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We introduce a compiler that automatically inserts software countermeasures to protect cryptographic algorithms against power-based side-channel attacks. The compiler first estimates which instruction instances leak the most information through side-channels. This information is obtained either by dynamic analysis, evaluating an information theoretic metric over the power traces acquired during the execution of the input program, or by static analysis. As information leakage implies a loss of security, the compiler then identifies (groups of) instruction instances to protect with a software countermeasure such as random precharging or Boolean masking. As software protection incurs significant overhead in terms of cryptosystem runtime and memory usage, the compiler protects the minimum number of instruction instances to achieve a desired level of security. The compiler is evaluated on two block ciphers, AES and Clefia; our experiments demonstrate that the compiler can automatically identify and protect the most important instruction instances. To date, these software countermeasures have been inserted manually by security experts, who are not necessarily the main cryptosystem developers. Our compiler offers significant productivity gains for cryptosystem developers who wish to protect their implementations from side-channel attacks.

This paper introduces a generic and automated methodology to protect hardware designs from side-channel attacks in a manner that is fully compatible with commercial standard cell design flows. The paper describes a tool that artificially adds jitter to the clocks of the sequential elements of a cryptographic unit, which increases the non-determinism of signal timing, thereby making the physical device more difficult to attack. Timing constraints are then specified to commercial EDA tools, which restore the circuit functionality and efficiency while preserving the introduced randomness. The protection scheme is applied to an AES-128 hardware implementation that is synthesized using both ASIC and FPGA design flows. © 2013 EDAA.

We introduce a counting stream register snoop filter, which improves the performance of existing snoop filters based on stream registers. Over time, this class of snoop filters loses the ability to filter memory addresses that have been loaded, and then evicted, from the caches that are filtered; they include cache wrap detection logic, which resets the filter whenever the contents of the cache have been completely replaced. The counting stream register snoop filter introduced here replaces the cache wrap detection logic with a direct-mapped update unit and augments each stream register with a counter, which acts as a validity checker; loading new data into the cache increments the counter, while replacements, snoopy invalidations, and evictions decrement it. A cache wrap is detected whenever the counter reaches zero. Our experimental evaluation shows that the counting stream register snoop filter architecture improves the accuracy compared to traditional stream register snoop filters for representative embedded workloads. © 2012 IEEE.

In cryptography, side channel attacks, such as power analysis, attempt to uncover secret information from the physical implementation of cryptosystems rather than exploiting weaknesses in the cryptographic algorithms themselves. The design and implementation of physically secure cryptosystems is a challenge for both hardware and software designers. Measuring and evaluating the security of a system is manual and empirical, which is costly and time consuming; this work demonstrates that it is possible to automate these processes. We introduce a systematic methodology for automatic application of software countermeasures and demonstrate its effectiveness on an AES software implementation running on an 8-bit AVR microcontroller. The framework identifies the most vulnerable instructions of the implementation to power analysis attacks, and then transforms the software using a chosen countermeasure to protect the vulnerable instructions. Lastly, it evaluates the security of the system using an information-theoretic metric and a direct attack. © 2011 ACM.

Essential thrombocythemia (ET) is a type of myeloproliferative neoplasm that increases the risk of thrombosis. To diagnose this disease, the analysis of mutations in the Janus Kinase 2 (JAK2), thrombopoietin receptor (MPL), or calreticulin (CALR) gene is recommended. Disease poses diagnostic challenges due to overlapping mutations with other neoplasms and the presence of triple-negative cases. This study explores the potential of Raman spectroscopy combined with machine learning for ET diagnosis. We assessed two laser wavelengths (785, 1064 nm) to differentiate between ET patients and healthy controls. The PCR results indicate that approximately 50% of patients in our group have a mutation in the JAK2 gene, while only 5% of patients harbor a mutation in the ASXL1 gene. Additionally, only one patient had a mutation in the IDH1 and one had a mutation in IDH2 gene. Consequently, patients having no mutations were also observed in our group, making diagnosis challenging. Raman spectra at 1064 nm showed lower amide, polysaccharide, and lipid vibrations in ET patients, while 785 nm spectra indicated significant decreases in amide II and C-H lipid vibrations. Principal Component Analysis (PCA) confirmed that both wavelengths could distinguish ET from healthy subjects. Support Vector Machine (SVM) analysis revealed that the 800-1800 cm -1 range provided the highest diagnostic accuracy, with 89% for 785 nm and 72% for 1064 nm. These findings suggest that FT-Raman spectroscopy, paired with multivariate and machine learning analyses, offers a promising method for diagnosing ET with high accuracy by detecting specific molecular changes in serum. Principal Component Analysis (PCA) confirmed that both wavelengths could distinguish ET from healthy subjects. Support Vector Machine (SVM) analysis revealed that the 800-1800 cm -1 range provided the highest diagnostic accuracy, with 89% for 785 nm and 72% for 1064 nm. These findings suggest that FT-Raman spectroscopy, paired with multivariate and machine learning analyses, offers a promising method for diagnosing ET with high accuracy by detecting specific molecular changes in serum., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The study utilized Fourier transform infrared (FTIR) spectroscopy coupled with chemometrics to investigate protein composition and structural changes in the blood serum of patients with polycythemia vera (PV). Principal component analysis (PCA) revealed distinct biochemical properties, highlighting elevated absorbance of phospholipids, amides, and lipids in PV patients compared to healthy controls. Ratios of amide I/amide II and amide I/amide III indicated alterations in protein structures. Support vector machine analysis and receiver operating characteristic curves identified amide I as a crucial predictor of PV, achieving 100% accuracy, sensitivity, and specificity, while amide III showed a lower predictive value (70%). PCA analysis demonstrated effective differentiation between PV patients and controls, with key wavenumbers including amide II, amide I, and CH lipid vibrations. These findings underscore the potential of FTIR spectroscopy for diagnosing and monitoring PV., (© 2024 The Author(s). Journal of Biophotonics published by Wiley-VCH GmbH.)

