Elliptic Curve Cryptography for Wireless Sensor Networks Using the Number Theoretic Transform

We implement elliptic curve cryptography on the MSP430 which is a commonly used microcontroller in wireless sensor network nodes. We use the number theoretic transform to perform finite field multiplication and squaring as required in elliptic curve scalar point multiplication. We take advantage of the fast Fourier transform for the first time in the literature to speed up the number theoretic transform for an efficient realization of elliptic curve cryptography. Our implementation achieves elliptic curve scalar point multiplication in only 0.65 s and 1.31 s for multiplication of fixed and random points, respectively, and has similar or better timing performance compared to previous works in the literature

Implementing RSA for Wireless Sensor Nodes

As wireless sensor networks (WSNs) become more widespread, potential attacks against them also increase and applying cryptography becomes inevitable to make secure WSN nodes. WSN nodes typically contain only a constrained microcontroller, such as MSP430, Atmega, etc., and running public key cryptography on these constrained devices is considered a challenge. Since WSN nodes are spread around in the field, the distribution of the shared private key, which is used in a symmetric key cryptographic algorithm for securing communications, is a problem. Thus, it is necessary to use public key cryptography to effectively solve the key distribution problem. The RSA cryptosystem, which requires at least a 1024-bit key, is the most widely used public key cryptographic algorithm. However, its large key size is considered a drawback for resource constrained microcontrollers. On the other hand, RSA allows for extremely fast digital signature generation which may make it desirable in applications where messages transmitted by sensor nodes need to be authenticated. Furthermore, for compatibility with an existing communication infrastructure, it may be desirable to adopt RSA in a WSN setting. With this work, we show that, in spite of its long key size, RSA is applicable for wireless sensor networks when optimized arithmetic, low-level coding and some acceleration algorithms are used. We pick three versions of the MSP430 microcontroller, which is used widely on wireless sensor network nodes, and implement 1024-bit RSA on them. Our implementation achieves 1024-bit RSA encryption and decryption operations on MSP430 in only 0.047 s and 1.14 s, respectively. In order to achieve these timings, we utilize several acceleration techniques, such as the subtractive Karatsuba-Ofman, Montgomery multiplication, operand scanning, Chinese remainder theorem and sliding window method. To the best of our knowledge, our timings for 1024-bit RSA encryption and decryption operations are the fastest reported timings in the literature for the MSP430 microcontroller

SoK:Investigation of security and functional safety in industrial IoT

There has been an increasing popularity of industrial usage of Internet of Things (IoT) technologies in parallel to advancements in connectivity and automation. Security vulnerabilities in industrial systems, which are considered less likely to be exploited in conventional closed settings, have now started to be a major concern with Industrial IoT. One of the critical components of any industrial control system turning into a target for attackers is functional safety. This vital function is not originally designed to provide protection against malicious intentional parties but only accidents and errors. In this paper, we explore a generic IoT-based smart manufacturing use-case from a combined perspective of security and functional safety, which are indeed tightly correlated. Our main contribution is the presentation of a taxonomy of threats targeting directly the critical safety function in industrial IoT applications. Besides, based on this taxonomy, we identified particular attack scenarios that might have severe impact on physical assets like manufacturing equipment, even human life and cyber-assets like availability of Industrial IoT application. Finally, we recommend some solutions to mitigate such attacks based mainly on industry standards and advanced security features of mobile communication technologies

A network-based positioning method to locate false base stations

In recent years False Base Stations (FBSs) have received increased attention. A False Base Station can perform active or passive attacks against mobile devices or user equipment (UE) to steal private information, such as International Mobile Subscriber Identifier (IMSI), to trace users locations, or to prevent users from getting service from operators. Most of the existing solutions related to FBS have focused on the detection aspects of the false station rather than locating its position. However, once an FBS is detected in a network, discovering its exact location precisely and remotely becomes highly crucial to initiate preventive actions. In this work, we propose a network-based localization method for estimating the exact geographical position of an FBS whose existence is already detected in a cellular network. Our method relies on a comparative pairwise analysis of the Reference Signals Received Power (RSRP) values reported as a standard procedure by the UEs in the vicinity of FBS through their measurement reports. Specifically, for each pair of related measurement reports, we identify a half-plane indicating the probable location of the FBS and then predict the exact location based on the intersection of all obtained half-planes. We have implemented and experimentally evaluated our proposed method in the Network Simulator 3 (ns-3) and showed that it accurately estimates FBS location with meter-level precision under different scenarios in a cellular network

The prevalence of childhood psychopathology in Turkey: a cross-sectional multicenter nationwide study (EPICPAT-T).

Aim: The aim of this study was to determine the prevalence of childhood psychopathologies in Turkey

Prevalence of Childhood Affective disorders in Turkey: An epidemiological study

Aim: To determine the prevalence of affective disorders in Turkey among a representative sample of Turkish population. Methods: This study was conducted as a part of the "The Epidemiology of Childhood Psychopathology in Turkey" (EPICPAT-T) Study, which was designed by the Turkish Association of Child and Adolescent Mental Health. The inclusion criterion was being a student between the second and fourth grades in the schools assigned as study centers. The assessment tools used were the K-SADS-PL, and a sociodemographic form that was designed by the authors. Impairment was assessed via a 3 point-Likert type scale independently rated by a parent and a teacher. Results: A total of 5842 participants were included in the analyses. The prevalence of affective disorders was 2.5 % without considering impairment and 1.6 % when impairment was taken into account. In our sample, the diagnosis of bipolar disorder was lacking, thus depressive disorders constituted all the cases. Among depressive disorders with impairment, major depressive disorder (MDD) (prevalence of 1.06%) was the most common, followed by dysthymia (prevalence of 0.2%), adjustment disorder with depressive features (prevalence of 0.17%), and depressive disorder-NOS (prevalence of 0.14%). There were no statistically significant gender differences for depression. Maternal psychopathology and paternal physical illness were predictors of affective disorders with pervasive impairment. Conclusion: MDD was the most common depressive disorder among Turkish children in this nationwide epidemiological study. This highlights the severe nature of depression and the importance of early interventions. Populations with maternal psychopathology and paternal physical illness may be the most appropriate targets for interventions to prevent and treat depression in children and adolescents

The prevalence of childhood psychopathology in Turkey: a cross-sectional multicenter nationwide study (EPICPAT-T)

Conclusion: This is the largest and most comprehensive epidemiological study to determine the prevalence of psychopathologies in children and adolescents in Turkey. Our results partly higher than, and partly comparable to previous national and international studies. It also contributes to the literature by determining the independent predictors of psychopathologies in this age group