Ioannis Papapanagiotou

Enhancing the accuracy of iBeacons for indoor proximity-based services

Proximity-based Services (PBS) require high detection accuracy, energy efficiency, wide reception range, low cost and availability. However, most existing technologies cannot satisfy all these requirements. Apples Bluetooth Low Energy (BLE), named iBeacon, has emerged as a leading candidate in this domain and has become an almost industry standard for PBS. However, it has several limitations. It suffers from poor proximity detection accuracy due to its reliance on Received Signal Strength Indicator (RSSI). To improve proximity detection accuracy of iBeacons, we present two algorithms that address the inherent flaws in iBeacons current proximity detection approach. Our first algorithm, Server-side Running Average (SRA), uses the path-loss model-based estimated distance for proximity classification. Our second algorithm, Server-side Kalman Filter (SKF), uses a Kalman filter in conjunction with SRA. Our experimental results show that SRA and SKF perform better than the current moving average approach utilized by iBeacons. SRA results in about a 29% improvement while SKF results in about a 32% improvement over the current approach in proximity detection accuracy.

Internet of things: Survey on security

ABSTRACT The Internet of things (IoT) is intended for ubiquitous connectivity among different entities or “things”. While it provides effective and efficient solutions to many real world challenges, the security aspect of it has always been questioned. The situation is further exacerbated by the number of connected devices growing exponentially. As a result, security and privacy has emerged as a significant challenge for the IoT. In this paper, we aim to provide a thorough survey on IoT security and privacy challenges from the perspective of technologies and architecture used. This work focuses on IoT intrinsic vulnerabilities and their implications to the fundamental information security challenges in confidentiality, integrity, and availability. The approach of this survey is to summarize and synthesize published work in IoT; relate it to the security conjuncture of the field; and project future research directions.

Real-Time Digital Signatures for Time-Critical Networks

The secure and efficient operation of time-critical networks, such as vehicular networks, smart-grid, and other smart-infrastructures, is of primary importance in today’s society. It is crucial to minimize the impact of security mechanisms over such networks so that the safe and reliable operations of time-critical systems are not being interfered. For instance, if the delay introduced by the crypto operations negatively affects the time available for braking a car before a collision, the car may not be able to safely stop in time. In particular, as a primary authentication mechanism, existing digital signatures introduce a significant computation and communication overhead, and therefore are unable to fully meet the real-time processing requirements of such time-critical networks. In this paper, we introduce a new suite of real-time digital signatures referred to as <italic>Structure-free and Compact Real-time Authentication</italic> (<inline-formula> <tex-math notation=LaTeX>

A self-organized resource provisioning for cloud block storage

{SCRA}

A trace-driven evaluation of cloud computing schedulers for IaaS

</tex-math></inline-formula>), supported by hardware acceleration, to provide delay-aware authentication in time-critical networks. <inline-formula> <tex-math notation=LaTeX>

Occupant tracking in smart facilities: An experimental study

{SCRA}

TECHNIQUES FOR PERFORMING DATA RECONCILIATION IN DISTRIBUTED DATA STORE SYSTEMS

</tex-math></inline-formula> is a novel signature framework that can transform any secure aggregate signature into a signer efficient signature. We instantiate <inline-formula> <tex-math notation=LaTeX>

Microlocation for Smart Buildings in the Era of the Internet of Things: A Survey of Technologies, Techniques, and Approaches

{SCRA}

Unsupervised Crowd-Assisted Learning Enabling Location-Aware Facilities

</tex-math></inline-formula> framework with condensed-RSA, BGLS, and NTRU signatures. Our analytical and experimental evaluation validates the significant performance advantages of <inline-formula> <tex-math notation=LaTeX>

Cloud communications and networking

{SCRA}