Using regression learners to predict performance problems on software updates

Author(s):  
Aitor Gartziandia ◽  
Aitor Arrieta ◽  
Aitor Agirre ◽  
Goiuria Sagardui ◽  
Maite Arratibel
2020 ◽  
Vol 19 (2) ◽  
pp. 63-74
Author(s):  
Klaus Moser ◽  
Hans-Georg Wolff ◽  
Roman Soucek

Abstract. Escalation of commitment occurs when a course of action is continued despite repeated drawbacks (e.g., maintaining an employment relationship despite severe performance problems). We analyze process accountability (PA) as a de-escalation technique that helps to discontinue a failing course of action and show how time moderates both the behavioral and cognitive processes involved: (1) Because sound decisions should be based on (hopefully unbiased) information search, which requires time to gather, the effect of PA on de-escalation increases over time. (2) Because continuing information search creates behavioral commitment, the debiasing effect of PA on information search diminishes over time. (3) Consistent with the tunnel vision notion, the effects of less biased information search on de-escalation decrease over time.


Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4393
Author(s):  
JongHyup Lee ◽  
Taekyoung Kwon

The Industrial Internet of Things (IIoT) could enhance automation and analytics in industrial environments. Despite the promising benefits of IIoT, securely managing software updates is a challenging problem for those critical applications. This is due to at least the intrinsic lack of software protection mechanisms in legacy industrial systems. In this paper, to address the challenges in building a secure software supply chain for industrial environments, we propose a new approach that leverages distributed watchdogs with blockchain systems in protecting software supply chains. For this purpose, we bind every entity with a unique identity in the blockchain and employ the blockchain as a delegated authenticator by mapping every reporting action to a non-fungible token transfer. Moreover, we present a detailed specification to clearly define the behavior of systems and to apply model checking.


Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1220
Author(s):  
Chee Wei Lee ◽  
Stuart Madnick

Urban mobility is in the midst of a revolution, driven by the convergence of technologies such as artificial intelligence, on-demand ride services, and Internet-connected and self-driving vehicles. Technological advancements often lead to new hazards. Coupled with the increased levels of automation and connectivity in the new generation of autonomous vehicles, cybersecurity is emerging as a key threat affecting these vehicles. Traditional hazard analysis methods treat safety and security in isolation and are limited in their ability to account for interactions among organizational, sociotechnical, human, and technical components. In response to these challenges, the cybersafety method, based on System Theoretic Process Analysis (STPA and STPA-Sec), was developed to meet the growing need to holistically analyze complex sociotechnical systems. We applied cybersafety to coanalyze safety and security hazards, as well as identify mitigation requirements. The results were compared with another promising method known as Combined Harm Analysis of Safety and Security for Information Systems (CHASSIS). Both methods were applied to the Mobility-as-a-Service (MaaS) and Internet of Vehicles (IoV) use cases, focusing on over-the-air software updates feature. Overall, cybersafety identified additional hazards and more effective requirements compared to CHASSIS. In particular, cybersafety demonstrated the ability to identify hazards due to unsafe/unsecure interactions among sociotechnical components. This research also suggested using CHASSIS methods for information lifecycle analysis to complement and generate additional considerations for cybersafety. Finally, results from both methods were backtested against a past cyber hack on a vehicular system, and we found that recommendations from cybersafety were likely to mitigate the risks of the incident.


2021 ◽  
Vol 145 ◽  
pp. 111067
Author(s):  
John Balfour ◽  
Roger Hill ◽  
Andy Walker ◽  
Gerald Robinson ◽  
Thushara Gunda ◽  
...  

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 739
Author(s):  
Nicholas Ayres ◽  
Lipika Deka ◽  
Daniel Paluszczyszyn

The vehicle-embedded system also known as the electronic control unit (ECU) has transformed the humble motorcar, making it more efficient, environmentally friendly, and safer, but has led to a system which is highly dependent on software. As new technologies and features are included with each new vehicle model, the increased reliance on software will no doubt continue. It is an undeniable fact that all software contains bugs, errors, and potential vulnerabilities, which when discovered must be addressed in a timely manner, primarily through patching and updates, to preserve vehicle and occupant safety and integrity. However, current automotive software updating practices are ad hoc at best and often follow the same inefficient fix mechanisms associated with a physical component failure of return or recall. Increasing vehicle connectivity heralds the potential for over the air (OtA) software updates, but rigid ECU hardware design does not often facilitate or enable OtA updating. To address the associated issues regarding automotive ECU-based software updates, a new approach in how automotive software is deployed to the ECU is required. This paper presents how lightweight virtualisation technologies known as containers can promote efficient automotive ECU software updates. ECU functional software can be deployed to a container built from an associated image. Container images promote efficiency in download size and times through layer sharing, similar to ECU difference or delta flashing. Through containers, connectivity and OtA future software updates can be completed without inconveniences to the consumer or incurring expense to the manufacturer.


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