Security Threat Analyses and Attack Models for Approximate Computing Systems

2021 ◽  
Vol 26 (4) ◽  
pp. 1-31
Author(s):  
Pruthvy Yellu ◽  
Landon Buell ◽  
Miguel Mark ◽  
Michel A. Kinsy ◽  
Dongpeng Xu ◽  
...  
Keyword(s):  
Error Resilience ◽  
Security Threats ◽  
Approximate Computing ◽  
Security Threat ◽  
Security Vulnerabilities ◽  
Computing Systems ◽  
Quantitative Analyses ◽  
Resilience Mechanisms ◽  
The Impact ◽  
Attack Models

Approximate computing (AC) represents a paradigm shift from conventional precise processing to inexact computation but still satisfying the system requirement on accuracy. The rapid progress on the development of diverse AC techniques allows us to apply approximate computing to many computation-intensive applications. However, the utilization of AC techniques could bring in new unique security threats to computing systems. This work does a survey on existing circuit-, architecture-, and compiler-level approximate mechanisms/algorithms, with special emphasis on potential security vulnerabilities. Qualitative and quantitative analyses are performed to assess the impact of the new security threats on AC systems. Moreover, this work proposes four unique visionary attack models, which systematically cover the attacks that build covert channels, compensate approximation errors, terminate normal error resilience mechanisms, and propagate additional errors. To thwart those attacks, this work further offers the guideline of countermeasure designs. Several case studies are provided to illustrate the implementation of the suggested countermeasures.

scholarly journals Robust Computing for Machine Learning-Based Systems

2020 ◽  
pp. 479-503
Author(s):  
Muhammad Abdullah Hanif ◽  
Faiq Khalid ◽  
Rachmad Vidya Wicaksana Putra ◽  
Mohammad Taghi Teimoori ◽  
Florian Kriebel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Rapid Development ◽  
Autonomous Driving ◽  
High Accuracy ◽  
Security Threats ◽  
Security Vulnerabilities ◽  
Smart Healthcare ◽  
Super Computer ◽  
Temporal Redundancy ◽  
The Impact

AbstractThe drive for automation and constant monitoring has led to rapid development in the field of Machine Learning (ML). The high accuracy offered by the state-of-the-art ML algorithms like Deep Neural Networks (DNNs) has paved the way for these algorithms to being used even in the emerging safety-critical applications, e.g., autonomous driving and smart healthcare. However, these applications require assurance about the functionality of the underlying systems/algorithms. Therefore, the robustness of these ML algorithms to different reliability and security threats has to be thoroughly studied and mechanisms/methodologies have to be designed which result in increased inherent resilience of these ML algorithms. Since traditional reliability measures like spatial and temporal redundancy are costly, they may not be feasible for DNN-based ML systems which are already super computer and memory intensive. Hence, new robustness methods for ML systems are required. Towards this, in this chapter, we present our analyses illustrating the impact of different reliability and security vulnerabilities on the accuracy of DNNs. We also discuss techniques that can be employed to design ML algorithms such that they are inherently resilient to reliability and security threats. Towards the end, the chapter provides open research challenges and further research opportunities.

Perspectives on security threat politics

2016 ◽  
Author(s):  
Daniel Stevens ◽  
Nick Vaughan-Williams
Keyword(s):  
Political Psychology ◽  
Subject Matter ◽  
Security Studies ◽  
Security Threats ◽  
Security Threat ◽  
The Social ◽  
Personal Level ◽  
The Subject ◽  
The Impact

This Chapter highlights the importance of the subject matter of the book and situates the approach and contribution in the fields of International Relations and Political Psychology. It explores existing insights into the question of what ‘security threats’ are and how we can study everyday perceptions and experiences of them. In the IR and Security Studies literature the impact of the social constructivist turn, alongside the broadening and deepening of the security agenda, has meant that threats are now widely seen as produced through dialogue and interaction between states and non-state actors alike. What has tended to be overlooked, however, is the role of public opinion and everyday views, stories, and experiences in shaping securitizing moves and conditioning their ultimate success and/or failure. In turn, two main problems are identified with psychological and behavioural analyses of threat: first, that research tends to focus on discrete security threats, such as from terrorism, immigration, or the environment, limiting understanding of threats in general, and, second, the predominant focus on threats at the national or personal level at the expense of other levels at which threats may be experienced by citizens.

scholarly journals Heavy-Metal Contents and the Impact of Roasting on Polyphenols, Caffeine, and Acrylamide in Specialty Coffee Beans

