7 research outputs found
ΠΠ»Π³ΠΎΡΠΈΡΠΌ ΠΈ ΡΠ΅Ρ Π½ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ ΡΠ΅ΡΠ΅ΠΉ
ΠΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ ΡΠ°ΠΊΡΠΎΡΡ, ΠΎΠ±ΡΡΠ»Π°Π²Π»ΠΈΠ²Π°ΡΡΠΈΠ΅ ΡΠ°ΡΡΠΈΡΠ΅Π½ΠΈΠ΅ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ ΠΈ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΈΠ²Π½ΠΎΡΡΠΈ ΡΠ΅ΡΠ΅Π²ΠΎΠΉ ΡΠ°Π·Π²Π΅Π΄ΠΊΠΈ ΠΏΠΎ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΡΠΎΡΡΠ°Π²Π° ΠΈ ΡΡΡΡΠΊΡΡΡΡ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ Π²ΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠ΅ ΡΡΠ°ΡΠΈΠΎΠ½Π°ΡΠ½ΠΎΡΡΠΈ ΠΈΡ
ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ. ΠΡΠΊΡΡΡΡΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ Π·Π°ΡΠΈΡΡ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΡ
Π½Π° ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΎΠ² ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠΎΡΠΌΠ°Π»ΠΈΠ·Π°ΡΠΈΡ ΠΈ Π²Π½Π΅Π΄ΡΠ΅Π½ΠΈΠ΅ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π° Π·Π°ΠΏΡΠ΅ΡΠ°ΡΡΠΈΡ
ΡΠ΅Π³Π»Π°ΠΌΠ΅Π½ΡΠΎΠ² ΠΎΠ±ΠΎΡΠ½ΠΎΠ²ΡΠ²Π°ΡΡ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ Π·Π°Π΄Π°ΡΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠΌΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ°ΠΌΠΈ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ, ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΡΡΡΠΈΡ
Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΠ΅ΡΠ΅Π²ΠΎΠΉ ΡΠ°Π·Π²Π΅Π΄ΠΊΠΈ.
ΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠ°Ρ Π½Π°Ρ
ΠΎΠ΄ΠΈΡΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠ΅ ΡΠ΅ΠΆΠΈΠΌΡ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ Π΄Π»Ρ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΠΈΡΡΠ°ΡΠΈΠΉ. ΠΡΠΈΠ²Π΅Π΄Π΅Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ°ΡΡΠ΅ΡΠΎΠ². ΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ Π°Π»Π³ΠΎΡΠΈΡΠΌ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π·Π°Π΄Π°ΡΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΠΈ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΠΎΠΉ Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΠ΅ΡΠΈ, ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°ΡΡΠΈΠΉ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΠ΅ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΠΎΡΡΠΈ Π΄ΠΎΠ±ΡΠ²Π°Π΅ΠΌΡΡ
ΡΠ΅ΡΠ΅Π²ΠΎΠΉ ΡΠ°Π·Π²Π΅Π΄ΠΊΠΎΠΉ Π΄Π°Π½Π½ΡΡ
. ΠΠΎΠΊΠ°Π·Π°Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΡΠΏΡΡΠ°Π½ΠΈΠΉ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠ³ΠΎ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ. ΠΠΎΠ»ΡΡΠ΅Π½Π½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ²ΠΈΠ΄Π΅ΡΠ΅Π»ΡΡΡΠ²ΡΡΡ, ΡΡΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΠΏΠΎ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΌΡ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΏΠΎΠ²ΡΡΠΈΡΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΈΠ²Π½ΠΎΡΡΡ Π·Π°ΡΠΈΡΡ Π·Π° ΡΡΠ΅Ρ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΈΡ
ΠΏΠΎΠ΄ΡΠ΅ΡΠ΅ΠΉ. ΠΡΠΈ ΡΡΠΎΠΌ Π΄ΠΎΡΡΠΈΠ³Π½ΡΡΠΎ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅ ΠΊΡΠΈΡΠΈΡΠ΅ΡΠΊΠΈ Π²Π°ΠΆΠ½ΡΡ
ΡΠΎΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΠΉ, Π° ΠΈΠ½ΡΠ΅ΡΠ²Π°Π»Ρ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ Π°Π΄Π°ΠΏΡΠΈΠ²Π½Ρ ΠΊ ΡΡΠ»ΠΎΠ²ΠΈΡΠΌ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ Π΄Π΅ΠΉΡΡΠ²ΠΈΡΠΌ Π·Π»ΠΎΡΠΌΡΡΠ»Π΅Π½Π½ΠΈΠΊΠ°.
