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In recent years, the Internet of Things (IoT) becomes popular technology. The one aspect that makes important concern in IoT is the confidentiality of communications. For securing communication in IoT, cryptography algorithm such as symmetrical cryptography requires the secret key exchange process in a public wireless network to ensure the sameness of the secret key. However, the exchange of secret keys in the public wireless network can be exploited by adversaries. So, we present the secret key generation scheme that generates a shared random key through observation of the communication channel parameter i.e. Receive Signal Strength (RSS) between two devices that no need to exchange the secret key. We use Middle-Point quantization to convert the RSS into bit sequences and use Clover Filter to eliminate the error bits after the quantization process. Measurement results showed that the proposed scheme improves the performance of existing schemes if the interval used is 25. The proposed scheme improves the KGR 24 times and improves efficiency to 63%. While for KDR, the proposed scheme can decrease the KDR value of 67.9%. Also, in all scenarios, the proposed scheme can pass the NIST randomness test.

In symmetric cryptography systems have problems in the distribution of secret keys. The two users who will communicate require sharing keys through the public channel. The proposed solution to overcome these problems is to utilize information from the physical layer (e.g. RSS). Received Signal Strength (RSS) is an indicator for measuring the power received by wireless devices. The advantage of secret key extraction using physical layer information from a wireless channel is that it allows both devices within the transmission range to extract the secret key together. In this paper, we propose a secret key generation scheme adopted from an existing scheme with modifications to improve performance. Our proposed system is applied to static and dynamic conditions to test performance. The proposed algorithm is able to obtain a reduction in KDR (Key Disagreement Rate) up to 48.42% and an increase in the KGR (Key Generation Rate) up to 23.35% when compared to the existing scheme. Our proposed system also successfully passed the randomness using the NIST test with the approximate value of entropy generated 0.80 in static conditions and 0.81 in dynamic conditions.

Transportation has become one of the needs of human life. One of the most used transportation in Indonesia is a motorcycle. This transportation is reliable, has a wide variety of uses, is capable of handling traffic jams, and is very economical. But motorbikes have a relatively high risk for the safety of the rider compared to cars. With driver behavior and road congestion conditions, accidents often occur. In this research, we observed the movement of the driver through a smartphone and built an application that was able to provide a warning to motorists. In this system we use 2 types of sensors, Accelerometer and Gyroscope sensors which are generally the basic features of a smartphone. We adopt a Machine Learning-based movement identification process with an Artificial Neural Network (ANN) algorithm. ANN will do what movements it does based on the data obtained from the Accelerometer and Gyroscope sensor values. The application is installed on a smartphone and put it on a vehicle with a fixed position. The device will calculate the activity based on several predetermined categories of the driver status. The status categories are normal, zig-zag, sleepy, turn right, turn left, U-turn, sudden braking, sudden acceleration, and speed bumps. The level of accuracy generated by Machine Learning using the Artificial Neural Network Algorithm in this research was 96,2%.

Drone service is an Unmanned Aerial Vehicle (UAV) whose function is to deliver goods using air routes. Drone services sometimes have to travel long distances with a guaranteed security system to get to the customer's location and return safely to the base. But in fact, in the use of an insecure Internet of Drone (IoD) environment, there will be many attacks that try to manipulate the approximate location or interrupt transmission of data from fake nodes. Therefore, this paper focuses on a reliable data communication security system between drone services and server. Because the drone service uses a lightweight device, we propose a Hybrid cryptographic security scheme that has simple computing but a high level of security. It has layered encryption using AES- 256, ECC, and SHA256 which are provides high data authentication and encryption services for each node. The proposed scheme is efficient in terms of processing time so that it will not significantly affect the realtime sensor data from the drone. The experimental results show that the proposed system reaches 88.61 milliseconds to encrypt and decrypt messages using the Raspberry Fi device.

Virtualization and Software-defined Networking (SDN) are emerging technologies that play a major role in cloud computing. Cloud computing provides efficient utilization, high performance, and resource availability on demand. However, virtualization environments are vulnerable to various types of intrusion attacks that involve installing malicious software and denial of services (DoS) attacks. Utilizing SDN technology, makes the idea of SDN-based security applications attractive in the fight against DoS attacks. Network intrusion detection system (IDS) which is used to perform network traffic analysis as a detection system implemented on SDN networks to protect virtualization servers from HTTP DoS attacks. The experimental results show that SDN-based IDS is able to detect and mitigate HTTP DoS attacks effectively.

Due to features of mobility and velocity of movement all nodes in Vehicular Ad-hoc Networks (VANETs), these infrastructureless wireless ad-hoc networks become challenging. This is much more interesting when involving not only security but also privacy protection of vehicles. Secure communications among vehicles or between vehicles and Road-Side Units (RSUs) should be mandatory satisfied through encryption, anonymous authentication, and the integrity guarantee of exchanging information. Hence, both security and privacy protection of vehicles should be considered. Therefore, this paper proposes an anonymous authentication system to enable a vehicle proves that he/she is a legitimated vehicle in the VANET without revealing his/her privacy information to other vehicles or RSUs. To realize this aim, an efficient group signature scheme is adopted. The measurement results showed the practicality of proposed system to achieve only about 185 ms or 121 ms in conducting an anonymous authentication either in Vehicle-to-Vehicle (V2V) communication or Vehicle-to-RSU (V2R) communication.

This research focuses on tracking user-behavior based on applications usage of the user’s smartphone and creates a conclusion of user behavior when he/she has a trip of traveling. To track the application usage from the user’s smartphone, a library from Android SDK is utilized in creating an instruction that can track the application usage from the user’s smartphone. While he/she is on a trip, his/her positions can be tracked by using Google Maps API as well integrated on the application. To realize these functionalities, a heuristic method is adopted. In this application, user behavior data that have been made are stored in the database. The data sent are secured using the RSA algorithm and equipped with message digest verification. The results show that our proposed application is worked properly within the testing scope for behavioral generation during traveling.