Aug 2026· International journal of intelligent engineering and systems· Vol 19, pp. 1025-1039
Abstract
The rapid scalability of IoT has brought computing power to the edge of the network where low powered devices have a great deal of difficulty protecting themselves from cyber-attack due to their limited resources (memory, processing, power).Current authentication protocols (i.e., TLS/DTLS, IPSec) are certainly statistically secure but computationally too expensive for low powered devices and as such expose them to a variety of cyber-attacks (replay, impersonation, man-in-the-middle, etc.).This paper introduces a new mutual authentication protocol called LEAP (Lightweight Edge Authentication Protocol) specifically developed for low powered edge devices in the IoT space.LEAP utilizes two message exchanges between devices using only lightweight cryptographic primitives (i.e., SHA-256 hash and simple XOR operations) to arrive at a mutual authentication and fresh session key.The protocol was developed using Python on Raspberry Pi Gateways and ESP32 Microcontrollers, with an extensive experimental performance evaluation as well as validating network resilience using the CIC IoT Dataset 2023.LEAP has a mean authentication time of 12.4 ms, an energy consumption of 28.4 mJ, and a memory footprint of only 11.2 KB flash and 4.8 KB RAM; therefore, LEAP provides a 28-fold speed improvement over the optimized ECC protocol of Sciancalepore et al. (2016) and a 33-fold improvement over the ECC protocol of Wang et al. (2018), with corresponding energy reductions of 26-fold and 31-fold respectively.Additionally, ProVerif checked that LEAP is secure against replay attacks, man-in-the-middle attacks and impersonation attacks under the Dolev-Yao adversary model.By providing verified resistance to replay, man-in-the-middle, and impersonation attacks under the Dolev-Yao adversary model, together with excellent efficiency, this makes LEAP a practical and viable method of authenticating resource constrained devices at the edge of the IoT, which is a critical gap in today's security landscape.
Agile - denoting "the quality of being agile, readiness for motion, nimbleness, activity, dexterity in motion" - software development methods are attempting to offer an answer to the eager business community asking for lighter weight along with faster and nimbler software development processes. This is especially the case with the rapidly growing and volatile Internet software industry as well as for the emerging mobile application environment. The new agile methods have evoked substantial amount of literature and debates. However, academic research on the subject is still scarce, as most of existing publications are written by practitioners or consultants. The aim of this publication is to begin filling this gap by systematically reviewing the existing literature on agile software development methodologies. This publication has three purposes. First, it proposes a definition and a classification of agile software development approaches. Second, it analyses ten software development methods that can be characterized as being "agile" against the defined criterion. Third, it compares these methods and highlights their similarities and differences. Based on this analysis, future research needs are identified and discussed.
P. Abrahamsson, O. Salo, Jussi Ronkainen et al.· arXiv.org· 728 citations· ⚡54
Context: Software startups are newly created companies with no operating history and fast in producing cutting-edge technologies. These companies develop software under highly uncertain conditions, tackling fast-growing markets under severe lack of resources. Therefore, software startups present a unique combination of characteristics which pose several challenges to software development activities. Objective: This study aims to structure and analyze the literature on software development in startup companies, determining thereby the potential for technology transfer and identifying software development work practices reported by practitioners and researchers. Method: We conducted a systematic mapping study, developing a classification schema, ranking the selected primary studies according their rigor and relevance, and analyzing reported software development work practices in startups. Results: A total of 43 primary studies were identified and mapped, synthesizing the available evidence on software development in startups. Only 16 studies are entirely dedicated to software development in startups, of which 10 result in a weak contribution (advice and implications (6); lesson learned (3); tool (1)). Nineteen studies focus on managerial and organizational factors. Moreover, only 9 studies exhibit high scientific rigor and relevance. From the reviewed primary studies, 213 software engineering work practices were extracted, categorized and analyzed. Conclusion: This mapping study provides the first systematic exploration of the state-of-art on software startup research. The existing body of knowledge is limited to a few high quality studies. Furthermore, the results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al.· Information and Software Tec...· 394 citations· ⚡54
What if pathology foundation models could do more with less? GigaPath-Flash and GigaTIME-Flash cut computational demands while maintaining strong performance, opening the door to larger studies and broader exploration. The post GigaPath-Flash and GigaTIME-Flash: Toward population-scale discovery with efficient pathology foundation models appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduAug 31, 2026
With millions of users across the world, Julia has been used to conduct cutting-edge research and to design new drugs, jet engines, heat pumps, and more.
MIT News · Artificial Intelligence· news.mit.eduAug 27, 2026
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.