Spelling suggestions: "subject:"trojan""
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Assuring Intellectual Property Through Physical and Functional ComparisonsHastings, Adam Kendall 01 December 2018 (has links)
Hardware trojans pose a serious threat to trusted computing. However, hardware trojan detection methods are both numerous and onerous, making hardware trojan detection a difficult and time-consuming procedure. This thesis introduces the IP Assurance Framework, which drastically improves the time it takes design teams to test for hardware trojans. The IP Assurance Framework is implemented in two ways: The first method, Physical Assurance, compares instantiated IP blocks to a golden model via physical-level comparisons, while the second method, Functional Assurance, compares IP to a golden model using logical-level comparisons. Both methods are demonstrated to distinguish between tampered and untampered IP blocks, with a tolerable effect on IP timing and area.
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Increasing Security and Trust in HDL IP through Evolutionary ComputingKing, Bayley 23 August 2022 (has links)
No description available.
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The State of Home Computer Security / Säkerhetsläget för hemdatorer 2004Frisk, Ulf, Drocic, Semir January 2004 (has links)
<p>Hundreds of millions of people use their home computers every day for different purposes. Many of them are connected to the Internet. Most of them are unaware of the threats or do not know how to protect themselves. This unawareness is a major threat to global computer security. </p><p>This master thesis starts by explaining some security related terms that might be unknown to the reader. It then goes on by addressing security vulnerabilities and flaws in the most popular home computer operating systems. The most important threats to home computer security are reviewed in the following chapter. These threats include worms, email worms, spyware and trojan horses. After this chapter some possible solutions for improving home computer security are presented. Finally this master thesis contains a short user survey to find out what the problems are in the real world and what can be doneto improve the current situation.</p>
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Σύστημα ανίχνευσης για hardware trojansΚαλογερίδου, Γεωργία 27 April 2015 (has links)
Η επιστήμη της τεχνολογίας αυξάνεται ραγδαία μέρα με τη μέρα. Δυστυχώς όμως όλες αυτές οι νέες τεχνολογικές τάσεις μπορεί να κρύβουν δυσάρεστες «εκπλήξεις». Τα τελευταία χρόνια οι ασύρματες επικοινωνίες έχουν γίνει ένα πολύ σημαντικό κομμάτι της καθημερινότητάς μας. Εμπιστευόμαστε τις ασύρματες συσκευές μας και τις εταιρίες που τις παρέχουν. Ωστόσο, ερωτήματα όπως πόσο ασφαλείς μπορεί να είναι οι συσκευές μας ή οι ασύρματες επικοινωνίες μας δημιουργούνται κάθε μέρα. Παράλληλα με αυτά τα ερωτήματα, εμφανίζονται και τα Hardware Trojans. Τα Hardware Trojans είναι μέρος αυτών των καινούριων τάσεων και αποτελούν ένα πολύ σοβαρό πρόβλημα στο πεδίο των ολοκληρωμένων κυκλωμάτων. Μέχρι σήμερα έχουν γίνει ποικίλες μελέτες, χρησιμοποιώντας διαφορετικές στρατηγικές, Trojans και μεθόδους ανίχνευσης. Στη συγκεκριμένη διπλωματική εργασία παρουσιάζουμε ένα σύστημα ανίχνευσης για Hardware Trojans σε ολοκληρωμένα κυκλώματα ασύρματης κρυπτογράφησης (wireless cryptographic integrated circuit). Περιγράφεται η διαρροή των μυστικών πληροφοριών μέσω ασύρματης επικοινωνίας, χρησιμοποιώντας την τεχνική των ολοκληρωμένων κυκλωμάτων μικτού σήματος (mixed-signal integrated circuits). Δημιουργήθηκαν δύο διαφορετικά Hardware Trojans, τα οποία εισήχθησαν στο αρχικό μας σύστημα, τα οποία βέβαια δεν αλλάζουν τη λειτουργικότητά του. Παρ’ όλ’ αυτά, μπορούν να διαρρεύσουν μυστικές πληροφορίες του συστήματος. Παρουσιάζεται λοιπόν πως είναι δυνατόν να ανιχνευτεί ένα Trojan επιτυχώς μέσω διαφορετικών στατιστικών μετρήσεων που αφορούν τη συχνότητα και το πλάτος του ασύρματου σήματος μετάδοσης. / Technology grows so rapidly day by day. Unfortunately, all these new technological