Biblio

Users can directly access and share information from portable devices such as a smartphone or an Internet of Things (IoT) device. However, to prevent them from becoming victims to launch cyber attacks, they must allow selective sharing based on roles of the users such as with the Ciphertext-Policy Attribute Encryption (CP-ABE) scheme. However, to match the resource constraints, the scheme must be efficient for storage. It must also protect the device from malicious users as well as allow uninterrupted access to valid users. This paper presents the CCA secure PROxy-based Scalable Revocation for Constant Cipher-text (C-PROSRCC) scheme, which provides scalable revocation for a constant ciphertext length CP-ABE scheme. The scheme has a constant number of pairings and computations. It can also revoke any number of users and does not require re-encryption or redistribution of keys. We have successfully implemented the C-PROSRCC scheme. The qualitative and quantitative comparison with related schemes indicates that C-PROSRCC performs better with acceptable overheads. C-PROSRCC is Chosen Ciphertext Attack (CCA) secure. We also present a case study to demonstrate the use of C-PROSRCC for mobile-based selective sharing of a family car.

This Wireless Sensor Network is a network of devices that communicates the information gathered from a monitored field through wireless links. Small size sensor nodes constitute wireless sensor networks. A Sensor is a device that responds and detects some type of input from both the physical or environmental conditions, such as pressure, heat, light, etc. Applications of wireless sensor networks include home automation, street lighting, military, healthcare and industrial process monitoring. As wireless sensor networks are distributed across large geographical area, these are vulnerable to various security threats. This affects the performance of the wireless sensor networks. The impact of security issues will become more critical if the network is used for mission-critical applications like tactical battlefield. In real life deployment scenarios, the probability of failure of nodes is more. As a result of resource constraints in the sensor nodes, traditional methods which involve large overhead computation and communication are not feasible in WSNs. Hence, design and deployment of secured WSNs is a challenging task. Attacks on WSNs include attack on confidentiality, integrity and availability. There are various types of architectures that are used to deploy WSNs. Some of them are data centric, hierarchical, location based, mobility based etc. This work discusses the security issue of hierarchical architecture and proposes a solution. In hierarchical architectures, sensor nodes are grouped to form clusters. Intra-cluster communication happens through cluster heads. Cluster heads also facilitate inter-cluster communication with other cluster heads. Aggregation of data generated by sensor nodes is done by cluster heads. Aggregated data also get transferred to base through multi-hop approach in most cases. Cluster heads are vulnerable to various malicious attacks and this greatly affects the performance of the wireless sensor network. The proposed solution identifies attacked cluster head and changes the CH by identifying the fittest node using genetic algorithm based search.

Energy efficiency and security is a critical requirement for computing at edge nodes. Unrolled architectures for lightweight cryptographic algorithms have been shown to be energy-efficient, providing higher performance while meeting resource constraints. Hardware implementations of unrolled datapaths have also been shown to be resistant to side channel analysis (SCA) attacks due to a reduction in signal-to-noise ratio (SNR) and an increased complexity in the leakage model. This paper demonstrates optimal leakage models and an improved CFA attack which makes it feasible to extract first-order side-channel leakages from combinational logic in the initial rounds of unrolled datapaths. Several leakage models, targeting initial rounds, are explored and 1-bit hamming weight (HW) based leakage model is shown to be an optimal choice. Additionally, multi-band narrow bandpass filtering techniques in conjunction with correlation frequency analysis (CFA) is demonstrated to improve SNR by up to 4×, attributed to the removal of the misalignment effect in combinational logics and signal isolation. The improved CFA attack is performed on side channel signatures acquired for 7-round unrolled SIMON datapaths, implemented on Sakura-G (XILINX spartan 6, 45nm) based FPGA platform and a 24× reduction in minimum-traces-to-disclose (MTD) for revealing 80% of the key bits is demonstrated with respect to conventional time domain correlation power analysis (CPA). Finally, the proposed method is successfully applied to a fully-unrolled datapath for PRINCE and a parallel round-based datapath for Advanced Encryption Standard (AES) algorithm to demonstrate its general applicability.