Security Attacks and Countermeasures in Smart Homes

The Internet of Things (IoT) application is visible in all aspects of humans’ day-to-day affairs. The demand for IoT is growing at an unprecedented rate, from wearable wristwatches to autopilot cars. The smart home has also seen significant advancements to improve the quality of lifestyle. However, the security and privacy of IoT devices have become primary concerns as data is shared among intelligent devices and over the internet in a smart home network. There are several attacks - node capturing attack, sniffing attack, malware attack, boot phase attack, etc., which are conducted by adversaries to breach the security of smart homes. The security breach has a negative impact on the tenants\u27 privacy and prevents the availability of smart home services. This article presents smart homes\u27 most common security attacks and mitigation techniques

Adapting In-Game Agent Behavior by Observation of Players Using Learning Behavior Trees

In this paper we describe Learning Behavior Trees, an extension of the popular game AI scripting technique. Behavior Trees provide an effective way for expert designers to describe complex, in-game agent behaviors. Scripted AI captures human intuition about the structure of behavioral decisions, but suffers from brittleness and lack of the natural variation seen in human players. Learning Behavior Trees are designed by a human designer, but then are trained by observation of players performing the same role, to introduce human-like variation to the decision structure. We show that, using this model, a single hand-designed Behavior Tree can cover a wide variety of player behavior variations in a simplified Massively Multiplayer Online Role-Playing Game

A survey on security analysis of machine learning-oriented hardware and software intellectual property

Intellectual Property (IP) includes ideas, innovations, methodologies, works of authorship (viz., literary and artistic works), emblems, brands, images, etc. This property is intangible since it is pertinent to the human intellect. Therefore, IP entities are indisputably vulnerable to infringements and modifications without the owner’s consent. IP protection regulations have been deployed and are still in practice, including patents, copyrights, contracts, trademarks, trade secrets, etc., to address these challenges. Unfortunately, these protections are insufficient to keep IP entities from being changed or stolen without permission. As for this, some IPs require hardware IP protection mechanisms, and others require software IP protection techniques. To secure these IPs, researchers have explored the domain of Intellectual Property Protection (IPP) using different approaches. In this paper, we discuss the existing IP rights and concurrent breakthroughs in the field of IPP research; provide discussions on hardware IP and software IP attacks and defense techniques; summarize different applications of IP protection; and lastly, identify the challenges and future research prospects in hardware and software IP security

A survey on security analysis of Amazon echo devices

Since its launch in 2014, Amazon Echo family of devices has seen a considerable increase in adaptation in consumer homes and offices. With a market worth millions of dollars, Echo is used for diverse tasks such as accessing online information, making phone calls, purchasing items, and controlling the smart home. Echo offers user-friendly voice interaction to automate everyday tasks making it a massive success. Though many people view Amazon Echo as a helpful assistant at home or office, few know its underlying security and privacy implications. In this paper, we present the findings of our research on Amazon Echo’s security and privacy concerns. The findings are divided into different categories by vulnerability or attacks. The proposed mitigation(s) to the vulnerabilities are also presented in the paper. We conclude that though numerous privacy concerns and security vulnerabilities associated with the device are mitigated, many vulnerabilities still need to be addressed

Infusing Raspberry Pi in the Computer Science Curriculum for Enhanced Learning

With the advent of cloud computing, the Internet of Things (IoT), and mobile computing, CS faculty are continuously revamping the curriculum material to address such burgeoning set of technologies in practical and relatable ways. Raspberry Pi (RPi) devices represent an ideal hardware/software framework that embodies all these technologies through its simple architecture, small form factor (that minimizes the volume and footprint of a desktop computer), and ability to integrate various sensors that network together and connect to the Cloud. Therefore, one of the strategies of Computer Science Department, to enhance depth of learning concepts, has been to infuse Raspberry Pi (RPi) in computer science courses. RPi has been incorporated since 2016 in targeted courses, notably, Computer Organization & Assembly Language, Computer Architecture, Database Management Design & Implementation, Unix/Linux Programming, Internet Programming, and Senior Project. An inexpensive credit card sized computer, an RPi lends itself to allow depth of learning of concepts. From implementing firewalls, intrusion detection systems, scripting, client-server based computing, distributed computing, to interfacing with sensors and actuators, a student is guided to polish concepts taught in a class through RPi Project Based Learning (RPBL). Computer science curriculum already provides breadth of learning. The infusion of RPi in key courses provides depth in targeted concepts. There are peripheral desirable consequences as well, including a student learning prevalently used Linux environment even though a targeted course may have nothing directly to do with Linux. Furthermore, RPi provides an opportunity for students to realize that software programs can be interfaced with sensors and actuators to provide immersed experience in programming. From simply interfacing a switch and a Light Emitting Diode (LED) to getting data from sensors, buffering, and uploading to the cloud, a student already would have touched upon multiple disciplines in computer science. This paper provides a blueprint to infusing RPi in the targeted courses, and how each RPi based project provides depth to a targeted concept

Improving STEM Education in Research: Preliminary Report on the Development of a Computer-Assisted Student-Mentor Research Community

Research education in STEM disciplines currently suffers from 1) The inability to feasibly collect highly detailed data on both the student’s and mentor’s activities; 2) The lack of tools to assist students and mentors in organizing and managing their research activities and environments; and 3) The inability to correlate a student’s assessment results with their actual research activities. Together these three problems act to impede both the improvement and educational quality of student research experiences. We propose a computer-assisted student-mentor research community as a solution to these problems. Within this community setting, students and their mentors are provided tools to make their work easier, much like a word processor makes writing a letter easier. Through their use of these tools, details of student-mentor activities are automatically recorded in a relational database, without burdening users with the responsibility of archiving data. Equally important, student assessments of outcome can be directly related to student activity, allowing educators to identify practices resulting in successful research experiences. Community tools also facilitate the use of labor-intensive teaching laboratories involving real inquiry-based research. The community structure has the added benefit of allowing students to see, communicate and interact more freely with other students and their projects, thus enriching the student’s research experience. We provide herein a preliminary report on the development and testing of a prototype, student-mentor research community, and present its tools, an assessment of student interest in participating in the community, and discuss its further development into a nationally-available student-mentor research community

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Towards Adaptive Quest Narrative in Shared, Persistent Virtual Worlds

In this paper, we discuss motivations for studying interactive narrative in shared, persistent worlds using the established conventions of quest-based MMORPGs.  We present a framework for categorizing the various techniques used in these games according to the interaction between the world model and the quest model.  Using this framework we generalize recent games to present a more dynamic world model, and investigate extensions to the quest model to support storytelling through adaptive quest narratives