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1310
Author(s):  
Matúš Várady ◽  
Sylwester Ślusarczyk ◽  
Jana Boržíkova ◽  
Katarína Hanková ◽  
Michaela Vieriková ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Dry Matter ◽  
Green Beans ◽  
Caffeoylquinic Acids ◽  
Coffee Beans ◽  
Metal Contents ◽  
Specialty Coffee ◽  
Quantitative Analyses ◽  
The Impact

The aim of this study was to determine the effect of roasting on the contents of polyphenols (PPH), acrylamide (AA), and caffeine (CAF) and to analyze heavy metals in specialty coffee beans from Colombia (COL) and Nicaragua (NIC). Samples of NIC were naturally processed and COL was fermented anaerobically. Green beans from COL (COL-GR) and NIC (NIC-GR) were roasted at two levels, light roasting (COL-LIGHT and NIC-LIGHT) and darker roasting (COL-DARK and NIC-DARK), at final temperatures of 210 °C (10 min) and 215 °C (12 min), respectively. Quantitative analyses of PPH identified caffeoylquinic acids (CQA), feruloylquinic acids, and dicaffeoylquinic acids. Isomer 5-CQA was present at the highest levels and reached 60.8 and 57.7% in COL-GR and NIC-GR, 23.4 and 29.3% in COL-LIGHT and NIC-LIGHT, and 18 and 24.2% in COL-DARK and NIC-DARK, respectively, of the total PPH. The total PPH contents were highest in COL-GR (59.76 mg/g dry matter, DM). Roasting affected the contents of PPH, CAF, and AA (p < 0.001, p < 0.011 and p < 0.001, respectively). Nickel and cadmium contents were significantly higher in the COL-GR than in the NIC-GR beans. Darker roasting decreased AA content, but light roasting maintained similar amounts of CAF and total PPH.

scholarly journals The potential for person-centred planning to support the community participation of adults with an intellectual disability

2021 ◽  
pp. 174462952110221
Author(s):  
Darren McCausland ◽  
Esther Murphy ◽  
Mary McCarron ◽  
Philip McCallion
Keyword(s):  
Intellectual Disability ◽  
Mixed Methods ◽  
Community Participation ◽  
Social Inclusion ◽  
Mixed Methods Approach ◽  
Complex Needs ◽  
Qualitative Case Studies ◽  
Quantitative Analyses ◽  
The Right ◽  
The Impact

Person-centred planning (PCP) puts individuals with an intellectual disability at the centre of service and support planning, identifying how individuals wish to live their lives and what is needed to make that possible. PCP has been identified as having the potential to facilitate improved social inclusion and community participation. A mixed-methods approach combined quantitative analyses with qualitative case studies of individuals with severe-profound intellectual disability to assess the impact of PCP on community participation for adults with an intellectual disability at a disability service in Dublin. We conclude that PCP may provide a good basis to plan community participation and, with the right supports in place, may provide opportunities for people with complex needs to improve their community participation. Supports including familiar staff and family are critical to the success of PCP for people with complex needs, and their absence may undermine the best intentions of PCP for this population.

DAM: A Theoretical Framework for SensorSecurity in IoT Applications

2021 ◽  
Vol 12 (3) ◽  
Author(s):  
Bisma Gulzar ◽  
Ankur Gupta
Keyword(s):  
Theoretical Framework ◽  
Sensor Nodes ◽  
Security Threats ◽  
Security Vulnerabilities ◽  
Iot Applications ◽  
Potential Impact ◽  
Multiple Domains ◽  
Sensor Security ◽  
Incorrect Data

As IoT applications are pervasively deployed across multiple domains, the potential impact of their security vulnerabilities are also accentuated. Sensor nodes represent a critical security vulnerability in the IoT ecosystem as they are exposed to the environment and accessible to hackers. When compromised or manipulated, sensor nodes can transmit incorrect data which can have a damaging impact on the overall operation and effectiveness of the system. Researchers have addressed the security vulnerabilities in sensor nodes with several mechanisms being proposed to address them. This paper presents DAM (Detect, Avoid, Mitigate), a theoretical framework to evaluate the security threats and solutions for sensor security in IoT applications and deployments. The framework leads to the classification of sensor security threats and categorization of available solutions which can be used to either detect vulnerabilities and attacks, recover from them or completely avoid them. The proposed framework will be useful for evaluating sensor security in real-world IoT deployments in terms of potential threats and designing possible solution

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