Primary myelofibrosis (PM) is a myeloproliferative neoplasm characterized by stem cell-derived clonal neoplasms. Several factors are involved in diagnosing PM, including physical examination, peripheral blood findings, bone marrow morphology, cytogenetics, and molecular markers. Commonly gene mutations are used. Also, these gene mutations exist in other diseases, such as polycythemia vera and essential thrombocythemia. Hence, understanding the molecular mechanism and finding disease-related biomarker characteristics only for PM is crucial for the treatment and survival rate. For this purpose, blood samples of PM (n = 85) vs. healthy controls (n = 45) were collected for biochemical analysis, and, for the first time, Fourier Transform InfraRed (FTIR) spectroscopy measurement of dried PM and healthy patients' blood serum was analyzed. A Support Vector Machine (SVM) model with optimized hyperparameters was constructed using the grid search (GS) method. Then, the FTIR spectra of the biomolecular components of blood serum from PM patients were compared to those from healthy individuals using Principal Components Analysis (PCA). Also, an analysis of the rate of change of FTIR spectra absorption was studied. The results showed that PM patients have higher amounts of phospholipids and proteins and a lower amount of H-O=H vibrations which was visible. The PCA results indicated that it is possible to differentiate between dried blood serum samples collected from PM patients and healthy individuals. The Grid Search Support Vector Machine (GS-SVM) model showed that the prediction accuracy ranged from 0.923 to 1.00 depending on the FTIR range analyzed. Furthermore, it was shown that the ratio between α-helix and β-sheet structures in proteins is 1.5 times higher in PM than in control people. The vibrations associated with the CO bond and the amide III region of proteins showed the highest probability value, indicating that these spectral features were significantly altered in PM patients compared to healthy ones' spectra. The results indicate that the FTIR spectroscope may be used as a technique helpful in PM diagnostics. The study also presents preliminary results from the first prospective clinical validation study., Competing Interests: Declaration of Competing Interest The authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Primary myelofibrosis (PM) is one of the myeloproliferative neoplasm, where stem cell-derived clonal neoplasms was noticed. Diagnosis of this disease is based on: physical examination, peripheral blood findings, bone marrow morphology, cytogenetics, and molecular markers. However, the molecular marker of PM, which is a mutation in the JAK2V617F gene, was observed also in other myeloproliferative neoplasms such as polycythemia vera and essential thrombocythemia. Therefore, there is a need to find methods that provide a marker unique to PM and allow for higher accuracy of PM diagnosis and consequently the treatment of the disease. Continuing, in this study, we used Raman spectroscopy, Principal Components Analysis (PCA), and Partial Least Squares (PLS) analysis as helpful diagnostic tools for PM. Consequently, we used serum collected from PM patients, which were classified using clinical parameters of PM such as the dynamic international prognostic scoring system (DIPSS) for primary myelofibrosis plus score, the JAK2V617F mutation, spleen size, bone marrow reticulin fibrosis degree and use of hydroxyurea drug features. Raman spectra showed higher amounts of C-H, C-C and C-C/C-N and amide II and lower amounts of amide I and vibrations of CH 3 groups in PM patients than in healthy ones. Furthermore, shifts of amides II and I vibrations in PM patients were noticed. Machine learning methods were used to analyze Raman regions: (i) 800 cm -1 and 1800 cm -1 , (ii) 1600 cm -1 -1700 cm -1 , and (iii) 2700 cm -1 -3000 cm -1 showed 100 % accuracy, sensitivity, and specificity. Differences in the spectral dynamic showed that differences in the amide II and amide I regions were the most significant in distinguishing between PM and healthy subjects. Importantly, until now, the efficacy of Raman spectroscopy has not been established in clinical diagnostics of PM disease using the correlation between Raman spectra and PM clinical prognostic scoring. Continuing, our results showed the correlation between Raman signals and bone marrow fibrosis, as well as JAKV617F. Consequently, the results revealed that Raman spectroscopy has a high potential for use in medical laboratory diagnostics to quantify multiple biomarkers simultaneously, especially in the selected Raman regions., Competing Interests: Declaration of competing interest There are no conflicts of interest in this study., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Essential thrombocythemia (ET) reflects the transformation of a multipotent hematopoietic stem cell, but its molecular pathogenesis remains obscure. Nevertheless, tyrosine kinase, especially Janus kinase 2 (JAK2), has been implicated in myeloproliferative disorders other than chronic myeloid leukaemia. FTIR analysis was performed on the blood serum of 86 patients and 45 healthy volunteers as control with FTIR spectra-based machine learning methods and chemometrics. Thus, the study aimed to determine biomolecular changes and separation of ET and healthy control groups illustration by applying chemometrics and ML techniques to spectral data. The FTIR-based results showed that in ET disease with JAK2 mutation, there are alterations in functional groups associated with lipids, proteins and nucleic acids significantly. Moreover, in ET patients the lower amount of proteins with simultaneously higher amount of lipids was noted in comparison with the control one. Furthermore, the SVM-DA model showed 100% accuracy in calibration sets in both spectral regions and 100.0% and 96.43% accuracy in prediction sets for the 800-1800 cm -1 and 2700-3000 cm -1 spectral regions, respectively. While changes in the dynamic spectra showed that CH 2 bending, amide II and CO vibrations could be used as a spectroscopy marker of ET. Finally, it was found a positive correlation between FTIR peaks and first bone marrow fibrosis degree, as well as the absence of JAK2 V617F mutation. The findings of this study contribute to a better understanding of the molecular pathogenesis of ET and identifying biomolecular changes and may have implications for early diagnosis and treatment of this disease., Competing Interests: Declaration of Competing Interest The authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript., (Copyright © 2023 Elsevier B.V. All rights reserved.)

