Recently, research studies have focused on quantifying suicidality in the autistic population. A crucial finding of this research is that Autistics are four to eight times more likely to die by suicide, yet the risk is often missed by common diagnostic approaches. While this is important, studies overlook a demographic group with the highest suicidality rate: autistic women. Not only have studies shown autistic women are more likely to die, roughly 40\% are misdiagnosed or get no diagnosis. This adds an additional layer of methodological challenges in aforementioned studies into suicidality and autism as study populations include only diagnosed Autistics. This implies that future studies should aim to recruit participants not according to the demographics of the diagnosed autistic population but by the demographics of diagnosed and undiagnosed autistic population. Without this updated approach, the likelihood of undiagnosed suicidality in the highest risk category, autistic females, continues to exist and this can cause treatment delay in individuals with a high clinical need. This talk discusses the critical need for correct populations and targeted understanding of key subgroups.
Undoubtedly, a community is best fostered when all members of the community having an equitable opportunity to contribute their unique gifts and strengths, regardless of their gender and ability status. However, diverse accessibility requires an additional cognitive load and efforts that professionals with disabilities put forth towards this load are rarely addressed in Statistics and Data Science (SDS), especially for those at the intersection with other marginalized identities like women or non-binary people. During this session, the invited panelists with various disabilities – both visible and invisible – will share their lived experiences on the intersection as womxn with different accessibility needs and challenges. They will be invited to share their journey in SDS, the valuable lessons they've learned from their journey and unique challenges, and how their disabilities may have helped them become a more productive professional and/or a better human being. The panel will conclude with a discussion to engage the audience with best practices for accessibility and inclusivity in SDS.
This webinar will provide an overview of resources that help job seekers with disabilities navigate transitions between school and work, as well as testimonials. Many statisticians alternate between holding a professional position and attending educational programs, often leading to multiple transitions between school and work throughout one's career trajectory. This webinar brings together experts on accommodations for transitions to work as well as statisticians with disabilities who have experienced transitions between school and work during their careers. A Q&A and discussion period will follow the presentations. All are welcome to attend the webinar.
Erin is a mathematician and computer scientist who is very autistic, has ADHD and several severe psychological conditions in addition to chronic kidney disease. Erin will talk about the decision to disclose, preparing for the accommodations process, things to do to protect yourself, and how to handle disclosing to coworkers if they need to be involved in accommodations.
The topic of injustice, inequity, lack of diversity, and barriers to inclusion is widely discussed in education, employment, professional practices, policy development, and other social settings. In the statistics and data science community, we have initiatives and activities that are focused on providing opportunities to various intersectional groups in the field. This panel will discuss some of the efforts that have been and are being made to move the field of statistical sciences toward practicing justice, equity, diversity, and inclusion both internally on their boards and committees and throughout the organizations they serve. The panelists represent the Committee on Minorities in Statistics, the Committee on Statistics and Disability, the Committee on Women in Statistics, the Justice, Equity, Diversity, and Inclusion (JEDI) Outreach Group, the LGBTQ+ Advocacy Committee, the Membership Council, and the Washington Statistical Society. They will each share the work of their organizations, the successes and challenges, and how others can become involved.
In this paper, we provide the initial steps towards a botnet deception mechanism, which we call 2face. 2face provides deception capabilities in both directions – upward, to the command and control (CnC) server, and downward, towards the botnet nodes – to provide administrators with the tools they need to discover and eradicate an infestation within their network without alerting the botnet owner that they have been discovered. The key to 2face is a set of mechanisms for rapidly reverse engineering the protocols used within a botnet. The resulting protocol descriptions can then be used with the 2face network deception tool to generate high-quality deceptive messaging, against the attacker. As context for our work, we show how 2face can be used to help reverse engineer and then generate deceptive traffic for the Mirai protocol. We also discuss how this work could be extended to address future threats.
https://scholarspace.manoa.hawaii.edu/items/5bae15d5-e612-4033-838d-e04a7d860cf1
Using pervasive provenance to secure mainstream systems has recently attracted interest from industry and government. Recording, storing and managing all of the provenance associated with a system is a considerable challenge. Analyzing the resulting noisy, heterogeneous, continuously-growing provenance graph adds to this challenge, and apparently necessitates segmentation, that is, approximating, compressing or summarizing part or all of the graph in order to identify patterns or features. In this paper, we describe this new problem space for provenance data management, contrast it with related problem spaces addressed by prior work on provenance abstraction and sanitization, and highlight challenges and future directions toward solutions to the provenance segmentation problem.
https://www.usenix.org/conference/tapp16/workshop-program/presentation/abreu
Multinational teams are becoming the standard as companies compete globally. We hear stories of US-based teams who prefer Agile development practices but who encounter growing pains, including cultural and time zone differences, when they add overseas contributors.
Engineering teams want to collaborate and work well together regardless of how they may be distributed. This case study delves into the problems we experienced on one team spread across two continents (in United States and India). To bridge the differences and solve these problems, we had to take the time to really communicate with one another about how each site interpreted Agile concepts, what they saw as the main obstacles to development, and how we could best solve problems without sacrificing our priorities.
The solution was not for the team members at one site to issue a process to the entire team; instead we collaboratively reached a solution that ensured communication between sites, decreased turnaround time, improved quality, and received buy-in from the whole engineering team. Some of the practices we have put into place could assist other teams in being successful working across development sites.
In the end, we found that Agile development can work internationally if the process has enough structure, team knowledge is made more explicit, and everyone’s voice is heard.
https://www.pnsqc.org/archives/success-failure-got-agile-work-distributed-international-team/
Despite the use of strong encryption schemes, one can still learn information about encrypted data using side channel attacks [2]. Watching what physical memory is being accessed can be such a side channel. One can hide this information by using oblivious simulation - hiding the true access pattern of a program. In this paper we will review the model behind oblivious simulation, attempt to formalize the problem and define a security game. We will review the major solutions pro- posed so far, the square root and hierarchical solutions, as well as propose a new variation on the square root solution. Additionally, we will show a new formalization for providing software protection by using an encryption scheme and oblivious simulation.
https://magazine.amstat.org/blog/2022/07/01/my-asa-story-erin-chapman/