Biblio

To protect against misuse of passwords compromised in a breach, consumers should promptly change affected passwords and any similar passwords on other accounts. Ideally, affected companies should strongly encourage this behavior and have mechanisms in place to mitigate harm. In order to make recommendations to companies about how to help their users perform these and other security-enhancing actions after breaches, we must first have some understanding of the current effectiveness of companies’ post-breach practices. To study the effectiveness of password-related breach notifications and practices enforced after a breach, we examine—based on real-world password data from 249 participants—whether and how constructively participants changed their passwords after a breach announcement. Of the 249 participants, 63 had accounts on breached domains; only 33% of the 63 changed their passwords and only 13% (of 63) did so within three months of the announcement. New passwords were on average 1.3× stronger than old passwords (when comparing log10-transformed strength), though most were weaker or of equal strength. Concerningly, new passwords were overall more similar to participants’ other passwords, and participants rarely changed passwords on other sites even when these were the same or similar to their password on the breached domain. Our results highlight the need for more rigorous passwordchanging requirements following a breach and more effective breach notifications that deliver comprehensive advice.

The design of modern computer hardware heavily relies on third-party intellectual property (IP) cores, which may contain malicious hardware Trojans that could be exploited by an adversary to leak secret information or take control of the system. Existing hardware Trojan detection methods either require a golden reference design for comparison or extensive functional testing to identify suspicious signals. In this paper, we propose a new formal verification method to verify the security of hardware designs. The proposed solution formalizes fine grained gate level information flow model for proving security properties of hardware designs in the Coq theorem prover environment. Compare with existing register transfer level (RTL) information flow security models, our model only needs to translate a small number of logic primitives to their formal representations without the need of supporting the rich RTL HDL semantics or dealing with complex conditional branch or loop structures. As a result, a gate level information flow model can be created at much lower complexity while achieving significantly higher precision in modeling the security behavior of hardware designs. We use the AES-T1700 benchmark from Trust-HUB to demonstrate the effectiveness of our solution. Experimental results show that our method can detect and pinpoint the Trojan.

The Security Behavior Intentions Scale (SeBIS) measures the computer security attitudes of end-users. Because intentions are a prerequisite for planned behavior, the scale could therefore be useful for predicting users' computer security behaviors. We performed three experiments to identify correlations between each of SeBIS's four sub-scales and relevant computer security behaviors. We found that testing high on the awareness sub-scale correlated with correctly identifying a phishing website; testing high on the passwords sub-scale correlated with creating passwords that could not be quickly cracked; testing high on the updating sub-scale correlated with applying software updates; and testing high on the securement sub-scale correlated with smartphone lock screen usage (e.g., PINs). Our results indicate that SeBIS predicts certain computer security behaviors and that it is a reliable and valid tool that should be used in future research.