trends may hide unpleasant “surprises”. In recent years wireless communications have become an important part of our everyday life. We rely on our wireless devices and the companies who provide them. However, questions like how safe can our devices be or how secure can our wireless communications be, rise up almost every day. In parallel with these questions, the appearance of Hardware Trojans rise up too. Hardware Trojans are part of these new trends and they have become a serious issue in the field of integrated circuits. Various studies have been done till today, using different strategies, Trojans and detection methods. At this dissertation it is presented a Hardware Trojan detection framework in wireless cryptographic integrated circuit. Τhe leak of secret information through wireless communication is described, using the technic of mixed-signal integrated circuits. There are two Hardware Trojans created and inserted to the original system, which do not change the functionality of the system, but can leak secret information from it. It is presented how a Trojan can be successfully detected through different statistic measurements which are related to the frequency and amplitude of the wireless transmission signal.
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The State of Home Computer Security / Säkerhetsläget för hemdatorer 2004Frisk, Ulf, Drocic, Semir January 2004 (has links)
Hundreds of millions of people use their home computers every day for different purposes. Many of them are connected to the Internet. Most of them are unaware of the threats or do not know how to protect themselves. This unawareness is a major threat to global computer security. This master thesis starts by explaining some security related terms that might be unknown to the reader. It then goes on by addressing security vulnerabilities and flaws in the most popular home computer operating systems. The most important threats to home computer security are reviewed in the following chapter. These threats include worms, email worms, spyware and trojan horses. After this chapter some possible solutions for improving home computer security are presented. Finally this master thesis contains a short user survey to find out what the problems are in the real world and what can be doneto improve the current situation.
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Orbitální a kolizní dynamika malých těles / Orbital and collisional dynamics of small bodiesRozehnal, Jakub January 2021 (has links)
This work is devoted to a study of dynamical and collisional processes, governing populations of small bodies in the Solar System. It pays special attention to asteroid families and Jupiter Trojans. Librating around L4 and L5 Lagrangian points of the Sun-Jupiter-asteroid system, these asteroids are believed to be captured from the trans- Neptunian region during a giant planet system instability about 4 Gy ago. We discovered (back in 2011) there is only one significant collisional family among Trojans, associated with C-type asteroid (3548) Eurybates, i.e., one of the targets for the upcoming 'Lucy' mission. Detailed analysis of new proper resonant orbital elements, colours and albedos, together with statistical significance computations, allowed us to find five more collisional families: Hektor, (9799), Arkesilaos, Ennomos, and (247341). The discovery of the first D-type family associated with (624) Hektor was the most surprising, because it is the most primitive taxonomic type. Using long-term dynamical simulations of synthetic families, evolving by chaotic diffusion, we estimated the ages of the Eurybates and Hektor families, approximately (2.5±1.5) Gy for both. We also studied impact processes by means of the smoothed-particle hydrodynamics (SPH). We simulated cratering events on (624) Hektor, the origin...
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Detection of Avionics Supply Chain Non-control-flow Malware Using Binary Decompilation and Wavelet AnalysisHill, Jeremy Michael Olivar 09 August 2021 (has links)
No description available.
