Sonia Sabir

Sumin Han, Youngjun Park, Sonia Sabir et al.

Despite advancements in real estate appraisal methods, this study primarily focuses on two pivotal challenges. Firstly, we explore the often-underestimated impact of Points of Interest (POI) on property values, emphasizing the necessity for a comprehensive, data-driven approach to feature selection. Secondly, we integrate road-network-based Areal Embedding to enhance spatial understanding for real estate appraisal. We first propose a revised method for POI feature extraction, and discuss the impact of each POI for house price appraisal. Then we present the Areal embedding-enabled Masked Multihead Attention-based Spatial Interpolation for House Price Prediction (AMMASI) model, an improvement upon the existing ASI model, which leverages masked multi-head attention on geographic neighbor houses and similar-featured houses. Our model outperforms current baselines and also offers promising avenues for future optimization in real estate appraisal methodologies.

Inayat Ali, Sonia Sabir, Zahid Ullah

The Internet of Things (IoT) is one of the emerging technologies that has grabbed the attention of researchers from academia and industry. The idea behind Internet of things is the interconnection of internet enabled things or devices to each other and to humans, to achieve some common goals. In near future IoT is expected to be seamlessly integrated into our environment and human will be wholly solely dependent on this technology for comfort and easy life style. Any security compromise of the system will directly affect human life. Therefore security and privacy of this technology is foremost important issue to resolve. In this paper we present a thorough study of security problems in IoT and classify possible cyberattacks on each layer of IoT architecture. We also discuss challenges to traditional security solutions such as cryptographic solutions, authentication mechanisms and key management in IoT. Device authentication and access controls is an essential area of IoT security, which is not surveyed so far. We spent our efforts to bring the state of the art device authentication and access control techniques on a single paper.

Inayat Ali, Sonia Sabir, Eraj Khan

Privacy problems are lethal and getting more attention than any other issue with the notion of the Internet of Things (IoT). Since IoT has many application areas including smart home, smart grids, smart healthcare system, smart and intelligent transportation and many more. Most of these applications are fueled by the resource-constrained sensor network, such as Smart healthcare system is powered by Wireless Body Area Network (WBAN) and Smart home and weather monitoring systems are fueled by Wireless Sensor Networks (WSN). In the mentioned application areas sensor node life is a very important aspect of these technologies as it explicitly effects the network life and performance. Data aggregation techniques are used to increase sensor node life by decreasing communication overhead. However, when the data is aggregated at intermediate nodes to reduce communication overhead, data privacy problems becomes more vulnerable. Different Privacy-Preserving Data Aggregation (PPDA) techniques have been proposed to ensure data privacy during data aggregation in resource-constrained sensor nodes. We provide a review and comparative analysis of the state of the art PPDA techniques in this paper. The comparative analysis is based on Computation Cost, Communication overhead, Privacy Level, resistance against malicious aggregator, sensor node life and energy consumption by the sensor node. We have studied the most recent techniques and provide in-depth analysis of the minute steps involved in these techniques. To the best of our knowledge, this survey is the most recent and comprehensive study of PPDA techniques.