ΠΠΎΠ²ΠΈΠ·Π½Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π·Π°ΠΊΠ»ΡΡΠ°Π΅ΡΡΡ Π² ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°ΠΏΠΏΠ°ΡΠ°ΡΠ° ΡΠ΅ΠΎΡΠΈΠΈ ΠΌΠ°ΡΠΊΠΎΠ²ΡΠΊΠΈΡ
ΡΠ»ΡΡΠ°ΠΉΠ½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΠΈ ΡΠ΅ΡΠ΅Π½ΠΈΠΈ ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΉ ΠΠΎΠ»ΠΌΠΎΠ³ΠΎΡΠΎΠ²Π° Π΄Π»Ρ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΡ Π²ΡΠ±ΠΎΡΠ° ΡΠ΅ΠΆΠΈΠΌΠΎΠ² Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ. ΠΠΎΠ²ΠΈΠ·Π½Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠ³ΠΎ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° ΡΠΎΡΡΠΎΠΈΡ Π² ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ Π΄Π»Ρ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠΌΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ°ΠΌΠΈ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΠΎΠΉ Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΠ΅ΡΠΈ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΠ΅ΡΠ΅Π²ΠΎΠΉ ΡΠ°Π·Π²Π΅Π΄ΠΊΠΈ
ΠΠ»Π³ΠΎΡΠΈΡΠΌ ΠΈ ΡΠ΅Ρ Π½ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ ΡΠ΅ΡΠ΅ΠΉ
The main factors that determine the expansion of capabilities and increase the effectiveness of network intelligence to identify the composition and structure of client-server computer networks due to the stationarity of their structural and functional characteristics are analyzed. The substantiation of an urgent problem of dynamic management of structurally-functional characteristics of the client-server computer networks functioning in the conditions of network reconnaissance is resulted on the grounds of the revealed protection features of client-server computer networks at the present stage that is based on realization of principles of spatial safety maintenance, and also formalization and introduction of forbidding regulations.
The mathematical model allowing to find optimum modes for dynamic configuration of structurally-functional characteristics of client-server computer networks for various situations is presented. Calculation results are given. An algorithm is presented that makes it possible to solve the problem of dynamic configuration of the structural and functional characteristics of a client-server computer network, which reduces the reliability time of data obtained by network intelligence. The results of practical tests of software developed on the basis of the dynamic configuration algorithm of client-server computer networks are shown. The obtained results show that the use of the presented solution for the dynamic configuration of client-server computer networks allows to increase the effectiveness of protection by changing the structural and functional characteristics of client-server computer networks within several subnets without breaking critical connections through time intervals that are adaptively changed depending on the functioning conditions and the attackerβs actions.
The novelty of the developed model lies in the application of the mathematical apparatus of the Markovβs theory of random processes and Kolmogorovβs solution of equations to justify the choice of dynamic configuration modes for the structural and functional characteristics of client-server computer networks. The novelty of the developed algorithm is the use of a dynamic configuration model for the structural and functional characteristics of client-server computer networks for the dynamic control of the structural and functional characteristics of a client-server computer network in network intelligence.ΠΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ ΡΠ°ΠΊΡΠΎΡΡ, ΠΎΠ±ΡΡΠ»Π°Π²Π»ΠΈΠ²Π°ΡΡΠΈΠ΅ ΡΠ°ΡΡΠΈΡΠ΅Π½ΠΈΠ΅ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ ΠΈ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΈΠ²Π½ΠΎΡΡΠΈ ΡΠ΅ΡΠ΅Π²ΠΎΠΉ ΡΠ°Π·Π²Π΅Π΄ΠΊΠΈ ΠΏΠΎ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΡΠΎΡΡΠ°Π²Π° ΠΈ ΡΡΡΡΠΊΡΡΡΡ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ Π²ΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠ΅ ΡΡΠ°ΡΠΈΠΎΠ½Π°ΡΠ½ΠΎΡΡΠΈ ΠΈΡ
ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ. ΠΡΠΊΡΡΡΡΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ Π·Π°ΡΠΈΡΡ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΡ
Π½Π° ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΎΠ² ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠΎΡΠΌΠ°Π»ΠΈΠ·Π°ΡΠΈΡ ΠΈ Π²Π½Π΅Π΄ΡΠ΅Π½ΠΈΠ΅ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π° Π·Π°ΠΏΡΠ΅ΡΠ°ΡΡΠΈΡ
ΡΠ΅Π³Π»Π°ΠΌΠ΅Π½ΡΠΎΠ² ΠΎΠ±ΠΎΡΠ½ΠΎΠ²ΡΠ²Π°ΡΡ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ Π·Π°Π΄Π°ΡΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠΌΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ°ΠΌΠΈ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ, ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΡΡΡΠΈΡ
Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΠ΅ΡΠ΅Π²ΠΎΠΉ ΡΠ°Π·Π²Π΅Π΄ΠΊΠΈ.
ΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠ°Ρ Π½Π°Ρ
ΠΎΠ΄ΠΈΡΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠ΅ ΡΠ΅ΠΆΠΈΠΌΡ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ Π΄Π»Ρ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΠΈΡΡΠ°ΡΠΈΠΉ. ΠΡΠΈΠ²Π΅Π΄Π΅Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ°ΡΡΠ΅ΡΠΎΠ². ΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ Π°Π»Π³ΠΎΡΠΈΡΠΌ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π·Π°Π΄Π°ΡΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΠΈ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΠΎΠΉ Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΠ΅ΡΠΈ, ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°ΡΡΠΈΠΉ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΠ΅ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΠΎΡΡΠΈ Π΄ΠΎΠ±ΡΠ²Π°Π΅ΠΌΡΡ
ΡΠ΅ΡΠ΅Π²ΠΎΠΉ ΡΠ°Π·Π²Π΅Π΄ΠΊΠΎΠΉ Π΄Π°Π½Π½ΡΡ
. ΠΠΎΠΊΠ°Π·Π°Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΡΠΏΡΡΠ°Π½ΠΈΠΉ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠ³ΠΎ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ. ΠΠΎΠ»ΡΡΠ΅Π½Π½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ²ΠΈΠ΄Π΅ΡΠ΅Π»ΡΡΡΠ²ΡΡΡ, ΡΡΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΠΏΠΎ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΌΡ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΏΠΎΠ²ΡΡΠΈΡΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΈΠ²Π½ΠΎΡΡΡ Π·Π°ΡΠΈΡΡ Π·Π° ΡΡΠ΅Ρ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΈΡ
ΠΏΠΎΠ΄ΡΠ΅ΡΠ΅ΠΉ. ΠΡΠΈ ΡΡΠΎΠΌ Π΄ΠΎΡΡΠΈΠ³Π½ΡΡΠΎ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅ ΠΊΡΠΈΡΠΈΡΠ΅ΡΠΊΠΈ Π²Π°ΠΆΠ½ΡΡ
ΡΠΎΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΠΉ, Π° ΠΈΠ½ΡΠ΅ΡΠ²Π°Π»Ρ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ Π°Π΄Π°ΠΏΡΠΈΠ²Π½Ρ ΠΊ ΡΡΠ»ΠΎΠ²ΠΈΡΠΌ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ Π΄Π΅ΠΉΡΡΠ²ΠΈΡΠΌ Π·Π»ΠΎΡΠΌΡΡΠ»Π΅Π½Π½ΠΈΠΊΠ°.
ΠΠΎΠ²ΠΈΠ·Π½Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π·Π°ΠΊΠ»ΡΡΠ°Π΅ΡΡΡ Π² ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°ΠΏΠΏΠ°ΡΠ°ΡΠ° ΡΠ΅ΠΎΡΠΈΠΈ ΠΌΠ°ΡΠΊΠΎΠ²ΡΠΊΠΈΡ
ΡΠ»ΡΡΠ°ΠΉΠ½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΠΈ ΡΠ΅ΡΠ΅Π½ΠΈΠΈ ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΉ ΠΠΎΠ»ΠΌΠΎΠ³ΠΎΡΠΎΠ²Π° Π΄Π»Ρ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΡ Π²ΡΠ±ΠΎΡΠ° ΡΠ΅ΠΆΠΈΠΌΠΎΠ² Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ. ΠΠΎΠ²ΠΈΠ·Π½Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠ³ΠΎ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° ΡΠΎΡΡΠΎΠΈΡ Π² ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΡΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΠ΅ΠΉ Π΄Π»Ρ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠΌΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ°ΠΌΠΈ ΠΊΠ»ΠΈΠ΅Π½Ρ-ΡΠ΅ΡΠ²Π΅ΡΠ½ΠΎΠΉ Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΠ΅ΡΠΈ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΠ΅ΡΠ΅Π²ΠΎΠΉ ΡΠ°Π·Π²Π΅Π΄ΠΊΠΈ
Moving Target Defense for Web Applications
abstract: Web applications continue to remain as the most popular method of interaction for businesses over the Internet. With it's simplicity of use and management, they often function as the "front door" for many companies. As such, they are a critical component of the security ecosystem as vulnerabilities present in these systems could potentially allow malicious users access to sensitive business and personal data.
