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VulnaChat: Vulnerability Chatbot

VulnaChat: Vulnerability Chatbot

Abstract

This capstone project develops an AI-powered chatbot to address cybersecurity vulnerabilities, leveraging the Common Vulnerabilities and Exposures (CVE) system and the Common Vulnerability Scoring System (CVSS). The chatbot will provide accessible and informative support for understanding and mitigating these vulnerabilities, potentially leading to significant improvements in cybersecurity practices.

Objective

ในยุคที่การรักษาความปลอดภัยทางไซเบอร์มีการพัฒนาอย่างรวดเร็ว องค์กรต่างๆต้องเผชิญกับความท้าทายมากมายในการระบุและลดความเสี่ยงจากช่องโหว่ต่างๆ ภัยคุกคามทางไซเบอร์ที่มีความซับซ้อนเพิ่มขึ้นทำให้จำเป็นต้องมีเครื่องมือที่มีประสิทธิภาพและประสิทธิผลเพื่อช่วยให้นักทดสอบเจาะระบบสามารถประเมินช่องโหว่และผลกระทบที่อาจเกิดขึ้นได้ วิธีการปัจจุบันมักเกี่ยวข้องกับการค้นหาด้วยตนเองผ่านฐานข้อมูลขนาดใหญ่ ซึ่งอาจใช้เวลานานและมีโอกาสเกิดข้อผิดพลาดจากมนุษย์ แชทบอทที่ใช้ปัญญาประดิษฐ์สามารถทำให้กระบวนการนี้มีประสิทธิภาพมากขึ้น โดยให้ข้อมูลที่รวดเร็วและแม่นยำเกี่ยวกับช่องโหว่เฉพาะ รวมถึงคำอธิบาย คะแนน CVSS และระดับความรุนแรง

Other Innovations

Effect of freshness preservation methods of Threadfin breams (Nemipterus furcosus) from small scale fisheries on quality for sashimi.

คณะเทคโนโลยีการเกษตร

Effect of freshness preservation methods of Threadfin breams (Nemipterus furcosus) from small scale fisheries on quality for sashimi.

Threadfin breams is an economically important fish that can be found in fisheries in both the Gulf of Thailand and Andaman Sea and is cheap. In addition, the consumption of raw fish as sashimi is increasingly popular in Thailand. Therefore, it is necessary to promote its consumption to increase its value. This study investigated the preservation of threadfin breams (N. furcosus) for raw or sashimi consumption. The preservation of threadfin breams consisted of Ikejime (K) and cold seawater (S) methods, and the preservation of the fish by Gutting (G) and whole (W) and storing for 3 days on ice (I) or in a refrigerator (F). The freshness quality of threadfin breams was evaluated by sensory, physicochemical (TVB-N, TMA-N and pH), freshness index (Ki-value) and microbiological methods. It was found that after being stored for 3 days, the KGF group of threadfin breams had the highest overall sensory score, which was 8.36±0.80 points, and the KWI, SWI and SWF groups of threadfin breams had the lowest overall sensory scores, which were 8.13±0.77, 8.13±0.77 and 8.13±0.81 points, respectively. And the overall sensory scores of all experimental groups of fish increased significantly (p<0.05). The TVB-N value of threadfin breams in KGF group had the lowest TVB-N value, which was 1.37±0.93 mg nitrogen/100 g sample. The threadfin breams in SGI group had the highest TVB-N value, which was 2.36±1.15 mg nitrogen/100 g sample. The TVB-N of fish in all experimental groups increased significantly (p<0.05). The TMA-N value of threadfin breams in KGF group had the lowest TMA-N value, which was 1.56±0.88 mg nitrogen/100 g sample. The threadfin breams in SWF group had the highest TMA-N value, which was 2.17±1.22 mg nitrogen/100 g sample. The TMA-N of fish in all experimental groups increased significantly (p<0.05). The pH value of threadfin breams in KGF group had the lowest pH value, which was 6.40±0.12. The threadfin breams in SWF group had the highest pH value, which was 6.78±0.25. The pH of fish in all experimental groups increased significantly (p<0.05). Ki value The threadfin breams in KGF group had the lowest Ki value, which was 9.05±0.73%. The threadfin breams in KWI group had the highest Ki value, which was 12.88±4.19%. The Ki value of all experimental groups of fish increased without statistical significance (p>0.05). In terms of freshness quality in microbiology, it was found that in all experimental groups, Salmonella spp., S. aureus, B. cereus, C. perfringens and E. coli were found in all experimental groups of threadfin breams. All types of microorganisms in all groups of threadfin breams increased with statistical significance (p<0.05). When compared with the freshness quality criteria in terms of sensory, chemical, physical, freshness index and microbiology, it was found that all groups of threadfin breams were very fresh and suitable for raw consumption during the preservation and storage for 3 days. After 3 days of storage, the threadfin breams should be consumed cooked because the freshness quality of the fish is not suitable for raw consumption due to the increase in various parameters. The increase in various parameters is due to the deterioration of the fish and the activities of microorganisms. Therefore, threadfin breams is suitable to promote raw consumption within 3 days of storage. In addition, fish preservation, especially by Ikejime method, then cutting open the belly and storing in the refrigerator, can help improve the freshness of the fish. The results of this study can be used to develop techniques for preserving fish after capture for fishermen and can promote the increase in the value of threadfin breams in the future.

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DEVELOPMENT OF CURCUMIN DOUBLE-WALLED BEADS COLORIMETRIC SENSOR FOR DETERMINATION OF PYRIDOXINE (VITAMIN B6) IN DIETARY SUPPLEMENT WITH DETECTION BY IMAGE PROCESSING

คณะวิทยาศาสตร์

DEVELOPMENT OF CURCUMIN DOUBLE-WALLED BEADS COLORIMETRIC SENSOR FOR DETERMINATION OF PYRIDOXINE (VITAMIN B6) IN DIETARY SUPPLEMENT WITH DETECTION BY IMAGE PROCESSING

A smartphone-based colorimetric sensor for quantitative detection of pyridoxine (Vitamin B6, VB-6) in functional drink samples has been realized by developing double layer hydrogel. Electrostatic interaction initiates the cross-linking and produces double layer hydrogel.

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SOH  Estimation for  Li-ion battery

คณะวิศวกรรมศาสตร์

SOH Estimation for Li-ion battery

Currently, lithium batteries are widely used in electronic devices and electric vehicles, making the estimation of their State of Health (SOH) crucial. Accurate SOH estimation helps extend battery lifespan, reduce maintenance costs, and prevent safety issues such as overheating or explosions. This project aims to study and analyze mathematical models of batteries and develop SOH estimation techniques using Neural Networks to enhance accuracy and evaluation speed. The experiment involved collecting charge and discharge data from three lithium battery cells under controlled temperature conditions while maintaining a constant current. The current, voltage, and time data were recorded and analyzed to determine the battery capacity for each cycle. These data were then used to train a Neural Network model. The results demonstrated an effective method for predicting battery health status. The outcomes of this project can contribute to the development of a Battery Management System (BMS) that improves battery efficiency and longevity. Additionally, it provides a foundation for applying artificial intelligence techniques in the energy sector effectively.

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