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Detecting RTL Trojans Using Artificial Immune Systems and High Level Behavior ClassificationZareen, Farhath 20 February 2019 (has links)
Security assurance in a computer system can be viewed as distinguishing between self and non-self. Artificial Immune Systems (AIS) are a class of machine learning (ML) techniques inspired by the behavior of innate biological immune systems, which have evolved to accurately classify self-behavior from non-self-behavior. This work aims to leverage AIS-based ML techniques for identifying certain behavioral traits in high level hardware descriptions, including unsafe or undesirable behaviors, whether such behavior exists due to human error during development or due to intentional, malicious circuit modifications, known as hardware Trojans, without the need fora golden reference model. We explore the use of Negative Selection and Clonal Selection Algorithms, which have historically been applied to malware detection on software binaries, to detect potentially unsafe or malicious behavior in hardware. We present a software tool which analyzes Trojan-inserted benchmarks, extracts their control and data-flow graphs (CDFGs), and uses this to train an AIS behavior model, against which new hardware descriptions may be tested.
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Built-In Return-Oriented Programs in Embedded Systems and Deep Learning for Hardware Trojan DetectionWeidler, Nathanael R. 01 December 2019 (has links)
Microcontrollers and integrated circuits in general have become ubiquitous in the world today. All aspects of our lives depend on them from driving to work, to calling our friends, to checking our bank account balance. People who would do harm to individuals, corporations and nation states are aware of this and for that reason they seek to find or create and exploit vulnerabilities in integrated circuits. This dissertation contains three papers dealing with these types of vulnerabilities. The first paper talks about a vulnerability that was found on a microcontroller, which is a type of integrated circuit. The final two papers deal with hardware trojans. Hardware trojans are purposely added to the design of an integrated circuit in secret so that the manufacturer doesn’t know about it. They are used to damage the integrated circuit, leak confidential information, or in other ways alter the circuit. Hardware trojans are a major concern for anyone using integrated circuits because an attacker can alter a circuit in almost any way if they are successful in inserting one. A known method to prevent hardware trojan insertion is discussed and a type of circuit for which this method does not work is revealed. The discussion of hardware trojans is concluded with a new way to detect them before the integrated circuit is manufactured. Modern deep learning models are used to detect the portions of the hardware trojan called triggers that activate them.
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Monitoring for Reliable and Secure Power Management Integrated Circuits via Built-In Self-TestJanuary 2019 (has links)
abstract: Power management circuits are employed in most electronic integrated systems, including applications for automotive, IoT, and smart wearables. Oftentimes, these power management circuits become a single point of system failure, and since they are present in most modern electronic devices, they become a target for hardware security attacks. Digital circuits are typically more prone to security attacks compared to analog circuits, but malfunctions in digital circuitry can affect the analog performance/parameters of power management circuits. This research studies the effect that these hacks will have on the analog performance of power circuits, specifically linear and switching power regulators/converters. Apart from security attacks, these circuits suffer from performance degradations due to temperature, aging, and load stress. Power management circuits usually consist of regulators or converters that regulate the load’s voltage supply by employing a feedback loop, and the stability of the feedback loop is a critical parameter in the system design. Oftentimes, the passive components employed in these circuits shift in value over varying conditions and may cause instability within the power converter. Therefore, variations in the passive components, as well as malicious hardware security attacks, can degrade regulator performance and affect the system’s stability. The traditional ways of detecting phase margin, which indicates system stability, employ techniques that require the converter to be in open loop, and hence can’t be used while the system is deployed in-the-field under normal operation. Aging of components and security attacks may occur after the power management systems have completed post-production test and have been deployed, and they may not cause catastrophic failure of the system, hence making them difficult to detect. These two issues of component variations and security attacks can be detected during normal operation over the product lifetime, if the frequency response of the power converter can be monitored in-situ and in-field. This work presents a method to monitor the phase margin (stability) of a power converter without affecting its normal mode of operation by injecting a white noise/ pseudo random binary sequence (PRBS). Furthermore, this work investigates the analog performance parameters, including phase margin, that are affected by various digital hacks on the control circuitry associated with power converters. A case study of potential hardware attacks is completed for a linear low-dropout regulator (LDO). / Dissertation/Thesis / Masters Thesis Electrical Engineering 2019
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