted several different classes of trust flows from these real-world scenarios. Combining this knowl- edge with some design patterns from HCISEC, we develop criteria for a system that will enable humans apply these same methods of trust-building in the digital world. We then present Attribute-Based, Usefully Secure Email (ABUSE) and not only show that it meets our criteria, but also provide empirical evidence that real users are helped by the system