This study aimed to develop a novel approach for diagnosing Polycythemia Vera (PV), a stem cell-derived neoplasm of the myeloid lineage. The approach utilized Raman spectroscopy coupled with multivariate analysis to analyze blood serum samples collected from PV patients. The results showed that PV serum exhibited lower protein and lipid levels and structural changes in the functional groups that comprise proteins and lipids. The study also demonstrated differences in lipid biosynthesis and protein levels in PV serum. Using the Partial Least Square Discriminant Analysis (PLS-DA) model, Raman-based multivariate analysis achieved high accuracy rates of 96.49 and 93.04% in the training sets and 93.10% and 89.66% in the test sets for the 800-1800 cm -1 and 2700-3000 cm -1 ranges, respectively. The area under the curve (AUC) values of the test datasets were calculated as 0.92 and 0.89 in the 800-1800 cm -1 and 2700-3000 cm -1 spectral regions, respectively, demonstrating the effectiveness of the PLS-DA models for the diagnosis of PV. This study highlights the potential of Raman spectroscopy-based analysis in the early and accurate diagnosis of PV, enabling the application of effective treatment strategies., Competing Interests: Declaration of Competing Interest The authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Variant Philadelphia (Ph) translocations involving chromosome 7 are rarely seen in Chronic Myeloid Leukemia (CML) patients. It is aimed to contribute new cases to the literature by reviewing the cases in our archive and shed light into the understanding of the role of chromosome 7 in CML. This study was carried out in 237 newly diagnosed CML patients with variant Ph translocations. Among the patients, those with variant Ph translocation involving chromosome 7 were evaluated in terms of clinical and genetic characteristics. Chromosome analysis was performed on 24 and 48 h of bone marrow cultures. FISH analysis was performed with BCR-ABL1 dual color dual fusion translocation probes. BCR-ABL1 transcript levels were analysed by QRT-PCR and results were reported as BCR-ABL1/ABL1 (BCR-ABL1 (IS) %) according to international scale. Four of the patients had variant Ph translocations including chromosome 7. The karyotypes were 46,XX,t(7;9;22)(p13;q34;q11); 46,XX,t(7;9;22)(p21;q34;q11); 46,XX,t(7;9;22)(q22;q34;q11) and 46,XY,t(7;9;22)(q22;q34;q11). The breakpoints demonstrated by cytogenetic analysis were confirmed by FISH analysis. Monitoring by QRT-PCR showed that patients with variant Ph translocation including 7p13 and 7p21 had a dramatic decrease in BCR-ABL1 levels resulting in complete hematological, complete cytogenetic and deep molecular responses. Despite achieving complete hematological, complete cytogenetic response in two patients with variant Philadelphia translocation, including 7q22, no major molecular response was achieved and both patients are still in the warning category. Response to tyrosine kinase inhibitör therapy may be associated with both the variant translocation mechanism and new gene interactions that occur due to the breakpoints of additional chromosomes involved in translocation., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: Carriers of structural chromosomal rearrangements such as Robertsonian or reciprocal translocations have an increased risk of spontaneous abortion and producing offspring with genetic abnormalities., Case Report: We report a man with balanced chromosomal translocations located at 6p22, and 7q22. His wife has a history of four spontaneous abortions., Conclusion: Couples with a history of abortions should be investigated cytogenetically, after other causes of miscarriages are excluded. The possibility of spontaneous abortions can be reduced with preimplantation genetic diagnosis (PGD) before embryo transfer.