Computing on Vertices in Data Mining

The main challenges in data mining are related to large, multi-dimensional data sets. There is a need to develop algorithms that are precise and efficient enough to deal with big data problems. The Simplex algorithm from linear programming can be seen as an example of a successful big data problem solving tool. According to the fundamental theorem of linear programming the solution of the optimization problem can found in one of the vertices in the parameter space. The basis exchange algorithms also search for the optimal solution among finite number of the vertices in the parameter space. Basis exchange algorithms enable the design of complex layers of classifiers or predictive models based on a small number of multivariate data vectors.

On the Performance Analysis for CSIDH-Based Cryptosystems

In this paper, we present the performance and security analysis for various commutative SIDH (CSIDH)-based algorithms. As CSIDH offers a smaller key size than SIDH and provides a relatively efficient signature scheme, numerous CSIDH-based key exchange algorithms have been proposed to optimize the CSIDH. In CSIDH, the private key is an ideal class in a class group, which can be represented by an integer vector. As the number of ideal classes represented by these vectors determines the security level of CSIDH, it is important to analyze whether the different vectors induce the same public key. In this regard, we generalize the existence of a collision for a base prime p≡7mod8. Based on our result, we present a new interval for the private key to have a similar security level for the various CSIDH-based algorithms for a fair comparison of the performance. Deduced from the implementation result, we conclude that for a prime p≡7mod8, CSIDH on the surface using the Montgomery curves is the most likely to be efficient. For a prime p≡3mod8, CSIDH on the floor using the hybrid method with Onuki’s collision-free method is the most likely to be efficient and secure.

Security Architecture for Low Resource Devices in Smart City using Cloud

The world is moving towards modernization with the help of smart devices used in smart cities to make the whole lot intelligent and smart. These smart devices are extensively used in smart city and are capable of doing everything which one can do with the normal desktop computer. These smart devices like Smartphone have computational limitations are not able to store a large data to be used and collected in a smart city. In this paper, we propose a novel security architecture which first uses the Elliptic Curve Diffie Helman Key Exchange Algorithms to exchange the keys between the two low power devices (Smartphone). The keys are used to encrypt the large data (images and videos etc). The data is encrypted using the private keys of a device and then send to the cloud for safe storage. The data can be only accessed by the communicating device with the same key. The proposed security architecture enables these smart devices to store the huge data collected from the smart city to store on the cloud. If another device requests the same set of data, the keys can be shared secretly and the communicating device can be allowed to download the data directly from the cloud. This architecture relieves the Smartphone from the storage limitation and also enables it to communicate with faster speed and securely.

A Modified Otway-Rees Protocol to Overcome Triple MAB Vulnerability

With growth of internet and wireless networks all around the world, information security has taken a central stage to protect commercial and well as personal data. Key exchange algorithms play an important role in information security. In this paper we study the Otway-Rees protocol and its vulnerabilities and propose a modified Otway-Rees protocol to overcome them. We then evaluate performance of the protocol from various points of view such as execution time, encryption speed and power consumption by comparing the original and proposed protocols. We find that although the original protocol is faster, the difference in speed is not significant and the modified protocol protects against vulnerability resulting in the best choice between the two protocols.

Side-by-Side Analysis of Key Exchange Algorithms for Load Optimized Security in MQTT Protocol

The Information Technology has evolved and we have reached at an era of Internet of Things (IoT). According to International Telecommunication Union’s Global Standards Initiative (GSI), it is the network of all kinds of ‘things’ embedded with electronics, sensors, actuators, software etc. Things connected in open Internet poses high security risks. Majority of these devices use Message Queuing Telemetry Transport (MQTT) protocol for exchanging information. Most of the devices with limited storage and computing power are connected using MQTT. Since the protocol doesn't provide any mechanism for encryption, the security aspect of the protocol is really weak. This paper describes the need for empowering security in MQTT. In this research work, we benchmark different cryptographic algorithms and propose the best possible algorithm to enable higher level of security in MQTT. This work further demonstrates how to use the proposed algorithm to enable lightweight key exchange mechanism among MQTT devices.