The inherent nature of web applications enables anyone to access them anytime and anywhere, this includes any malicious actors looking to exploit vulnerabilities present in the web application. In addition, the static configurations of these web applications enables attackers the opportunity to perform reconnaissance at their leisure, increasing their success rate by allowing them time to discover information on the system. On the other hand, defenders are often at a disadvantage as they do not have the same temporal opportunity that attackers possess in order to perform counter-reconnaissance. Lastly, the unchanging nature of web applications results in undiscovered vulnerabilities to remain open for exploitation, requiring developers to adopt a reactive approach that is often delayed or to anticipate and prepare for all possible attacks which is often cost-prohibitive.
Moving Target Defense (MTD) seeks to remove the attackers' advantage by reducing the information asymmetry between the attacker and defender. This research explores the concept of MTD and the various methods of applying MTD to secure Web Applications. In particular, MTD concepts are applied to web applications by implementing an automated application diversifier that aims to mitigate specific classes of web application vulnerabilities and exploits. Evaluation is done using two open source web applications to determine the effectiveness of the MTD implementation. Though developed for the chosen applications, the automation process can be customized to fit a variety of applications.Dissertation/ThesisMasters Thesis Computer Science 201
Moving target defense for securing smart grid communications: Architectural design, implementation and evaluation
Supervisory Control And Data Acquisition (SCADA) communications are often subjected to various kinds of sophisticated cyber-attacks which can have a serious impact on the Critical Infrastructure such as the power grid. Most of the time, the success of the attack is based on the static characteristics of the system, thereby enabling an easier profiling of the target system(s) by the adversary and consequently exploiting their limited resources. In this thesis, a novel approach to mitigate such static vulnerabilities is proposed by implementing a Moving Target Defense (MTD) strategy in a power grid SCADA environment, which leverages the existing communication network with an end-to-end IP Hopping technique among the trusted peer devices. This offers a proactive L3 layer network defense, minimizing IP-specific threats and thwarting worm propagation, APTs, etc., which utilize the cyber kill chain for attacking the system through the SCADA network. The main contribution of this thesis is to show how MTD concepts provide proactive defense against targeted cyber-attacks, and a dynamic attack surface to adversaries without compromising the availability of a SCADA system.
Specifically, the thesis presents a brief overview of the different type of MTD designs, the proposed MTD architecture and its implementation with IP hopping technique over a Control CenterβSubstation network link along with a 3-way handshake protocol for synchronization on the Iowa Stateβs Power Cyber testbed. The thesis further investigates the delay and throughput characteristics of the entire system with and without the MTD to choose the best hopping rate for the given link. It also includes additional contributions for making the testbed scenarios more realistic to real world scenarios with multi-hop, multi-path WAN. Using that and studying a specific attack model, the thesis analyses the best ranges of IP address for different hopping rate and different number of interfaces. Finally, the thesis describes two case studies to explore and identify potential weaknesses of the proposed mechanism, and also experimentally validate the proposed mitigation alterations to resolve the discovered vulnerabilities. As part of future work, we plan to extend this work by optimizing the MTD algorithm to be more resilient by incorporating other techniques like network port mutation to further increase the attack complexity and cost
Discrete Moving Target Defense Application and Benchmarking in Software-Defined Networking
Moving Target Defense is a technique focused on disrupting certain phases of a cyber-attack. The static nature of the existing networks gives the adversaries an adequate amount of time to gather enough data concerning the target and succeed in mounting an attack. The random host address mutation is a well-known MTD technique that hides the actual IP address from external scanners. When the host establishes a session of transmitting or receiving data, due to mutation interval, the session is interrupted, leading to the hostβs unavailability. Moving the network configuration creates overhead on the controller and additional switching costs resulting in latency, poor performance, packet loss, and jitter.
In this dissertation, we proposed a novel discrete MTD technique in software-defined networking (SDN) to individualize the mutation interval for each host. The host IP address is changed at different intervals to avoid the termination of the existing sessions and to increase complexity in understanding mutation intervals for the attacker. We use the flow statistics of each host to determine if the host is in a session of transmitting or receiving data. Individualizing the mutation interval of each host enhances the defender game strategy making it complex in determining the pattern of mutation interval. Since the mutation of the host address is achieved using a pool of virtual (temporary) host addresses, a subnet game strategy is introduced to increase complexity in determining the network topology. A benchmarking framework is developed to measure the performance, scalability, and reliability of the MTD network with the traditional network. The analysis shows the discrete MTD network outperforms the random MTD network in all tests